EPA-440/2-79-031
August 1979
Economic Analysis of
Pretreatment Standards
for Existing Sources
of the
Electroplating
Point Source Category
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£
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QUANTITY
U.S. ENVIRONMENTAL PROTECTION AGENCY
Office of Analysis and Evaluation
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EPA-440/2-79-031
August 1979
Economic Analysis of
Pretreatment Standards for
Existing Sources of the
Electroplating
Point Source Category
Contract No.
68-01-3996
Prepared for:
Office of Analysis and Evaluation
U.S. Environmental Protection Agency
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PREFACE
The attached document is a contractor's study prepared
for the Office of Analysis and Evaluation of the Environ-
mental Protection Agency (EPA). The purpose of the study
is to analyze the economic impact which could result from
the application of pretreatment standards established under
section 307 (b) of the Federal Water Pollution Control Act,
as amended.
The study supplements the technical study, Development
Document for Existing Source Pretreatment Standards in
The Electroplating Point Source Category, August 1979,
and the earlier Development Documents supporting the issu-
ance of interim final and final regulations under section
307(b). These documents survey existing and potential
waste treatment control methods and technologies within
particular industrial point source categories and support
the proposed pretreatment standards based upon an analysis
of the feasibility of these standards in accordance with
the requirements of section 307 (b) of the Act. The invest-
ment and operating costs associated with alternative control
and treatment technologies are presented in Supplement B to
the Development Document which is available for inspection
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Washington, D.C., 20460. The attached document supplements
this analysis by estimating the broader economic effects
which might result from the required application of various
control methods and technologies. This study investigates
the effect of compliance in terms of product-price increases,
effects upon employment and the continued viability of af-
fected plants.
The study has been prepared with the supervision and
review of the Office of Analysis and Evaluation of EPA.
This report was submitted in partial fulfillment of Contract
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table of contents
Page
Number
EXECUTIVE SUMMARY
I. STUDY METHODOLOGY 1-1
II. THE INDUSTRY II-l
III. POLLUTION ABATEMENT REQUIREMENTS
AND COSTS III-l
IV. SAMPLE CLOSURE RESULTS IV-1
V. ECONOMIC IMPACTS V-l
VI. LIMITS OF THE ANALYSIS VI-1
APPENDIXES
A - The Metalfinishing Job Shop
Sector Survey
B - The Printed Circuit Board Industry
Survey
C - The Captive Metalfinishing Industry
Survey
D - Sample Design and Survey Issues
E - Automated Financial Closure Methodology
F - The Pollution Abatement Cost Generating
Program
G - Validation of the Pollution Abatement
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INDEX OF EXHIBITS
Following
Page
I. EQUATIONS RELATING ESTIMATES OF 1-23
INVESTMENT FOR WATER TREATMENT WITH
GALLONS PER HOUR OF WATER TREATED
II. CLASSIFICATION OF FIRMS WITHIN THE 1-31
FINANCIAL CLOSURE METHODOLOGY
III. t-STATISTICS FOR ECONOMIC AND FINANCIAL 1-39
VARIABLES TESTED COMPARING CLOSURES AND
NON-CLOSURES (n = 36)
IV. BEST PRACTICABLE TREATMENT SYSTEM III-6
V. CAPITAL COST OF FILTRATION UNITS 111-10
VI. CAPITAL COST FOR CLARIFIERS WITH pH 111-10
ADJUSTMENT
VII. CAPITAL COSTS FOR CYANIDE OXIDATION III-ll
UNITS
VIII. CAPITAL COSTS FOR HEXAVALENT CHROME III-ll
REDUCTION
IX. RELATIONSHIP OF TOTAL SYSTEM FLOW RATE III-ll
TO INVESTMENT FOR LEAST COST (1) INDOOR
PLANTS-FILTER MODE
X. RELATIONSHIP OF TOTAL SYSTEM FLOW RATE III-ll
TO INVESTMENT FOR LEAST COST OUTDOOR
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INDEX OF TABLES
Page
Number
1-1 SAMPLE STRATA WEIGHTS 1-9
1-2 TOTAL NUMBER OF METALFINISHING JOB SHOPS 1-10
1-3 RESULTS OF MULTIPLE REGRESSION 1-44
II-l TOTAL AND PRODUCTION EMPLOYMENT
IN ALL JOB SHOPS AND IN THE INDIRECT
DISCHARGING SEGMENT ONLY 11-13
II-2 TOTAL AND PRODUCTION EMPLOYMENT IN ALL
PRINTED BOARD MANUFACTURERS AND IN THE
INDIRECT DISCHARGING SEGMENT ONLY 11-14
II-3 TOTAL AND PRODUCTION EMPLOYMENT IN ALL
CAPTIVE OPERATIONS AND IN THE INDIRECT
DISCHARGING SEGMENT ONLY 11-15
II-4 TYPICAL BALANCE SHEET ITEMS 11-25
II-5 VALUE OF SELECTED BALANCE SHEET ITEMS
ON A PER MAN BASIS 11-26
II-6 DISTRIBUTION OF SELECTED CAPITALIZATION
ITEMS BY SIZE OF FIRM II-2-7
II-7 SELECTED CAPITALIZATION ITEMS ON A
PER MAN BASIS 11-28
II-8 DISTRIBUTION OF PRICE BEHAVIOR BY
SIZE OF FIRM 11-31
II-9 SURVEY RESPONSES TO THE "JOB SHOP"
QUESTIONS 11-32
11-10 METALFINISHERS JUDGMENT OF THEIR CUSTOMERS'
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Page
Number
III-l
111- 2
III-3
III- 4
III- 5
V-l
V- 2
V-3
V-4
V-5
V-6
V-7
V-8
MEAN INVESTMENT CAPITAL TO MEET A
PRETREATMENT SYSTEM ARRAYED ACROSS
WATER USE CATEGORIES (GPD) 111-15
MEAN INVESTMENT CAPITAL TO MEET A
SYSTEM ARRAYED ACROSS METALFINISHING
EMPLOYMENT CATEGORIES III-15
MEAN INVESTMENT CAPITAL TO MEET PRINTED
BOARD MANUFACTURERS PRETREATMENT STANDARDS
ARRAYED ACROSS METALFINISHING EMPLOYMENT
CATEGORIES 111-16
MEAN INVESTMENT CAPITAL TO MEET A PRETREAT-
MENT SYSTEM ARRAYED ACROSS METALFINISHING
EMPLOYMENT CATEGORIES (536 Captive Facilities) 111-18
MEAN ANNUALIZED COST TO THE INDUSTRY OF THE
PRETREATMENT REGULATION (Arrayed by Wet-
metalfinishing Employment) 111-19
TOTAL PLANT CLOSURES IN THE JOB SHOP
SECTOR UNDER THE REGULATION ARRAYED BY
WMF EMPLOYMENT INTERVALS V-2
SALES AND EMPLOYMENT LOSSES DUE TO THE
REGULATION JOB SHOP CLOSURES ARRAYED
BY WMF EMPLOYMENT CATEGORIES V-2
SALES AND EMPLOYMENT LOSSES DUE TO THE
REGULATION JOB SHOP CLOSURES, SBA FINANCING
ARRAYED BY WMF EMPLOYMENT CATEGORIES V-3
ESTIMATED PLANT CLOSURES FOR PRINTED
BOARD MAKERS V-4
SALES AND EMPLOYMENT LOSSES FOR PRINTED
BOARD MAKERS V-5
PROJECTED TOTAL CAPTIVE CLOSURES BY THE
REGULATION V-7
EMPLOYMENT AND SALES EFFECTS OF CAPTIVE
CLOSURES DUE TO THE REGULATION V-7
TOTAL ECONOMIC IMPACTS OF PRETREATMENT
COMPLIANCE FOR THE METALFINISHING INDUSTRY
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EXECUTIVE SUMMARY
J This report presents an economic impact analysis of
the metalfinishing industry.^ The economic impact is that
due to capital investments in water pollution abatement
technology. JjThe primary measure of economic impact is the
number of potential plant closures due to these requisite
capital investments^^
For this summary, the following four points will be
developed:
Definitions and scope of the study
Data gathering and analytic methodologies
Descriptive information on the industry
Presentation of key findings (impacts).
1. THE STUDY IS RESTRICTED TO MUNICIPAL DISCHARGERS IN
THREE METALFINISHING PRODUCTION SECTORS
This report covers firms that belong to, or perform
processes common to the metalfinishing industry. These
firms are specifically involved with a discrete number of
production processes defined by the EPA as falling within
the Electroplating Point Source Category, and hence, regu-
lated under this guideline. The scope of the study is lim-
ited to those establishments which perform one or more of
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Electroplating of common metals
Electroplating of precious metals
Anodizing
Coatings, i.e., phosphating, chromating or
immersion plating
Chemical etching, milling and engraving
Electroless plating
Printed board manufacturing.
The regulations discussed in this report are EPA's Pre-
treatment Standards for Existing Sources in the Electro-
plating Point Source Category. Firms governed specifically
by Pretreatment Standards are those firms that now dis-
charge their effluent wastewater to a sewer that requires
chemical/biological treatment by a municipal or publically
owned treatment works (P0TV7) . Such firms are also called
indirect dischargers. In sum, the focus of study is that
universe of metalfinishing firms performing regulated pro-
cesses that discharge to POTW's and face compliance with
Pretreatment Standards.
The universe of metalfinishing firms is composed of
three production sectors. They are:
Job Shops—Independent, small (often family run)
operations that typically plate with copper,
nickel, chromium and zinc.
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Printed Board Manufacturers—Independent pro-
ducers of wire or circuit boards whose products
involve copper and electroless plating.
Captive Operations—Production centers, found
within manufacturing firms, that provide fin-
ishing services to the products of the parent
company.
These three sectors are studied independently in the
body of the report. Each is described as an economic en-
tity; costed for its pretreatment technology, and analyzed
for its expected impacts.
2. SURVEYS AND AUTOMATED IMPACT ROUTINES WERE THE PRIMARY
DATA GATHERING AND ANALYTIC METHODOLOGIES OF THE STUDY
This study is distinguished by the fact that virtually
all descriptive and analytic data came from primary sources.
Primary sources in this case are members of the industry
sectors for information pertinent to finances, production
processes and market conditions. Similarly, on the tech-
nical side, primary sources included pollution control
equipment suppliers for supplemental information on treatment
components and their costs.
There were three separate data gathering surveys.
The groups surveyed were:
Independent suppliers of metalfinishing services,
i.e., the job shops
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Independent producers of metal clad wiring or
printed circuit boards
Individual manufacturing establishments with in-
house metalfinishing capabilities, i.e., captive
operations.
All survey methodologies are written up in detail in
Chapter I and in Appendices A, B and C of this report.
Reviewing them here serves to set the findings of the next
section in perspective.
Job shops were contacted by mail in the winter
of 1976. Almost half of all listed metalfinish-
ing firms in the Dun's Market Identifiers File
were sent a questionnaire (2,221 of 5,551). Re-
turns came back from approximately 900 cases.
Usable mail returns numbered 444 of which 205 qualif-
fied as plant models for purposes of this report.
Captives were also contacted by mail in the early
spring of 1977. This was a population mailing to
some 8,800 firms in the Products Finishing sub-
scription list that met two criteria. They were
not independent job shops, and they provided data
to Products Finishing in the past suggesting a
regulated process was performed at the plant.
Returns came back from some 3,400 cases of which
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Printed circuit board manufacturers were identi-
fied through a two-step process. Underwriters
Laboratories furnished a listing of some 600 es-
tablishments or corporations that had submitted
a printed board product for testing. Their list-
ing was cross-checked against the Dun's Market
Identifiers File and produced some 300 matches.
Financial reports were ordered on all yielding
some 175 reports. These were screened and 100
firms contacted for detailed information.
This completes the brief description of the three sample
segments that define the industry of interest.
In addition to the primary data gathering surveys of
these industrial sectors comprising the industry, some small-
scale surveys were conducted to gather supplemental information:
Telephone interviews with commercial lending
officers to verify the appropriateness of key
financial criteria utilized in the automated
financial closure routine.
Telephone interviews with suppliers of pollution
abatement systems for the metalfinishing industry.
Of interest here was the correspondence of computer
generated equipment costs with professional quo-
tations .
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Telephone follow-up interviews with a sub-set of
study respondents to clarify the key financial
data of the study. This effort established that
the base year of the study was a "typical" year
for the industry as a whole.
Three additional study methodologies were required:
a method for applying the technical contractor's costs,
a means for predicting a financially vulnerable plant, and
a method for extrapolating closure results from the sample
to the population.
Costs were developed by the Technical Contractor
for the Agency's Effluent Guidelines Division,
using an automated cost program developed speci-
fically for this industry. From the early returns
to BAH's job shop questionnaire, 82 actual plants
providing detailed technical-production data were
selected for costing. Those 82 represented a
full distribution of job shops along key study
dimensions:
Processes
Water use
Employment
Size
Location
Lines
Sales
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While additional returns also could have been used
for technical review and costing the 82 were judged
a full and adequate data base.
Regression equations for unit costs as well as
flow allocation rules per component were then
derived by BA&H. This provided the analytic
tools for assigning costs to all other plant
models. A plant model was operationalized as
any survey respondent providing sufficient tech-
nical and financial data so that the plant could
be costed and tested for closure. There were
205 job shops, 40 printed board manufacturers,
and more than 600 captives which are plant models
and serve as closure test cases.
Closures were calculated by an automated financial
routine for both job shops and printed boards.
Captives, because their investment decision is
unique and because no detailed income statements
were requested, were handled through a different
analysis. The financial closure routine uses
reported income and balance sheet data to compute
a present cash flow situation and a projected
cash flow situation after the investment. Two
criteria must be satisfied for a firm to satisfy
the closure test. Its future coverage ratio must
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be at least 1.5 to support securing a bank loan
or failing that, the owner might choose to increase
his equity to help purchase the equipment as long as
his net compensation (salary, bunus, and profit after
taxes) is at least $15,000.
Closure rates for the population were determined
to be the same as the overall sample closure
rate. Tests were run to identify significant
differences in closure rates by the size of the
firm (i.e., testing by employment, sales and water
use). No significant differences were found.
Additional tests were run between survey respon-
dents and non-respondents and between the model
and non-model plants to test for systematic dif-
ferences. Again, none were found that affected
closure rates. Therefore, the closure rate found
in the plant model analysis is extrapolated di-
rectly to the universe to project total industry
impacts.
This finishes the discussion of how the study proceeded
methodologically. Summaries of major findings appear in
the next section.
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3. THE INDUSTRY CONSISTS PRIMARILY OF SMALL OPERATIONS
MEASURED BY SALES, EMPLOYMENT AND WATER USE
The following three sections provide summary descrip-
tions of selected descriptive data on each segment. Data
are presented first for all firms within the sector and
then for just the regulated indirect discharging segment
of the sector.
(1) Almost 3,000 Job Shops Are In the Electroplating
Point Source Category
The data base of the 1977 Dun's Market
Identifiers File and the 1972 U.S. Census
of Manufacturers estimate the population of
job shops at approximately 5,000 firms.
By the patterns of responses to the job shop
survey (Appendix A) more than half, or 2,941
firms do processes covered by these regulations.
Of this number more than 90%, or 2,734 com-
prise the indirect discharging segment, and
are the main focus of study.
On the basis of total employment, these 2,941
firms employ 69,700 people of which 52,275
are production employees in wetmetalfinishing.
For the indirect discharging segment the
numbers are 62,800 and 46,800 respectively.
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Only 14% of the job shops sell $1 million
or more annually with 72% of all firms sell-
ing $0.5 million or less a year. Average
sales at the plants are $580,000 with total
industry output estimated at $2.1 billion
annually. Indirect dischargers are estimated
to generated $1.9 billion in sales.
At the plant level, a job shop uses water on
average at the rate of 38,7 00 gallons per day
of which 83% or 32,300 gallons per day is
water used directly in metalfinishing pro-
duction processes. For the industry as a
whole, total plant water use is on the order
of 114 million gallons per day with 95 million
gallons per day taken by production processes.
For indirect dischargers the values are 109
million gallons with 88 million gallons per
day for production processes.
(2) Printed Board Manufacturers Are A Small Segment
of the Industry
Given that process group H of the regulations
of the Electroplating Point Source Category
is for printed board manufacturers all iden-
tified firms in the population (400) are
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affected by this guideline, with 327 estimated
to be indirect dischargers.
Printed board shops are reported to be, on
average, larger than the typical job shop.
Mean total employment is 60 men with 35 in
production finishing. For the industry as
a whole, this accounts for some 23,300 people
with 13,700 part of producing the printed
boards. For the indirect discharging segment
only these 327 producers employ 20,600 people
with 11,900 people in board production.
These independent manufacturers have larger
per plant sales than do the job shops. Only
35% sell under $0.5 million annually with
43% selling over a million. Plant sales on
average are $1.5 million with total industry
sales estimated at $610.4 million. Indirect
dischargers have annual sales estimated at
$494 million.
The mean total plant water use of this sector
is 21,900 gallons per day. Of this amount,
86% or 18,800 gallons per day are from pro-
duction processes. For the industry as a
whole, 8.7 million gallons per day are used
of which 7.5 million gallons are for metal-
finishing processes. For indirect dischargers
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the figures are 7.2 million and 6.1 million,
respectively.
Captive Operations Drive the Demographics of the
Industry
Survey results suggest that 47% of all cap-
tive operations do processes covered by these
regulations. This defines a population of
6,077 firms, of which 4,722 are indirect
dischargers.
Mean total employment of these firms is 660
men for a plant work force of slightly below
4 million men. But with 20 men per firm as-
signed to metalfinishing, the production
workforce is estimated to be 117,500. In-
direct dischargers represent 2.9 million
people with 87,000 in wet metalfinishing.
Total sales at the plant level average $20.1
million. Of this amount, however, 54% re-
flects sales of goods with metalfinishing.
Therefore, sales of metalfinished goods are
$10.9 million. Given that the finishing
cost of these goods does not exceed 10% of
the total production cost, the value added
by metalfinishing is estimated at $1.1 million
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per plant. For the total industry, this is
$6.7 billion annually. For the indirect dis-
charging segment, metalfinishing is a $5.1
billion industry.
In terms of plant water use, a firm with a
captive operation uses 808,000 gallons per
day. Of this total, 35% or 277,000 gallons
is used by the captive finishing operation.
On a daily basis, all 6,077 establishments
with captives use 4.9 billion gallons with
the captive operations requiring 1.7 billion
gallons. Indirect dischargers should account
for 3.8 billion gallons with 1.1 billion
gallons used in finishing operations.
4- COMPLIANCE WITH THE PRETREATMENT STANDARD COULD AFFECT
SOME TWENTY PERCENT OF ALL INDEPENDENT ESTABLISHMENTS
AND THREE PERCENT OF THE CAPTIVE OPERATIONS
The points listed below capture the key estimates and
findings of the study. All costs and impacts reported below
are only for the indirect discharging sector of each industry
segment.
For plants whose metalfinishing process water
flow is below 10,000 GPD the treatment technology
for pretreatment is:
Destruction of cyanide amenable to chlorina-
tion by single stage chlorination
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Precipitation and clarification of lead,
cadmium and cyanide.
For plants above the 10,000 GPD process water
level, the treatment technology consists of:
Oxidation of cyanide in two stage alkaline
chlorination
Reduction of hexavalent chromium (where necessary)
Precipitation and clarification of cadmium,
lead, copper, nickel, chromium, zinc and
silver.
Total investment costs for the three sectors to
meet Pretreatment standards are $1,340 million.
Of this total, jobbers face $187.6 million, printed
board $18.5 million and captives $1,134.4 million.
On a ten-year annualized basis, the total for
the industry is $493.9 million. Again for jobbers,
printed board makers and captives, the figures
are $62.5 million, $6.8 million and $424.6 million,
respectively.
Closures are possible in 19% of the job shops and
in 3% of the printed board firms. No closures
are predicted in captive operations although 3%
might divest the operation and purchase finishing
from jobbers. On an overall basis, 17% of the
independent operations and 9% of all operations
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within the Electroplating Point Source Category
may close as a result of pretreatment standards.
Other economic effects rest with price rises and
unemployment. Jobbers are expected to increase
price 7% and printed board makers 2%. Unemploy-
ment in the job shop sector could be 9,650 persons
and 321 positions in the printed board industry.
This corresponds to 14% and 1.3% of the jobs in
each sector.
No measurable impact on balance of trade levels
or on communities is anticipated because finish-
ing is neither an international commodity nor a
major regional employer.
Price impacts on the finished goods due to capital
investment in pretreatment equipment are expected
to be on the order of 1%. Given that no industrial
sector attributes more than 10% of the cost of the
finished good to metalfinishing, cost increases
of up to 10% in finishing should be reflected in
small point of sale price increases.
All impacts were computed on the basis of two
sources of capital; commercial bank loans, and
a special loan program such as the SBA. Were a
special loan program readily accessible to the
metalfinishing industry, job shop closure rates could
be one-fourth that predicted by regular financing.
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*****
This completes the discussion of the key points of
the study. The subsequent chapters of the report provide
the substance of each issue presented herein.
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I. STUDY METHODOLOGY
This chapter presents the several study methodologies
developed for assessing the impact of pollution control
capital investments on the metalfinishing industry.
As noted in the prior Executive Summary, the study
focuses on indirect dischargers; i.e., those firms now
discharging effluent wastes into a publically owned sewer
system. In addition, the relevant firms are only those now
performing finishing processes defined within the Electro-
plating Point Source Category. This restricts the industry
of interest to all independent metalfinishing job shops,
Printed Board makers, and general manufacturing establish-
ments with internal finishing operations (captives) covered
by this regulation.
Analytically, the study requirements are captured by
the following questions:
How many such firms are there?
What are their present economic, market and
production characteristics?
What type of (pre)treatment system must they
install?
What are the costs of such systems?
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How will making such investments affect the
structure and operating economies of the industry?
These questions are covered for each industry segment in
sections A, B and C in this chapter.
i. FIVE SEQUENTIAL OPERATIONS DEFINE THE STUDY
An overall study plan for conducting the analysis was
developed. It consists of the following five sequential
steps:
Survey the segments of the industry to gather
descriptive information
Designate a group of survey respondents as model
plants against which costs can be arrayed and
impacts assessed
Develop pretrcatment pollution control costs
through modelling and verify the applicability
of those estimates for specific cases
Design a tool capable of incorporating relevant
fiscal and cost data such that accurate predic-
tions of financially impacted firms can be made
Establish a means for scaling sample based ob-
servations to the universe of affected firms.
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2. EACH SEQUENTIAL OPERATION OF THE STUDY REQUIRED
ITS OWN DATA GATHERING OR APPLICATION METHODOLOGY
This study is a fresh look at the industry. None of
the descriptive information on the size, composition or
economics of metalfinishing, whether available through
secondary sources or prior studies has been used here. The
goal of the study was to generate new data throughout. The
methods for gathering or applying data for each segment of
the industry, metalfinishing job shops, printed board makers
and captive metalfinishers are presented on the following
pages.
A. THE SURVEY OF INDEPENDENT
(JOB SHOP)
METALFINISHING ESTABLISHMENTS
This section describes the method and design of the
survey of metalfinishing job shops. Also presented here
are the strategy and results of a follow-up phone survey
to non-respondents. The manner in which these results were
used to generate the estimate of the regulated population
is also presented. In Appendix A the survey instrument and
the raw field data appear.
1. Design
The approach taken in this survey was a mail question-
naire followed by a follow-up telephone interview to a sample
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of establishments not responding to the mail phase. A mail,
rather than a telephone or personal survey, was planned
because of the nature of the data elements sought in the
inquiry. Detailed and comprehensive information regarding
production line configurations, water usage, employment sta-
tistics, and financial data were needed. Such figures are
not normally readily accessible in an interview situation
and often require review and consultation with others. The
mail approach affords respondents an opportunity to search
out and to consider thoughtfully their written replies. Pre-
vious studies among members of this industry show that
respondents can and do answer even the most detailed and
searching questions in a mail survey. The telephone follow-
up with non-respondents was included as an essential second
step to determine whether or not these establishments dif-
fered along key parameters from those responding to the mail
survey. Because plant size differences were noted between
mail respondents and telephone respondents, a means of weight-
ing mail results to reflect population parameters was developed.
2. Method
Firms providing electroplating and metalfinishing
services are listed in SIC (Standard Industrial Classifi-
cations, Office of Management and Budget) 3471 and 3479. There-
fore, the universe under investigation in the study was
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defined as all firms listed in the two SIC's that currently
performed those manufacturing processes covered by the regu-
lations .
The most recent and complete listing of such firms
available at the start of the study was the Dun's Market
Identifiers File (DMI) purchased by the U.S. EPA from Dun
and Bradstreet. Contained in the DMI were 5,551 names of
organizations whose primary SIC is either 3471 or 3479.
This listing of 5,551 was ordered first by the size
of the company (using number of employees) and then, within
size categories, ordered by state and then alphabetically.
A survey design was employed that systematically
sampled from the universe using a fixed interval and a
random starting point. By employing a 2.5 interval and
going through the list, a sample universe of 2,221 estab-
lishments was derived.
3. The Instrument
Prior analyses, client discussions, and coordination
with the metalfinishing industry reinforced the conclusion
that considerable information was needed for systematic
economic impact analysis. The data would have to be gathered
via the mail. The instrument had to be a convenient self-
administered questionnaire. To this end, the following
developmental steps were followed. The study team:
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Solicited descriptors of technical and production
variables from the technical contractor. In this
way, data would be gathered from which pollution
control costs could be developed.
Provided drafts of the instrument to the industry's
association, the NAMF (National Association of
Metal Finishers). Their comments contributed
directly to the form, content, and length of the
final instrument.
Reviewed the early drafts with Booz, Allen's sampl-
ing survey division, National Analysts. Their
contribution went far beyond the duties of admin-
istering, coding, and scoring the returns. On
early drafts, they reviewed critically the language,
format, and lucidity of all items.
Prior to the first mailing the instrument was
tested on a subsample of 12 firms located in
New Jersey. This effort was conducted to ensure
that directions were self-explanatory, items clear,
and data obtainable. Valuable information was
gathered by sitting with a respondent and "walking
him through" all items. Several changes in the
instrument's form and length were made as a re-
sult of this pre-test.
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4. Execution
At the end of this development phase the final instru-
ment was 14 pages long and covered the topics of:
Production activities
Market conditions
Technical operations
Financial conditions
Treatment requirements
Investment options
In October, 1976, all 2,221 establishments were mailed
a questionnaire with cover letters from both the NAMF and
the Agency. A postage paid return envelope was enclosed.
Replies were monitored as received by National Analysts
and when the response levels diminished to fewer than two
to three a day, a second mailing went out to the non-respondents.
Again, a cover letter and a return envelope accompanied each
questionnaire.
5. Follow-up
The results of mailing to 2,221 are shown below.
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Result
Number of Sample Plants
Respondents
687
Subject to regulation
Out of scope
444
243
687
Undeliverables or
Not Classified
154
Undeliverables
Not Classified
143
11
154
Nonrespondents
1380
Total Sample
2221
Replies from 687 cases yielded a 31% response rate
and gave a rich analytical data base. But 1380 cases
did not answer and a follow-up telephone survey was de-
signed to determine whether non-response bias existed.
The telephone follow-up survey of the mail non-respondents
was conducted according to a sample stratified by employment
at the plant location as given by D&B. The weights, which
are used to extrapolate the telephone survey results to
the entire group of mail nonrespondents, are computed by
taking the reciprocal of the probability of selection within
strata and then adjusting for nonresponse to the telephone
survey. For each stratum, the probability of selection is
determined by the ratio of the number of plants in the
telephone sample to the number of mail nonrespondent plants.
The adjustment factor, which is multiplied by the reciprocal
-------
of the selection probability to obtain the weight, is com-
puted by adding unity to the ration of telephone nonrespon-
dents to the number of telephone respondents plants in the
same stratum. This factor adjusts the telephone respondents
to account for telephone nonrespondents, and is given by the
equation:
Weight =
No. of mail non-respondents
No. in telephone sample-No. of telephone
non-respondents
Quantities necessary to complete these computations are given
in the summary table below:
Table 1-1
Sample Strata Weights
D&B Employment Mail Telephone Telephone
Strata Nonrespondents Sample Nonrespondents Weight
1
2
3
4
5
6
7
8
9
(1-4)
(5-9)
(10-19)
(20-49)
(50-99)
(100-249)
(250+)
(zero)
(missing)
378
289
267
208
70
24
6
10
127
1,379*
124
57
47
19
20
6
2
3
42
320
6
7
1
2
1
1
0
2
28
3. 26
5.66
6.68
11.55
3.88
4.68
6. 00
3. 33
3.18
* Note that the total of mail nonrespondents in this table does not
agree with the same total in the previous table. This minor dis-
crepancy is due to one case being missing from the file on which
the weights are based.
The results of the mail and telphone survey were ex-
trapolated to the factor sample by applying the weighting
-------
to each of the 444 in-scope mail responses. A second extra-
polation to the entire D&B sampleing frame is accomplished
simply by multiplying by (5551/2221). This yields a final esti-
mate of the total population of independent job shops falling
within this regulation. This estimate is arrayed below.
Table 1-2
Total Number of
Metalfinishing Job Shops*
Size of
Firm** Total POTW***
1-4 1,156 1,045
5-9 682 658
10-19 546 524
20-49 357 339
50-99 159 142
100-249 41 26
Total 2,941 2,734
* Covered by Electroplating Point Source
Category Regulation
** Measured by wetmetalfinishing production employees
*** Discharging to Publicly Owned Treatment Works
B. THE PRINTED BOARD
MANUFACTURERS SURVEY
This section presents the method and design of a data
gathering survey of independent manufacturers of Printed
Boards. The instrument used and the raw data are contained
in Appendix B.
-------
1. Design
If all independent Printed Board Manufacturers (PBM's)
fell within one or two generic SIC 4-digit classifications
structuring their survey would have been straightforward.
Although many PBM's do appear in SIC 3679 (Electronic Com-
ponents, not elsewhere classified) two problems are obvious
with tapping that data source:
Many firms in SIC 3679 produce products far dif-
ferent from printed circuit boards, e.g., phono-
graph needles, earphones, relays
Known producers of printed boards do not necessarily
assign their firm to SIC 3679. Many use SIC's
3643, 3691, 2511, 5065, 5081.
The approach developed for targeting a sample from an esti-
mate of the population was the following:
From Underwriters Laboratories a listing of all
manufacturers of printed board products was ob-
tained. This listing numbered some 600 company
names
Dun and Bradstreet submitted the UL list to their
files and generated a DMI list of 508 "matches."
This list of 508 contained firms that were branches,
headquarters and independent locations.
Paring the list still further to just the indepen-
dent producers yielded 357 names. For analytic
-------
purposes this defined the population of interest.
Subsequent analysis suggested a somewhat higher
estimate of the universe, set at 400.
2. Method
With access to the DMI list of more than 350 firms, data
were available that could enable either a mail or phone sur-
vey to be conducted.
Of primary importance to the survey effort was to
obtain sufficient financial data for the automated closure
routine. The mail survey to jobbers had succeeded in gen-
erating financial data, but 6 to 8 weeks for a mail effort
were not available. In addition, there was little reason
to expect that a complete telephone survey which also sought
financial data could be successful.
The study method, then, was a synthesis of two methods.
A phone survey was part of the design because it yields data
immediately, but financial items would not be sought in
the interview but obtained directly from the Dun's reports.
The latest financial reports on approximately half the
identified population were purchased. This yielded a ran-
domly generated group of 190 firms all possessing financial
records. Perusal of these records showed slightly more than
100 provided values for enough account categories to develop
complete and consistent balance sheets as well as sales and
-------
profit data. This was the sample sub-group of primary in-
terest, and the group targeted for first contact.
All firms for which satisfactory financial records
existed were defined as the segment of the universe to be
contacted. This pre-screening of the sample assumed two
risks. One, there is a certain probability of under-
representing smaller firms since they seem to be less likely
to volunteer their statements to D&B. A second is the pos-
sibility that those firms offering data are overstating their
condition since no validation or certification of the records
is offered by D&B. While these biases could be self-canceling,
the fact remains that the sample is neither fully stratified
nor randomly drawn. However, it was the best available
under the circumstances.
3. Execution
A telephone interview guide (Appendix B) was developed
by Booz, Allen & Hamilton and the client. In addition, the
Technical Contractor was consulted for guidance on the pro-
duction and process items. Brevity guided the effort. Each
interview took fewer than 20 minutes to complete.
A team of special Booz, Allen & Hamilton consultants,
working for a week, made all the calls. Each call went
directly to the individual shown on the D&B listing as the
owner, president or chief officer of the establishment.
-------
Calls from the list of 190 continued until 100 inter-
views were completed. Reviewing all financial and technical
data for accuracy yielded a sub-sample of 40 plant models
that were used for estimating compliance burdens and closure
rates for the population.
C. SURVEY OF MANUFACTURING
ESTABLISHMENTS WITH
IN-HOUSE CAPTIVE
METALFINISHING OPERATIONS
This section presents the issues involved in the design
and execution of a data gathering effort in the captive metal-
finishing sector. Of specific interest here are the special
considerations of this sector that delineated the study ap-
proach. Appendix C contains the study instrument and all
the raw field data.
1. Design
As in the study of the Printed Circuit Board industry,
the key starting point in the survey of captive operations
was to define the universe. Essential to any sample design
is knowing the totality of all cases defining the population
from which a sample can be drawn.
The difficulty with respect to targeting a study of
captives is that any manufacturing establishment that pro-
duces a durable good might have applied surface finishing
-------
covered by these regulations. Consequently, establishments
with captive operations could appear throughout the indus-
trial manufacturing sectors covered by the U.S. Census of
Manufactures. This defines a universe in the hundreds of
thousands.
Resolution of this problem was provided through contact
with the publishers of Products Finishing magazine. People
knowledgeable about this industry, including the magazine's
publisher, maintained that it was widely read in the indus-
try; that its subscription list includes the vast majority
of establishments involved in metalfinishing; and prior sur-
veys by the magazine had already recorded the primary finish-
ing processes of the subscribers. An added reason for work-
ing with the Products Finishing list was that it served as
the source data for the National Commission on Water Quality's
estimate of 60,000 - 80,000 captive operations. The list,
therefore, was regarded as the best single estimator of the
universe of establishment with captive operations.
Procedurally, the survey of the captives was done as
follows:
Names and addresses of firms were not to be seen
by the Agency, or by BA&H. Mailing labels were
provided under the assurance that company names
would not be recorded in any fashion.
-------
Mailing was to occur at a single point, with no
means for second mailings, follow-ups or subse-
quent contact.
Both conditions were met.
2. Method
In October 1976, Products Finishing provided Booz,
Allen a card deck containing 21,975 records, each record
representing one firm. From the code sheet accompanying
the deck, it was possible to delete all establishments whose
primary SIC was either 3471 or 3479. This eliminated all
job shops from the population. Next, firms doing painting
only, and all firms doing only finishing processes outside
the Electroplating Point Source Category were eliminated.
This yielded a sub-set of subscribers which, on the basis
of information provided to Products Finishing magazine,
should be manufacturing plants with in-house finishing op-
erations doing finishing processes under this regulation.
There were 8,87 4 such establishments that defined the pop-
ulation of interest.
-------
The months of January and February 1977 were spent in
developing the questionnaire instrument. Several key deci-
sions were made:
Detailed financial information would not be re-
quested in the instrument because of the size
of some of the parent corporations, e.g., Ford
Motors, General Electric.
Detailed line descriptions and production process
information were also omitted because treatment
costs could be modelled by process water use
coupled to generic finishing processes, e.g.,
anodizing, chromating, common metals plating.
Freedom to divest the in-house operation was
judged a key factor so special attention was given
to the captive operation, relevance of the oper-
ation to on-going production schedules, the avail-
ability of outside finishing and the probability
of changing finishes or doing without metalfinish-
ing altogether.
The instrument (See Appendix C) went through five versions
before it was ready for mailing. Copies went to several
outside sources for critical comments. Providing their
critiques were Products Finishing editors, a director of
environmental engineering at a major corporation and an
academic researcher familiar with the industry. By early
March, 1977, the survey was ready to mail.
-------
3. Execution
On March 2, 1977 questionnaires were mailed to each
of the 8,874 establishments targeted as the relevant popula-
tion. The date requested for return was March 25. Due to
the fact that several firms called explaining that the ques-
tionnaire reached the "right" individual as late as March
20-21, the survey was kept open until April 8, 1977.
Questionnaires were received from 3,450 firms in the
sample for a response rate of 39%. The most interesting
finding from the returns is that 1,836 respondents (53%)
said they did not do a finishing process listed for the
Electroplating Point Source Category. There were 1,614
returns that yielded full and useful data.
*****
This completes the discussion on the three surveys
done for this economic analysis of the metalfinishing in-
dustry .
-------
3. POLLUTION CONTROL COSTS WERE DEVELOPED BY COMPUTER
APPLICATION OF FIELD DATA AND THEN MODELLED FOR
ECONOMIC IMPACT ANALYSIS
Appendix F to this report presents the logic, data
requirements and assumptions of the computer model developed
by the Technical Contractor for costing a Pretreatment Tech-
nology for the metalfinishing industry. The focus of this
section is restricted to the method employed by Booz, Allen
to synthesize these costs for use in the economic impact
analysis.
(1) The Technical Contractor Developed Pollution
Control Costs for 74 Job Shops
When some 300 job shop survey questionnaires had
been returned, they were reviewed for diversity, com-
pleteness of data and representativeness. Eighty-two
plants were chosen which provided sufficient data
for costing and which represented at least three to
four other returns. These 82 plants were considered
"model plants" for costing purposes and for their
cross-sectional representation of the industry.
The 8 2 plant records were submitted to the Tech-
nical Contractor for costing. Due to inconsistencies
and/or omissions on 8 records, costs were developed on
74 plants. The technical contractor returned to BAH
very detailed cost estimates for all 74 plants. Each
estimate illustrated the changes in costs under assump-
tions of different water use and compliance requirements.
-------
(2) Rules Were Developed for Relating the Equipment
Needs of the 74 Plants to the Plant Models Used
for Impact Analysis
More than 240 job shop respondents provided the
data needed for the fiscal-economic impact work; of
the 240 some 40 also were from the original costing
group of 74. Given that the goal of the analysis was
to model impacts on a large sample of plants, BAH worked
with the Agency and the technical contractor in relating
the costs developed for the 74 plants to cost equations
for all other usable plant models. Inspection of the
proudction operations of the 74 plants yielded one set
of decision rules for determining any plant's pollution
abatement needs.
Plants involved only in sulfuric acid anod-
izing, and/or nonelectroplating metalfinish-
ing operations (except chromating and bright
dipping) were likely to require pH adjust-
ment only to meet BPT requirements.
Plants involved only in copper, tin, cadmium,
zinc, precious metalplating or bright dip-
ping or a combination thereof were likely
to require cyanide destruction and pH ad-
justment equipment.
Plants involved only in chromium plating,
chromic acid anodizing, chromating or a
combination thereof were likely to require
-------
hexavalent chromium reduction and pH adjust-
ment equipment.
Other plants doing combinations of these
operations were likely to require all three
major systems: cyanide destruction, hexa-
valent chromium reduction, and pH adjustment.
Line segregation is a cost element if at
least two pieces of control equipment are
required. The cost of line segregation is
halved if only two pieces are specified or
if at least one piece of equipment is already
in place.
All plants plating with metals regulated under
this guideline will be required to treat the
metals bearing stream with clarification
filtration equipment.
(3) Rules Were Also Established for Allocating Flow
Volumes Through Each Component
Inspection of the 7 4 model plants revealed that
different types of finishing operations have character-
istic flow levels to their pollution control equipment.
This breakdown also appears in Appendix G.
The decision rules for allocating metalfinishing
process water flow to the various waste treatment com-
ponents appear below:
-------
Plants requiring installation of cyanide
destruction and pH equipment tend to have
about 56% of their metalfinishing water
flowing to the cyanide destruction unit.
Plants requiring installation of hexavalent
chromium reduction and pH adjustment equip-
ment tend to have about 2 3% of their metal-
finishing water flowing to the chrome reduc-
tion unit.
Plants requiring installation of systems fall
into two categories:
Plants which perform more than six
operations tend to have about 62% of
their metalfinishing water flow in the
cyanide destruction unit and about 4%
of their metalfinishing water flowing
to the hexavalent chromium reduction
unit.
Plants with six or fewer operations
tend to have about 8% of their metal-
finishing water flow to the cyanide
destruction unit and about 10% flowing
to the hexavalent chromium reduction
unit.
In all cases all the metalfinishing water
flows through the pH adjustment unit.
-------
(4) Cost Equations Per Component Were Developed as
a Function of Flow
Using the costs per component provided by the
Technical Contractor (fully built-up reflecting site
preparation and installation), and applying the flow
allocation rules per component shown above, a series
of predictor cost equations was derived. Exhibit I,
on the following page, presents these equations. Data
are presented for the costs, and then for the results
of a regression using the formula against the flow
data of 74 plants.
The equations account for between 60 and
80% of the variability betweeen investment
cost estimates and volume of water treated
in their appropriate regression of flow.
The pH adjustment equation was derived from
the computer model cost estimates as well
as from industry sources such as manufac-
turers and distributors of neutralization
systems.
Sludge haul and treatment costs were com-
puted at $.25 per gallon applied to 1% of
the total flow into the clarifier-filter.
-------
EXHIBIT I
U.S. Environmental Protection Agency
EQUATIONS RELATING ESTIMATES OF INVESTMENT FOR
WATER TREATMENT WITH GALLONS PER HOUR OF WATER TREATED
Subsystem
Hexavalent Chromium Reduction
Cyanide Destruction
pH Adjustment
Line Segregation
Clarifier
Diatomaceous Earth Filter
* Notes on Equations
1. Investment value in 1977 dollars.
2. GPH is the metalfinishing water to specific unit.
3. GPH is the total metalfinishing water of the plant.
Equation*
Investment ($) = 8,400 GPH 0.17
Investment ($) = 19,000 + 15.2 GPH
Investment ($) = 14,700 +1.0 GPH
Investment ($) 210 GPH 0.5
Investment ($) = $16,000 GPH 0.15
Correlation Statistic
0.8
0.9
0.9
Investment ($) = $4,065 GPH 0.33
-------
4- CLOSURES IN THE JOB SHOP SECTOR AND IN PRINTED BOARD
MANUFACTURING WERE PREDICTED FROM AN AUTOMATED CLOSURE
ROUTINE
A firm is labeled a potential closure if, for a given
pollution control system under a set of assumptions about
price increases and capital costs, the firm cannot finance
the investment through cash flows or through securing a
loan.
It is clear that such a determination requires informa-
tion on multiple variables; e.g.,
Cost of capital
Payback period
Depreciation schedules
Capital needs
Price increases
and the capacity to alter any one of them at will. An
automated model of plant behavior was needed that captured
both alternate policy options and fiscal conditions at the
plant level. Working with an automated routine capable of
reflecting changes to these objective functions was an im-
portant part of conducting a systematic industry impact
study. The method by which the closure routine developed
and its special features appears below. This primary routine
was utilized in predicting closures for the independent
metalfinishing job shops, and for the Printed Board Manu-
facturers. The closure methodology for the captive sector
-------
s significantly different and presented in the next major
ection.
(1) Calculating Costs and Modeling the Plant's Freedom
to Raise Prices Are Two Key Determinants of Closure
Two operations in the closure routine are parti-
cularly pertinent to the estimation of industry impacts.
One is the calculation of requisite price increases
needed to cover the incremental costs of pollution
control. The second is the modeling assumption of
how much of the new cost can be reflected as increased
price. The discussion here is limited to pricing
practice in the industry.
There are basically two models to pursue.
Pricing will be uniform in the industry with
price limits set by either the least cost,
average cost or marginal (high) cost pro-
ducer.
Pricing will be plant specific with each
producer raising his prices by precisely
the amount needed to cover costs independent
of the pricing decision of his known compe-
titors .
The choice of price scenario is pivotal to both
the magnitude and thereby to the significance of impacts
-------
predicted for the industry. While it is not known
through our surveys whether one or the other scenario
universally holds, there is a strong basis for arguing
that it is the latter of the two scenarios.
Uniform pricing in which incremental cost
pass throughs are limited by one type of
producer is found in those industries with
many anonymous producers of undifferentiated
goods; i.e., agriculture. Here the more ef-
ficient high volume producers directly in-
fluence the market price of the product.
Metalfinishing is characterized by a large
number and variety of producers some of-
fering specialized services to a few steady
customers, others performing multiple services
to a rapidly changing, diverse customer base.
The assumption of uniform pricing across
the industry would not be applicable.
Given the choice of an individualistic pricing
model, the second key assumption involves determining
how much of an incremental cost can be passed through
to a customer as a price increase. Respondents pro-
vided data on their pricing history and not only does
it confirm the assumption of plant specific pricing
behavior, it helps establish the ceiling on probable
future price increases.
-------
After recent price increases only 27.5% of the
plants reported volume declines.
Metalfinishers provided data on their esti-
mated future price increase; not only was
there a large range in values (0 - 50%), ar-
guing further for the lack of price leadership,
but the sample mean of 12.8% exceeds the esti-
mated average price increase for the industry
to come into compliance.
Metalfinishers also provided data on their
customers' reactions to price increases.
These data (pp 024-027 Appendix A) show clearly
that in the face of price increases most cus-
tomers cannot shift to captives, or eliminate
finishing on their products or start their
own finishing lines in-house.
For the purposes of this analysis each job shop
plant model will increase price by precisely the amount
of its incremental cost. This allows each plant to
increase revenues by the same amount as its annual
costs of compliance. This is operationalized in the
closure routine as the "full cost pass through" con-
dition. For the sample as a whole (205 plant models)
this pricing assumption yields an average, sales weighted,
price increase of 7.0 percent.
-------
(2) Cost of Capital for the Pollution Control Loan
Is a Related Study Parameter of Importance
The interest rate that metalfinishers would be
charged for a loan is another key analytic variable.
At the time of the survey, and in subsequent reviews
with loan officers, the interest rate charged by a com-
mercial bank was known to be in the 8% to 12% range,
depending primarily on prior borrowings and profitability
of the firm. Initially, the interest rate for purposes
of the study was 10%; however, critics suggested a
higher rate would more appropriately reflect trends
and conditions in money and credit markets. Accordingly,
for this final economic impact analysis the cost of
capital was set at 12%. Although fluctuations in in-
terest rates will continue, and selecting any one value
may be outmoded by the time a report appears in print,
one very important feature of this analysis must be
borne in mind:
The principal measure of plant vulnerability
employed in this industry impact analysis
is the plant's coverage ratio: a measure
of the ratio of cash generated to obligations.
Increases in interest rates are reflected
in both parts of the ratio, and projected
impacts are relatively insensitive to changing
levels to the cost of capital.
-------
(3) Two Unknowns in the Closure Model Are the Invest-
ment Decisions of Owners and Bankers
Although specifying the financial variables for
a closure analysis is straightforward, it is consider-
ably more difficult to assign "absolute" minimum values
for these variables in predicting candidates for clo-
sure. This is particularly true in applying profit-
ability standards because little is known about the
minimum profit expectations of small businessmen such
as independent metalfinishers.
The data as reported in the survey provide a de-
parture point. Typical profits and owner's compensa-
tion were calculated on the sample and used to develop
profitability criteria for predicting closures. A
firm was considered to show inadequate profitability
(and, hence, appear as a candidate to close) if:
It made no profit, i.e., profit after tax
was less than zero
Profit after tax plus owners compensation per
owner who works full time was less than the
cutoff value—selected to be $15,000, or the
median family income in 1976.
These profitability values are based on the sample
returns and include a combined assessment of:
Evaluation of the decision from a general cor-
porate point of view
-------
Assessment of the likely reaction of a small
business that is owned and operated by an
individual or, at most, a small group of peo-
ple who:
Have other opportunities for both their
investment and time, namely they could
own another business or invest in real
estate and work full time for a salary
elsewhere
Consider, from their unique situation,
the increased risk in owning their own
business versus the independence, etc.,
of being their own bosses.
Credit rules applied by bankers to loan applicants,
on the other hand, are well defined and easily described.
In practice, issues such as longstanding banking rela-
tionships and personal guarantees are important. There
are minimum standards of quality that bankers apply
to the projected financial performance of a loan ap-
plicant and a large number of financial ratios taken into
consideration. For purposes of this model one variable, coverage
ratio is calculated to represent the firm's credit worthi-
ness. It is clear that selecting one loan criterion vari-
able is a simplification for modeling purposes. However,
coverage ratio is an excellent measure of a firm's cash
flow situation and capacity to support further debt.
-------
In the model, a firm was judged to be unable to obtain a
bank loan if its coverage ratio was less than 1.5. This
is fairly liberal, assuming the personal guarantee of
the owner that is typical for metalfinishing and other
small industries. A coverage ratio of 2.0 is the stan-
dard minimum without the owners' personal guarantee.
Banks would be extremely hesitant to lend to a firm with
a coverage ratio approximating 1.0. Firms at a 1.0
coverage ratio have a projected cash flow that is exactly
equal to operating costs plus loan payments; this cash
flow would not provide for temporary business downturns
or other considerations of risk.
(4) Three Types of Closures and Two Types of Non-
Closures Are Predicted
Consideration of the profitability and capital
access measures and values lead to the five classifi-
cations of pre and post-investment firms illustrated in
Exhibit II, following this page. The classifications are
based on the possible combinations of profitability
and capital access, which range from a firm's being
rated poor in both categories—the upper left hand cor-
ner of the illustration--to a firm's being rated very
good in both categories—the lower right hand corner
of the illustration. The five categories are defined
as follows:
-------
EXHIBIT II
U.S. Environmental Protection Agency
CLASSIFICATION OF FIRMS WITHIN THE FINANCIAL
CLOSURE METHODOLOGY
Poor
PROFITABILITY
Very Good
Poor
Capital
Access
V
Very Good
(1) Vulnerable Firm
on Pre-Investment
Basis
(2)
Candidate for Closure Due To
Lack of Capital Access
(3)
Non-Closure
with Equity
Infusion
(4)
Candidate for
Closure Due To Lack
of Profitability
(5)
-------
Baseline Closure Candidate (1)--Those firms
that on both a current and projected basis
showed inadequate profitability, which implies
that they are candidates for closure regard-
less of the installation of pollution control
equipment.
Candidate for Closure Due to Lack of Capital
Access (2)--Those firms that have coverage
ratios under 1.5 and that would require pro-
hibitively large equity infusions to secure
loans.
Non-Closure With Equity Infusion (3)—Those
firms that have poor capital access but could
obtain loans with an investment of a reasonable
amount of additional equity by the owner on
a one-time basis. In the model the equity
infusion rule is invoked by either purchasing
it outright, or enabling the coverage ratio
to reach 1.5. The test only "saves" the firm
if the return to the owner is at least $15,000.
Candidate for Closure Due to Lack of Profit-
ability (4)--Those firms that could secure a
loan but which might not because of inadequate
projected profitability.
Non-Closure (5)--Those firms with both ade-
quate profitability and adequate capital access.
-------
Classification of the 205 selected plant models into
those five categories is the basis for extrapolation of
candidates for closure to the entire industry.
5. A CAPTIVES CLOSURE ANALYSIS IS BASED ON OPERATIONAL
RATHER THAN FINANCIAL CONSIDERATIONS
It is presumed that a manufacturing establishment invests
in its own in-house finishing operation for reasons of op-
erational efficiency; i.e., it costs less to do it in-house,
production functions do not allow shipping goods out for
finishing and then carrying inventory, or there are no ac-
ceptable outside finishing services. A closure decision for
such plants has to be viewed, therefore, in light of the
operating constraints of the production cycle:
Cost of the pretreatment system relative to prior
capital investments in metalfinishing
Age and size of the in-house finishing operation
with respect to its capital replacement require-
ments
Operating budget for finishing with respect to
its proportion of total value added by finishing
Importance of the finishing operation with respect
to the total production flow.
In sum, the closure test for captive operations is
whether a firm is "free" to divest its captive operations.
-------
The analysis focuses on the likelihood that a firm could
economically as well as operationally divest itself of its
finishing given its present commitment to the process.
Firms likely to divest rather than make the investment in
requisite treatment systems are those which among other
things:
Have the freedom to send out finishing work or
produce goods with an alternate finish
Produce relatively few metalfinished goods, and
for which the added value of finishing is minor.
(1) Seven Variables Are Key to the Captives Closure
Model
Given that the rationale for a captives closure
is based on "freedom to divest", the study requirement
was to gather the data capable of identifying such
firms. There are seven key information items that
permit this analysis. They are the following:
Plant value added by metalfinishing: com-
puted as the product of the respondent's
answers to three items:
Annual sales at the plant
Percent of goods receiving metalfinishing
Cost of metalfinishing as percent of the
total cost.
-------
Corporate value added by metalfinishing:
computed as the product of answers to the
following:
Annual sales of corporation
- Percent of goods receiving metalfinishing
Cost of metalfinishing as a percent of
the total cost
Estimated pollution control annualized cost:
computed from flow rates, metals present,
production processes and value of equipment
in place
Estimated annual increase in the metalfinish-
ing budget: computed as the ratio:
Estimated pollution control cost
Metalfinishing annual budget
Estimated increase in metalfinishing value
added due to the cost of the pollution con-
trol equipment computed as the ratio:
Estimated pollution control cost
Plant value added by metalfinishing
Estimated increase in sales price of goods
receiving metalfinishing due to the cost of
the pollution control equipment: computed
as the term:
Pollution control Percent of all
cost X goods receiving
Sale at plant metalfinishing
-------
Estimated risk factor, which is the incremental
increase in the metalfinishing equipment
base represented by the investment in pollu-
tion controls: computed as the ratio:
Pollution control capital cost
Replacement value of
metalfinishing equipment
(2) The Seven Variables Yield Five Important Matrices
Data from the seven variables permit distribution
of all respondents along a scoring dimension. Combining
two scoring dimensions yields a matrix. All respond-
ents can then be assigned to a specific cell in a
matrix. Five unique matrices were considered parti-
cularly important for characterizing captives operations.
They are:
Plant sales x value added
Plant sales x WMF employment
Value added x WMF employment
Plant value added x plant sales
Value added x risk factor.
(3) Those Operations that Fall Consistently in Certain
Cells Are the Candidates to Divest the Finishing
Operation
From the preceding, a working hypothesis for iden-
tifying a closure is that a closure should occur in:
-------
Any plant for which the pollution control
cost is large with respect to the plant
value added by finishing; as well as large
with respect to the total prior capital
investment in finishing.
The sample of respondents is cast in succession across
the five tables holding the results of the prior run
constant. This yields the number of captives with
low value added and low sales, high investment, high
risk and high price increase. Running the analysis
sequentially yields the estimate of all cases that fit
all the criteria. The analysis is not applying a
closure model, as much as it is building a closure
profile.
6. METHODS FOR LINKING SAMPLE CLOSURE RATES TO THE POP-
ULATION WERE TESTED: THE METHOD USED IS EXTRAPOLATING
BY DIRECT PROPORTIONALITY
A critical issue in a sample survey study is estab-
lishing the link between sample findings and the population.
In normal survey work, this is handled by the techniques of
sampling design and inferential statistics. In economic
impact analysis the problem of linking the sample to the
population is particularly acute because survey results have
to reflect the probable economic viability of an entire in-
dustry. Therefore, it is necessary to establish that:
-------
Sample selection is unbiased
Respondents are similar to non-respondents
Test cases, e.g., model plants used for the clo-
sure analysis reflect the wider sample
Model plant findings, e.g., closure rates, can
be extended systematically to the population.
The first three concerns are covered both in prior
points in this chapter as well as in Appendix D. The focus
of this section is the last point: the derivation of the
method for extrapolating sample plant closure rates to the
total industry. Analytically, the steps undertaken to de-
rive the method were the following:
Identifying the elements that distinguish closures
from non-closures
Testing the predictive power of those distinguish-
ing elements
Establishing the mechanism that serves to extra-
polate sample findings.
(1) Comparison of Model Plant Closures With Non-
Closures Identified 26 Potential Discriminating
Variables
During the period that the automated closure routine
was being developed, closures were computed manually
for a subset of 36 model plants. These 36 plants were
chosen at random from all.models on which there were
complete and consistent financial statements.
-------
All variables on which data had been gathered
were examined to compare and contrast probable closures
and non-closures. Additionally, new variables were
created for the analysis built from the ratios of tech-
nical to economic and financial measures.
Applying tests for differences between means, 26
variables were identified that had the capability to
separate a plant judged likely to close from one that
should not.
Exhibit III, on the following page, presents these
data. Nine of these variables seemed particularly pro-
mising for further analysis because their mean- dif-
ferences were statistically significant at the .95 con-
fidence level.
Of these nine "best" potential discriminators,
only one (metalfinishing employment) covers the entire
sample. All the remaining variables are plant-specific
calculations which cannot serve as general links from
sample results to industry results.
(2) Results of a Multiple Step-Wise Regression Yielded
Three Variables Capable of Linking Sample Results
to the~Population
Building on the preceding, a step-wise multiple
regression was run on these nine plus 9 additional
potential predictors of a closure. All 18 potential
-------
EXHIBIT III
U.S. Environmental Protection Agency
t-STATISTICS* FOR ECONOMIC AND FINANCIAL VARIABLES
TESTED COMPARING CLOSURES AND NON-CLOSURES
(n - 36)
Sales
-1.45
Total Employment
-0.83
Metal Finishing Production Employment
-1.87 •
Total Production Employment
-0.97
-Percent Metal Finishing
-1.38
Water Use, Total
0.32
Water Use, Metal Finishing
1.42
Coverage Ratio
-2.03 •
Fixed Asset Turnover
-0.58
Cash Flow/Sales
-0.72
Cash Flow/Total Assets
1.56
Profit After Tax/Sales
-1.62
Profit After Tax/Total Assets
-2.37 •
Profit After Tax/Net Worth
-0.53
Profit After Tax and Owners Compensation/Net Worth
0.52
Cash Flow/Capitalization
-2.32
Current Ratio
-0.37
Debt Percent
0.96
Debt/Equity
1.49
Borrowing Power**
-3.05 •
Sales/Total Employment
-1.06
Fixed Assets/Total Employment
0.71
Water Use, MF/MF Employment
2.43*
Water Use, MF/Sales
2.55*
Water Use, MF/Total Assets
2.11*
Water Use, MF/Net Worth
2.39*
*The t-statistic applies to the difference between the mean values
for the subsamples of probable closures and non-closures across the
variables listed above. Negative statistics result where the mean
for probable closures is less than the mean for non-closures.
**Net Worth minus long term debt, i.e., the amount of additional debt
that would yield a debt-to-equity ratio of 1.0.
Note:
* Significant at the 95 percent confidence level for nl+n2-2 degrees of
freedom, where nl=the number of probable closures and n2»the number
-------
predictors were selected for strength of their t-value.
The dependent measure chosen for the regression was
borrowing power because its t-value was large (-3.05)
and because it is the closest surrogate measure of the
firm's capacity to make an investment in pollution con-
trol equipment. Ideally, the test would be run against
known closures, but in forecast work that is the main
unknown variable rather than the known discriminator
variable.
A step-wise regression has the capability to select
from among a cluster of independent variables that one,
single variable which, by itself, best predicts to
the dependent variable. Holding that first variable
constant, the program searches for the second next
best independent variable, which in combination with
the first, predicts to the dependent variable. The
program continues in this step-wise fashion until 100%
of the variance about the criterion variable is ex-
plained, or until the combined net predictive power
of all the independent variables is exhausted. The
results of the regression appear in Table 1-4, on the
following page. Several outcomes of the regression are
quite important:
Total employment was the very poorest pre-
dictor
-------
TABLE 1-3
RESULTS OF MULTIPLE REGRESSION
ALL CLOSURE
FILE DATA4 (CREATION CATE » 03/10/77) EP*-BA6H METAL FINISHING STUDY- FINANCIAL UPDATE
*********************** MULTIPLE REGRESSION *****
DEPENDENT VARIABLE.. BORROW eCRROWING POWER
SUMMARY TABLE
VARIABLE
MULTIPLE R
R SQUARE
RSQ CHANGE
SIMPLE R
DOLLAR
SALES IN DCLLARS
o.e<;448
0.48230
0.48230
0.69448
DBPR
DEBT PERCENT
0.80929
0.65496
0. 17266
-0. 36603
XPATSAL
ADJ PAT-SALES
0.81518
0.66451
0.00956
0.17097
XPATASS
ADJ PAT-TOTAL ASSETS
0.8257?
0.68181
0.0173 0
0.04631
XCFCAP
ADJ CASH FLOW CAPITALIZATION
0.82950
0.68806
0.00625
-0.02421
WFEMP
WET FINISHING EMPLOYMENT
0.83169
0.69170
0.00364
0.62868
MFWTA
METAL FINISHING WATER TOTAL ASSETS
0.83237
0.69234
0.00113
-0.02644
MFWSAL
METAL FINISH WATER- SALES
0.84690
0.71723
0.02440
-0.00503
MFHDAT
—
0.84966
0.72193
0.00469
0.29379
MFWNH
METAL FINISHING WATER- NET WORHT
0.05663
0.73382
0.01189
-0.09856
FATURN
FIXED ASSET TURNOVER
0.85837
0.73765
0.00384
-0.02408
PCOV
PROJECTED CCVERAGE RATIO
0.85944
0.73864
0.00099
0.31489
XCFTA
ADJ CAS FLCW—TOTAL ASSETS
0.85979
0.73924
0-00060
-0.01223
MFWWFE
METAL FINISH WATER- W F EMPLOYMENT
0.85994
0.73950
0.00025
0.00674
SALTEMP
SALES-TOTAL EMPLCYMENT
0.66008
0.73974
0.00024
0.06592
DBEQR
DEBT- EQUITY RATIO
0.86016
0.73987
0.00013
-0.29170
TEMP
TOTAL EMPLOYMENT
0.86020
0.73994
0.00007
0.61504
-------
Total sales is the single best predictor
Of the 10 best predictors, 3 are sample-wide
data items:
Sales
- Wetfinishing employment
Wetfinishing water.
These three, however, are only the first,
sixth, and ninth best predictors. All the
others are plant specific calculations which
cannot link sample findings to industry para-
meters .
Based on the preceding, three sample variables have
been identified as appropriate and potentially useful
for projecting sample closure results to the popula-
tion. The next step was to test their predictive
power.
(3) Chi Square Analysis Rejected the Use of Any of
the Three Variables as Predictors of Closure
Later in the analysis, model plant closures were
available under a variety of price, cost, and regula-
tory scenarios. These closure results were then ar-
rayed as a function of sales, wet metalfinishing em-
ployment, and metalfinishing (process) water use inter-
vals. In addition, cross tabulations on these variables
-------
were run so that closure levels within cells could be
tested. A Chi Square analysis revealed that there
was no systematic movement of closure rate by sizing
interval. This means that the probability of a plant's
closing is independent of how large that firm is with
respect to its sales, production employment or process
water use.
Four summary conclusions are particularly relevant
for the remainder of this analysis:
Using plant descriptor variables (i.e.,
sales, people, water) to array closure
levels is only a data organization mechanism;
no predictive capacity is intended.
Because data for both the sample and the
population can be organized around these
three basic descriptor variables, they are
highly useful for the display of all findings.
Because closure rates are insensitive to
changes in the descriptor variables, no
means of making differential or weighted
extrapolation by size is suggested.
Overall closure rates for the sample must
stand for the presumed closure rate of the
population.
-------
*****
This completes the presentation of the study methodology.
Industry description is contained in the next chapter.
-------
-------
II. THE INDUSTRY
This section of the report presents some of the descrip-
tive information on the metalfinishing industry that was
gathered through the surveys. Metalfinishing is an extremely
common production operation with hundreds of finishing pro-
cesses commonly used. But not all finishing processes are
relevant here since the scope of this analysis is limited
to the processes enumerated under the Electroplating Point
Source Category:
Electroplating of common metals
Electroplating of precious metals
Anodizing
Coatings, i.e., phosphating, chromating or immer-
sion plating
Chemical etching, milling and engraving
Electroless plating
Printing board manufacturing.
Not only is the scope of this study limited to those
sectors of the industry doing the seven specific metalfin-
ishing processes, it is also limited to those individual
firms that are Indirect Dischargers. These are firms that
discharge their spent liquid wastes to a municipal sewer or
Publicly Owned Treatment Works (POTW's). All such firms
-------
are to comply with the promulgated Pretreatment Standard,
and are the sole focus of analysis. The balance of the
industry discharges its wastes directly to surface waters
and are identified as Direct Dischargers. They are beyond
the scope of this effort.
In the industry description that follows the distinc-
tion is drawn clearly between types of dischargers. The
distinction must also be drawn between the separate economic
entities or industry segments that comprise the metalfinish-
ing industry. There are three:
Independent metalfinishing job shops (referred to
hereafter as the job shops). These are often
fairly small operations averaging fewer than 10
production employees and selling below $600,000
annually. These firms cluster in the major manu-
facturing areas, and there are some 2,900 such
firms of which approximately 2,7 00 are covered
here.
Independent manufacturers of Printed Circuit Boards
(referred to hereafter as Printed Boards) are
also relatively small businesses. Typically,
these firms have some 30 production employees
and tend to cluster in areas noted for electronic
goods manufacture. The industry is quite small,
estimated to be 400 firms altogether of which
327 are of interest.
-------
Captive metalfinishing operations (referred to
hereafter as captives) are in-house operations
found in many durable goods manufacturing estab-
lishments. Although found in firms of several
hundred to thousands of employees, the captive
operation itself is comparable in size to a
job shop employing some 2 0 men. There are an
estimated 6,000 such operations doing processes
covered under the Electroplating Point Source
Category of which some 4,700 are Indirect
Dischargers.
In the next two major sections, the demographics of
these three industry segments will be presented. Primary
focus is given to the job shop sector: see Appendices B
and C for supplemental descriptions of the Printed Board
and captive sectors.
1. THE SIZE AND ECONOMIC VISIBILITY OF THE METALFINISHING
INDUSTRY IS DRIVEN BY THE CHARACTERISTICS OF THE
CAPTIVES SECTOR
In this section the demographics of the metalfinishing
industry performing processes covered by the regulations of
the Electroplating Point Source Category are presented.
-------
(1) Job Shops Are Small Producers Numbering Below
3000 Establishments
Census of Manufactures uses two SIC codes (3471
and 3479) to group manufacturing establishments whose
primary line of business is metalfinishing. These
firms are the independent producers or the job shop
sector of the industry.
Prior reports have maintained a distinction be-
tween these two SIC groups. This was due to the fact
that firms in SIC 3471 are major consumers of common
plating metals (i.e., copper, zinc, nickel, chromium)
whereas firms in SIC 3479 are distinguished by their
technical production processes (anodizing, phosphatiz-
ing, precious metal plating, etching, etc.). The
guidelines for the industry promulgated by the Agency
(July 1977 and September 1979) reinforced this distinc-
tion by establishing standards for each separate
process group:
A - Electroplating of common metals
B - Electroplating of precious metals
C - (Reserved)
D - Anodizing
E - Coatings
F - Chemical etching
G - Electroless plating
H - Printed Circuit Board manufacturing.
-------
Isolating the sectors in this fashion serves the
requirements of effluent regulation because it allows
a modular approach to issuing industry guidelines.
Maintaining these separate groupings for economic
impact purposes is unwarranted because at the plant
level such process distinctions are blurred.
Very few firms, regardless of being classi-
fied in SIC 3471 or 3479, perform just one
metalfinishing process (A through H).
Most firms perform two or more separate pro-
cesses and may derive revenues equally from
each. This precludes assigning a multipro-
cess plant to just one process group.
Effluent characteristics of the various
process groups do contain unique contaminants,
but identified pollution abatement technolo-
gies do not vary by these contaminants.
Costs are driven more by flow volumes than
by type of chemical found in the wastes.
The only exception is process group H,
Printed Board manufacturers, which is
treated as an independent economic entity.
For the above cited reasons, there is no analytic
purpose served in maintaining six process distinctions
(A through G). Findings and impacts on the job shop
-------
sector of the metalfinishing industry are reported
irrespective of the distribution of production pro-
cesses within the sector.
The summary characteristics of the job shop sec-
tor (both direct and indirect dischargers) are the
following:
Both the data base of the 1977 Dun's Market
Identifiers File and the 1972 U.S. Census of
Manufactures estimate the population of job
shops at approximately 5,000 firms. By the
pattern of responses to the job shop survey
(Appendix A), more than half, or 2,941 firms,
do processes covered by these regulations.
Of this number, 2734 are indirect dischargers.
On the basis of total employment, these
2,941 firms employ 6 9,7 00 people of which
52,300 are production employees in wetmetal-
finishing. Indirect dischargers employ
62,800 with an estimated 46,800 in wetmetal-
finishing production.
Only 14% of the job shops sell $1 million
or more annually with 72% of all firms
selling $0.5 million or less a year. Aver-
age sales at the plants are $580,000 with
total industry output estimated at $2.1
-------
billion annually. Indirect dischargers
have mean sales of $675,000 and estimated
annual sales of $1.9 billion.
At the plant level, a job shop uses water on
average at the rate of 38.700 gallons per
day of which 83% or 32,300 gallons per day
is water used directly in metalfinishing
production processes. For the industry as
a whole total plant water use is on the
order of 114 million gallons per day with
95 million gallons per day taken by produc-
tion processes. Again, for the indirect
discharging segment total water use is 105
million gallons per day with 88.3 million
gallons taken by production processes.
(2) Printed Circuit Board Manufacturers Are a Small
But Relevant Sector of the Industry
Presently, no single industrial classification
available through Census of Manufactures covers ade-
quately independent producers of Printed Circuit
Board (PB's). Census data (1972) for the industry
appear confined to SIC 3679 (Electronic Components
not elsewhere classified) which account for some
1,800 independent establishments with total sales of
$3.0 billion. But included in this estimate of
-------
establishments are producers of many non-PB products;
phonograph needles, magnetic recording media, relays,
transducers, earphones and headsets. Identifying just
the PB segment from census data is not possible.
The survey of this sector, as described in the
methodology section estimated the total population of
independent Printed Board firms at 4 00. Key descrip-
tive parameters of this segment appear below.
Given that process group H of the regula-
tions of the Electroplating Point Source
Category is for Printed Board manufacturers,
all identified firms in the population (400)
are affected by this guideline.
Printed Board shops are reported to be, on
average, larger than the typical job shop.
Mean total employment is 60 people with 35 in
production finishing. For the industry as
a whole this accounts for some 23,000 people
with 13,7000 people producing the Printed Boards.
Indirect dischargers are estimated to employ
20,000 people with 11,900 in production.
These independent manufacturers have larger
per plant sales than do the job shops. Only
34% sell under $0.5 million annually with
43% selling over a million. Plant sales on
-------
average are $1.5 million with total industry
sales estimated at $610.4 million. Indirect
dischargers should account for $494 million.
The mean total plant water use of this sector
is 21,900 gallons per day. Of this amount
86% or 18,800 gallons per day are from pro-
duction processes. For the industry as a
whole 8.7 million gallons per day are used
of which 7.5 million gallons are for metal-
finishing processes. Again, indirect dis-
chargers use 7.1 million gallons of which
6.1 million gallons are for metalfinishing
processes.
(3) The Captives Sector Drives the Economic Description
of the Industry
Manufacturing establishments that house their own
internal (captive) metalfinishing operations tend to
be very large firms. The magnitude of the captives'
contribution to the metalfinishing industry is illus-
trated below. Again, first by the total sector and
then for the indirect discharging segment only.
Survey results suggest that 47% of all cap-
tive operations do processes covered by
these regulations. This defines a weighted
-------
adjusted population of 6,077 firms. Of this
number, 4,722 are projected to be indirect
dischargers.
Mean total employment of these firms is 660
people for a plan work force of slightly below
4 million people. But with 20 people per firm
assigned to metalfinishing, the production
forces is some 117,000 people. Indirect dis-
chargers account for some 2.9 million people
and 87,000 production employees.
Total sales at the plant level are $20.1
million. Of this amount, however, 54%
reflects sales of goods with metalfinishing.
Therefore, sales of metalfinished goods are
$10.9 million. Given that the finishing
cost of these goods was found not to exceed
10% of the total production cost, the value
added by metalfinishing is estimated at $1.1
million per plant. For the total industry,
this is $6.7 billion annually. For the
indirect discharging segment sales are $5.0
billion annually.
In terms of plant water use, a firm with a
captive operation uses 808,000 gallons per
day. Of this total, 35% or 277,000 gallons
-------
is used by the captive finishing operation.
On a daily basis, all 6,077 establishments
with captives use 4.9 billion gallons with
the captive operations requiring 1.7 billion
gallons. Indirect dischargers account for
3.8 billion gallons with the finishing opera-
tion taking 1.1 billion gallons daily.
2. ALMOST ALL INDEPENDENT METALFINISHERS AND SLIGHTLY MORE
THAN HALF THE CAPTIVES WILL BE AFFECTED BY PRETREATMENT
REGULATIONS
Identifying just that portion of the industry discharg-
ing to a municipally owned sewer (POTW) is the second key
step in setting up the economic impact analyses of the pre-
treatment regulations. If a firm only discharged its efflu-
ent wastes to a sewer or to a navigable body of water, the
problem would be straightforward. But many firms discharge
in a manner that combines the options, as summarized
below.
Some captives report their effluent going to a
holding tank then to the POTW. Others report
using lagoons or settling beds, while others
report using both the river and the POTW. Al-
though 58% of all relevant respondents report
discharging to the POTW only, fully 77% of the
sample ultimately passes its discharge to the
-------
POTW. Therefore subpopulation of interest for
captives is 77.7% of 6,077 or A,122 firms subject
to pretreatment regulations.
Printed Board makers reported fewer discharge
options. Of the sample, 4% discharge directly
to navigable waters, 13% to leaching ponds, 2%
wouldn't say and 81% discharge to the POTW. Of
the total estimated population of 400 PB manufac-
turers, 327 are identified as subject to this
pretreatment regulation. (This value is not
strictly 81% of 400 because all the larger firms
were known to be indirect dischargers.)
Job shops report the proportion of dischargers to
POTW's over a range from 63% to 96% depending on
the size of the firm. The overall figure
weighted by the size of all firms is that 93% of
the industry is covered by pretreatment regula-
tion. This yields a population of interest of
2,734 (93% of 2,941).
For ease of presentation, Tables II-l, 2 and 3 on the
following pages array the three industry populations for
analysis. To help illustrate the relative size of each
population, data are arrayed by a sizing measure; the
-------
TABLE II-l
Total and Production Employment
in All Job Shops and in the
Indirect Discharging Segment Only
All Dischargers
Size of
Firm
1-4
5-9
10-19
20-49
50-99
100-249
Number of
Firms
1,156
682
546
357
159
41
Total
Employment
9,300
10,900
12,300
15,400
14,100
7,700
Production
Employment
3,500
5,800
10,200
13,600
12,000
7,200
Total
2,941
69,700
52,300
Indirect Dischargers
Size of
Firm
1-4
5-9
10-19
20-49
50-99
100-249
Number of
Firms
1,045
658
524
339
142
26
Total
Employment
8,460
10,600
11,700
14,500
12,600
4,860
Production
Employment
3,100
5,200
9,100
12,200
10,800
6,400
Total
2,734
62,800
46,800
-------
TABLE I1-2
Total and Production Employment
in All Printed Board Manufacturers
and in the Indirect Discharging
Segment Only
All Dischargers
Size of
Number of
Total
Production
Firm
Firms
Employment
Employment
1-4
16
450
50
5-9
62
520
460
10-19
78
2, 080
1,200
20-49
171
10,850
5,600
50-99
57
6,200
4,200
100-249
12
2, 070
1,600
250+
4
1,150
550
Total
400
23,300
13,700
Indirect
Dischargers
Size of
Number of
Total
Production
Firm
Firms
Employment
Employment
1-4
13
400
40
5-9
50
470
370
10-19
63
1,780
1,060
20-49
139
9,200
4,680
50-99
46
5,500
3,560
100-249
12
2,070
1,600
250+
4
1,150
55 0
Total
327
20,600
11,900
-------
TABLE II-3
Total and Production Employment
in All Captive Operations and
in the Indirect Discharging Segment Only
All Dischargers
Size of
Operation
1-4
5-9
10-19
20-49
50-99
100-249
250+
Number of
Captives
2,372
1,164
1,103
955
271
157
55
Total
Employment*
742
477
772
858
521
333
140
Production
Employment*
4
6
14
28,
18
24.
21. 0
Total
6,077
3,840
117. 5
Indirect Dischargers
Size of Number of Total Production
Operation Captives Employment* Employment*
1-4 1,833 586 4
5-9 884 378 5
10-19 884 613 11
20-49 748 632 21
50-99 203 370 13
100-249 131 258 19
250+ 39 92 14
Total 4,722 2,930 87
In thousands
-------
number of wetmetalfinishing employees. This serves to show
how tightly clustered each industry is to the smaller end
of the scale. Most finishing firms or operations are truly
small with respect to total wetfinishing production employ-
ment.
Now that the key sizing descriptors of the metalfinish-
ing industry have been developed and displayed, the balance
of this chapter will be devoted to characterizing the opera-
tions and general market economics of each sector.
3. MOST METALFINISHING FACILITIES PERFORM BASICALLY
SIMILAR FINISHING OPERATIONS IN WHICH PROCESS WATER
FLOW IS KEY TO APPRECIATING POLLUTION ABATEMENT NEEDS
This section provides a brief introduction to the man-
ufacturing processes of the industry. The purpose is to
describe metalfinishing generically, to illustrate the
prevalence of specific processes across sectors, and to
introduce the pollution control requirements of the industry.
All of this information is presented in greater detail in
Chapter III, Pollution Abatement Requirements and Costs.
(1) Metalfinishing Is a Process of Applying a Coating
to a Base Substance in an Aqueous Medium
The electroplating industry applies a surface
coating typically by electrodeposition to a base
material in order to enhance its corrosion protection,
heat resistence, anti-frictional characteristics or
-------
decorative appearance. The electroplating of common
metals includes the processes in which a ferrous or
nonferrous basis material is electroplated with copper,
nickel, chromium, zinc, tin, lead, cadmium, iron, alu-
minum or combinations thereof. Precious metals electro-
plating includes the processes in which a ferrous or
nonferrous basis material is plated with gold, silver,
palladium, platinum, rhodium, or combinations thereof.
Electroless plating on metals is not a separate
industry but an integral part of a number of industries,
such as aircraft manufacture and repair, shipbuilding,
automotive and heavy machinery. It is associated, in
general, with industries whose products have to with-
stand unfavorable conditions or significant wear and
abrasions. Electroless plating on plastics for both
functional and decorative purposes is most prevalent
in several major industries: automotive, furniture,
appliance and electronics.
(2) Plating and Finishing Processes Occur in
Production Lines
For the purpose of this document, a plating line
is defined as a row of tanks in which one or more
coatings are applied. A process is the accumulation
of steps required to bring about a plating result. A
rinse is a step in a process used to remove excess
-------
solution from the work following immersion in a pro-
cess bath. A rinse may consist of several steps such
as successive countercurrent rinsing or hot rinsing
followed by cold rinsing.
Conceptually, an electroless or electroplating
line may be broken down into three steps: pretreat-
ment involving the preparation of the basic material
for plating, actual application of the plate and the
post-treatment steps. As discussed previously, the
electroplating or electroless processes apply a surface
coating for functional or decorative purposes. In
electroplating, metal ions in either acid, alkaline or
neutral solutions are reduced on cathodic surfaces,
which are the workpieces being plated. The metal ions
in solution are usually replenished by the dissolution
of metal from anodes or small pieces contained in
inert wire or expanded metal baskets. Replenishment
with metal salts is also practiced, especially from
chromium plating. In this case, an inert material
must be selected for the anodes. Hundreds of different
electroplating solutions have been adopted commercially,
but only two or three types are utilized widely for a
particular metal or alloy. Cyanide solutions are
popular for copper, zinc, brass, cadmium, silver and
gold, for example, yet non-cyanide alkaline solutions
-------
containing pyrosphosphate or another agent have come
into use recently for zinc and copper. Zinc, copper,
tin and nickel are plated with acid sulfate solutions,
especially for plating relatively simple shapes.
Cadmium and zinc are sometimes electroplated from
neutral or slightly acide chloride solutions.
The electroplating process is basically an oxida-
tion reduction reaction. Typically, the part to be
plated is the cathode, and the plating metal is the
anode. Thus, to plate copper on zinc parts, the zinc
parts are the cathodes, and the anode is a copper bar.
On the application of electric power, the copper bar
anode will be oxidized, dissolving it in the electro-
lyte (which could be copper sulfate):
Cu = Cu++ + 2e~
The resulting copper ions are reduced at the
cathode (the zinc part) to form a copper plate:
Cu++ + 2e- = Cu
With one exception, notably chromium plating, all
metals are electroplated in a similar manner. In
chromium plating, the typical anode material is lead,
and the chromium is supplied to the plating baths as
chromic acid.
-------
(3) Wastewater Contaminants Requiring Treatment Come
From All Steps of the Production Processes
Wastewater from plating processes comes from
cleaning, surface preparation, plating, and related
operations. The constituents in this wastewater
include the basis material being finished as well as
the components in the processing solutions. Predomi-
nant among the wastewater constituents are copper,
nickel, chromium, zinc, lead, tin, cadmium, gold,
silver, and platinum metals, as well as ions of
phosphates, chlorides, and various metal complexing
agents.
A large proportion (approximately 80%) of the
water usage in plating is for rinsing. The water is
used to remove the process solution from the surface
of the work pieces. As a result of this rinsing, the
water becomes contaminated with the constituents of
the process solutions and is not directly reusable.
Dilute rinse water solutions of various process chemi-
cals result from each operation.
(4) Finishing Processes Appear with Similar Frequency
m Each Sector
Interesting parallels exist between the captives
and jobbers with respect to their basic production
processes. Fully three-quarters (77%) of all job
-------
shops work with common metals (copper, nickel, chrome,
zinc). Not quite one-quarter (24%) do electroplating
of precious metals with another one-quarter (24%)
indicating that they do anodizing. More than half
(55%) do a coatings process. These are not mutually
exclusive categories. Any one shop can do more than
one process and the majority do. Typically, a plater
of heavy metals also does chromating, perhaps combin-
ing the chromating with a bright dipping operation.
Almost every facility plating with heavy metals also
indicated the finishing operations of polishing,
buffing and grinding.
Captives also report heavy usage of the four
common plating metals. Most frequently reported are
nickel and copper, indicated by 63% and 51% of the
sample respectively. Gold and silver are also
reported for almost one-quarter of the sample (24%
and 18% respectively). Coatings, particularly
phosphating and chromating, appear in approximately
half the respondents (56% and 49% respectively).
Clearly, irrespective of economic sector, metal-
finishing processes assume a specific hierarchy; heavy
metal plating, coatings (phosphating, chromating) fol-
lowed by anodizing and precious metals plating.
-------
Printed Board manufacturers, due to the more
specialized nature of their product show a different
array of metals usage. Almost all respondents (85%-
95%) are heavy users of copper, nickel, gold and
solder. Chromium is used in only 13% of the cases.
Showing up in printed board operations is a much
higher prevalence of tin (72%) than in the other
sectors, and the presence of chelates (26%) .
(5) Total Water Requirements of Metalfinishing
Process Operations Are a Small Portion of Daily
Industrial Demand
On a daily basis, the independent producers
require approximately 114 million gallons of total
plant water. Of this total, some 80% is required for
metalfinishing process operations, yielding a total
finishing water usage of 95 MGPD. Of this total, 88
MGPD goes to POTW's.
Manufacturing plants with captive operations use
finishing water at a rate that is an order of magni-
tude greater than for jobbers. On a daily basis,
captives are estimated to use a total of 4.9 billion
gallons, of which 35% is used in metalfinishing
operations. This yields a process water use of 1.7
BGPD, of this total, 1,163 MGPD goes to POTW's.
Printed Board makers account for an additional 8.7
-------
MGPD of which 7.5 MGPD is for process water. This
contributes an additional 6 MGPD to POTW's. The
metalfinishing industry as a whole demands a total of
5.0 BGPD of which 1.8 BGPD is process water and 1.3
BGPD going to POTW's. As a basis of comparison, 1975
Census data show a total national industrial water
use of 63.6 BGPD. The metalfinishing industry, then,
accounts for 7.7% of all industrial water, with
metalfinishing process water representing 2% of the
daily national total.
Focusing the discussion on water use in the
industry serves two ends. It illustrates the volumes,
in absolute terms, of effluent wastes generated by
metalfinishing. It serves as well to illustrate that
at the plant level there will be a core group of con-
taminants to be treated irrespective of the unique
processes performed at the plant. Costs for the
pollution abatement systems required for pretreat-
ment will be shown to rest primarily with volumetric
flows through the treatment components, rather than
with processes or base materials plated or finished.
-------
4. LOCAL MARKET CONDITIONS COUPLED WITH THE FIRM'S
FINANCIAL CONDITION WILL AFFECT COMPLIANCE AND
CLOSURE RATES
Selected data from the job shop survey are presented
here because they illustrate two major determinants of
pretreatment investment impacts on the industry:
General financial condition of firms
Market demand and price behavior for the
industry.
This first point serves to illustrate the general cash flow
situation of firms or their capacity to support further debt.
The second is important because it reinforces the understand-
ing of firms' pricing freedoms and behaviors.
(1) Few Job Shops Appear To Be in a Strong Cash Flow
or Profitability Situation
The tables presented below are from the job shop
survey and are sample specific findings. While highly
indicative of industry conditions, no attempt to
extrapolate these data to the population has been made.
As used throughout these tables, the term SD stands
for standard deviation, e.g., the dispersal of values
about a computed average. The letter "K" represents
"thousands."
-------
Of the 344 firms providing profit data, the
mean profit before tax was $30.IK (SD = $95K)
and the mean after tax profit was $15.6K
(SD = $42K).
Not all plants providing financial informa-
tion had a profit in 1975. There were 60
plants reporting an operating loss, an
average of $4.4K (SD = $23.7) before tax,
and an after tax loss of $3.4K (SD = $16.3).
In reconstructing balance sheet information
from the sample, data are available for
approximately 300 respondents. Information
is arrayed in Table II-4 below for the total
sample, and then for three collapsed size
intervals.
TABLE II-4
Typical Balance Sheet Items
Employment
Size
Total
Item
Sample
(SD)
1-19
20-99
100+
(0001
's Dollars)
Current Assets
$200
$524
$103
$253
$1,470
Fixed Assets
176
302
69
277
768
Current Liabilities
115
276
53
170
612
Long-Term Debt
70
192
25
107
453
Net Worth
212
477
102
278
1,688
-------
The table shows a linear relationship
between size of firm and magnitude of
dollars. To test whether larger firms are
more economical, these values can be divided
by the mean employment for the intervals to
reflect dollars on a per-employee basis. In
Table II-5 below, the intervals have been
divided by the mean employment (8, 41, and
155 employees).
TABLE II-5
Value of Selected Balance Sheet Items
on a Per Man Basis
Dollars Per Man
By Size Interval
Item
1-19 20-99
100+
(000's Dollars)
Current Assets
$12.9 6.2
11.2
Fixed Assets
8.6 6.7
4.9
Current Liabilities
6.6 4.1
3.9
Long-Term Debt
3.1 2.6
2.9
Net Worth
12.8 6.8
10.9
It would now appear that smaller firms are
not appreciably different from larger ones
in their capital structure. They are quite
similar on current assets and net worth.
-------
One other basis for appreciating the capital
structure of the industry is to look at a
firm's fixed assets and its planned invest-
ments in those assets. These data are pre-
sented in Table II-6 below. It is inter-
esting to note that all firms attach compar-
able life to their assets, but the magnitude
of those assets is quite different by the
intervals.
TABLE II-6
Distribution of Selected Capitalization
Items by Size of Firm
Employment
Size
Item
Total
Sample
1-
-19
20-99
100+
(000's
Dollars)
Building Book Value
$ 96
$
50
$141
$173
Equipment Book Value
$134
$
53
$215
$481
Remaining Life of Building
15 yrs.
15
yrs.
16 yrs.
12 yrs.
Remaining Life of Equipment
6 yrs.
6
yrs.
6 yrs.
6 yrs.
Planned (5 year) Building
14
Investment
$ 38
$
$ 62
$105
Planned (5 year) Equipment
Investment
$ 12
$
4
$ 22
$ 15
Once again, converting these tables to a per-
employee basis reveals some interesting
patterns. Omitting the asset life, we note
in Table II-7 below that small firms have
-------
invested more in the past and will invest
more in their plants (on a per-man basis)
than larger plants.
All of the preceding should be sufficient
to discourage the use of a single sizing mea-
sure as an independent predictor of plant vulner-
ability or of closure.
TABLE II-7
Selected Capitalization Items
on a Per Man Basis
Item 1-19 20-99 100+
(0001s Dollars)
Building Value
Equipment Value
Next Building Investment
Next Equipment Investment
$6.2 $3.4 $1.1
6.6 5.2 3.1
1.7 1.5 .6
.5 .5 . l
(2) Most of the Firms in the Industry Are Job Shops
With Well Established Customer Relationships
No discussion point about the metalfinishing indus-
try receives more attention or is more important than
the structure and dynamics of the marketplace. Prior re-
ports, lacking primary data on market conditions built
the following paradigm:
Price competition in the industry is intense
because barriers to entry are low and new
entrants tend to price low to win business.
-------
Competition is tight and as prices are bid
down, prevailing prices can disrupt the
profit margins and operating efficiencies
of larger shops.
In light of new, incremental costs (pollu-
tion abatement expenses), firms could raise
prices and maintain business volume if:
Substitution of other finishes is not
feasible.
Foreign imports cannot pick up the
volume.
Metalfinishing is indispensable to
customers' needs.
Customers are unlikely to invest in
captive, in-house finishing.
These reports concluded that demand for plating should
be inelastic with respect to price since the above
listed conditions probably held true. Prior reports
made some additional assumptions about pricing set by
least cost producers and modeled price increases on
the order of 11% to 16% into industry impact analyses.
Field data can now replace presumption. All of
the critical issues on the dynamics of the market-
place were cast into specific survey questions. In
-------
this final section characterizing the metalfinishing
industry, data will be presented covering:
Structure of the marketplace
Pricing behavior
Customer response to price.
Respondents were asked to describe their firm
with respect to their customers, products, and compe-
titors. This set of items was "forced-choice." Two
possible answers were given and the respondent had
to select the one answer that best fit his firm.
There were five items with answers scored as a 'one'
or as a 'two.' The specific items and their results
appear in Table II-8, on the following page. The pre-
dicted pattern for the industry if it were dominated
by "pure" job shops should be 2, 2, 1, 2, 1. These
firms do show the operating characteristics associated
with job shops. The one item that is not as clearly
distinguished as the others is Item B, Number of
Customers. Job shops were presumed to sell to many
different customers and, in aggregate, they do. But
a fair number of respondents rely heavily on a few,
steady ones. If this proves to be the case for a
significant number of firms, the argument can be made
for customer loyalty and, perhaps, product specializa-
tion. Under such conditions, it is all the more
-------
TABLE II-8
Survey Responses to the "Job Shop" Questions
A. Does your firm specialize in services to a major
industry (i.e., automobile, aerospace, etc.) or
do you service many different industries?
Specialize in service to an industry 1
23.2%
Service many industries 2
76.8%
B.-
During the year are most of your sales to a few
steady customers or to many different customers?
Few steady customers 1
42.3%
Many different customers 2
57.7%
C.
Do your customers send you many different kinds
of products (all shapes and sizes) or do you
get basically the same products most of the
time?
Many different products 1
76.2%
Basically the same products 2
23.8%
D. Do you generally attract customers because you
can offer low prices or because you can take
on any assignment?
Offer low prices
1 29.2%
Take any assignment
2 70.8%
E. Do you face a lot of competition for your
customers or relatively little
Lot of competition
1 72.6%
Relatively little
2 27.4%
-------
likely that a customer will meet the new incremental
price increase of his supplier because it is literally
his only supplier of finishing services.
More than 90% of the sample provided data on
past and future price behavior. Within these several
survey questions on price, there were several differ-
ent study questions:
Amount of most recent past price increase
Customer reaction to that past increase
Estimate of maximum future price increase
The survey data on this issue are arrayed in Table
II-9 below.
TABLE II-9
Distribution of Price Behavior
by Size of Firm
Total Employment
Price 1-19 20-99 100+
Past Rise 9.4% 8.8% 7.5%
Future Rise 13.6% 11.8% 9.3%
In the past, the sample raised price by 9%; for the
future, the sample as a whole estimates price increases
of 12% could be sought.
-------
The key item in this section on marketplace
behavior is customer response to past price increases.
There are not sufficient historical data on the indus-
try to allow a demand coefficient to be derived
empirically. One can be imputed from a qualitative
assessment of the marketplace data that the survey
furnished.
All respondents were asked to judge what their
customers might do in response to a price increase.
Five customer options were listed, and the respondents
circled one code number for each item representing the
probability or likelihood of that option. Table 11-10,
on the following page, presents these data. The value
in each cell is the percent of all respondents who
selected that likelihood. Data were provided by 426
respondents.
For ease of presentation, the two categories at
each end of the scale ("very") have been collapsed.
30.6% think customers might buy more from
captives; 24.5 think it's likely, with 38.6%
saying unlikely. If the "maybe" category is
disregarded, then the industry does not expect
volume to be displaced to captive operations.
-------
TABLE 11-10
METALFINISHERS JUDGMENT OF THEIR
CUSTOMERS' REACTIONS TO PRICE INCREASES
Very
Very
Unlikely
Unlikely
Maybe
Likely
Likely
Customers might buy more
from captives
18.0
20.6
30.6
15.0
9.5
Customers might eliminate
Metalfinishing from their
23.2
18.7
22.1
17.1
12.4
products
Customers might start
their own in-house,
19.5
22.3
23.0
15.8
11.7
captive lines
Customers might shop around
more for the best price
2.6
2.4
6.7
24.1
59.7
Customers might use some
other finish for metal-
10.0
13.9
21.3
23.2
25.8
finishing
41.9% are confident that customers could not
or would not eliminate metalfinishing from
their products. Only 2 9.5% expect them to
do so.
41.8% do not expect their customers to start
in-house captive finishing operations. Only
27.5% think it is a strong possibility.
83.8% recognize that their customers would
have to shop more for the best price. Only
5% believe that customers would readily
meet any price increase.
-------
4 9.0% grant that their customers would con-
sider substituting for metalfinishing. Only
23.9% believe their customers do not have
that option.
These data are a clear qualitative statement of the
metalfinishers marketplace:
Metalfinishing in some form is probably
indispensable but substitutes are possible.
Starting in-house operations in light of
rising independent prices is not perceived
as a viable customer option.
With respect to demand (in light of price increases),
these data suggest that if everyone had to raise
prices, business volume would probably not fall off.
The elasticity of demand with respect to price is
probably highly inelastic.
* * * *
This concludes the presentation of key survey findings
with respect to the structure and composition of the inde-
pendent sector of the metalfinishing industry. Comparable
presentations are contained in Appendices B and C for the
other sectors. There do not appear to be any striking rever-
sals to industry characterization developed in earlier reports.
-------
Much of the data reinforce prior efforts, although the Key
application of the data is yet to come. That occurs in
Chapter IV when the survey's primary financial data are
incorporated in the closure analysis.
-------
-------
III. POLLUTION ABATEMENT REQUIREMENTS AND COSTS
This chapter defines the technology applicable for pre-
treatment, identifies the compliance requirements developed
by the Agency and arrays the anticipated costs for each
industry sector. In the methodology chapter, the rules
for developing investment costs per treatment component
were presented. Of interest here is the application of those
rules; i.g., the cost allocation program designed to specify
components and costs as a function of processes and water
use in individual plants.
Five major sections are contained in this chapter. They
are:
Identification of Pretreatment Technologies
Definition of the Regulation
Cost Allocation Rules
Component Costs
Industry Costs.
1. PRETREATMENT IS REQUIRED FOR THE CONTROL OF CYANIDE,
HEXAVALENT CHROMIUM, LEAD, CADMIUM AND OTHER METALS
Individual treatment technologies used in the industry
(electroplating, electroless or Printed Boards) are well
documented. Among the more common control applications are:
-------
Chemical reduction of hexavalent chromium
pH adjustment
Clarification
Diatomaceous earth filtration
Flotation
Oxidation by chlorine of cyanide
Oxidation by oxygen
Deep bed filtration
Ion exchange
Evaporation
Reverse osmosis
Ultrafiltration
Electrochemical recovery
Sludge dewatering.
For Pretreatment, however, the Agency has defined a Best
Practicable Pretreatment Technology that consists of the
following:
Reduction of hexavalent chromium to the trivalent
form and chromium removal from the wastestream
Destruction (oxidation) of cyanide
Precipitation and clarification of specific metals.
This Pretreatment technology is to be applied to all
firms discharging to a POTW and performing one or more pro-
cesses regulated under the Electroplating Point Source Cate-
gory.
-------
2. PLANT PROCESS WATER VOLUME IS A CRITERION FOR THE AP-
PLICABILITY OF PRETREATMENT REQUIREMENTS
For plants with a daily flow of 38,000 liters (10,000
gallons) per day or more, the promulgated standards limit
the discharges of cyanide and the following metals:
Lead
Cadmium
Copper
Nickel
Chromium
Zinc
Silver.
Additionally, the regulation limits total metals discharged
determined as the sum of the individual concentrations of copper,
nickel, chromium, and zinc.
Plants with a daily flow of less than 38,000 liters
(10,000 gallons) per day have a standard that limits only
lead, cadmium, and cyanide. Small water use plants are
also exempt from a total chromium limit and are not modeled
showing chromium reduction units.
Use of a water based cut-off reflects the Agency's
commitment to balancing the economic impact of this regula-
tion while maximizing environmental benefit. It is important
to note that there is no firm, quantitative method for com-
puting an optimum cut-off level. However, considerable
-------
thought and effort went to arriving at the 10,000 gallon
cut-off.
Major economic hardship is expected to fall on
the independent job shops which are fairly small
production operations. To be of benefit to the
job shops the cut-off level had to be set at a
value that covered a sizable number of facilities.
A 10,000 GPD level covers almost 50% of all job
shops.
Sets of cut-off levels were considered ranging
from a 'zero' level to 40,000 GPD; for each level
impacts as well as untreated discharge volumes
were compared. Comparisons were made between re-
lative increases in untreated flows against rela-
tive decreases in plant closure rates. The
pattern of data suggested that 10,000 GPD was a
useful and appropriate criterion.
As reflected by the above, compliance requirements are
targeted, to some measure, to process volume flow. Each
scenario (above and below the cut-off) is costed and a
range of industry costs and impacts derived. The next sec-
tion describes the method for applying technical compliance
costs to the model plant data base and subsequently to the
industry.
-------
3. PRETREATMENT SCENARIOS WERE COSTED FOR PLANTS USING AN
AUTOMATED SYSTEM INCORPORATING FLOW ALLOCATION RULES
PER TREATMENT COMPONENT
Once the technology is defined and the compliance sce-
narios articulated, the task becomes one of systematically
developing rules for costing abatement systems. The follow-
ing discussion points explain the costing rationale used in
the study.
(1) Application of Technologies Must Fit the Produc-
tion Processes
Each of the individual treatment technologies can
be combined to form systems capable of meeting the pro-
posed limitations on both direct and indirect dischargers.
However, the specific elements of a treatment system
must be appropriate to the chemical and metal constitu-
ents of a plant's process wastewater. Chromium reduction
and cyanide oxidation are used only if the wastewater
contains chromium or cyanide. Clarification includes
pH adjustment, precipitation, flocculation, and sedi-
mentation, which may be carried out in one or more ves-
sels or pits. Chelated wastes, if present, should be
clarified separately to prevent the chelates from tying
up metals in other waste streams. Sludge drying may be
carried out in the sludge drying beds or in a vacuum
filter, and contractor removal of sludge may sometimes
be replaced with landfilling on company property. In
addition, final neutralization (pH adjustment) of the
-------
wastewater before discharge may be needed to meet the
pH limitation, particularly if nickel salts are removed
effectively by clarification at a relatively high pH.
(2) Focus for This Study is End-of-Pipe Technology
Pollution abatement controls can be introduced as
in-line alterations to the production process through
the placement of water conservation equipment. Alter-
natively, controls can be introduced at the end of the
production process prior to discharge. It is this lat-
ter end-of-pipe approach that occupies this study. A
prototypical system appears in Exhibit IV on the next
page.
There are many alternative end-of-pipe applications
of control technologies. The listing in the prior sec-
tion should not be viewed as the universal or unchanging
definition of control technology applicable to metal-
finishing process wastes. Many alternative techniques
have been encountered in the field. These alternatives
range from the use of a settling lagoon to replace the
clarifier to the use of reverse osmosis, ion exchange,
membrane filtration, diatomaceous earth filtration, and
multiple stage rinsing to reduce discharge of pollutants.
-------
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EXHIBIT IV
U.S. Environmental Protection Agency
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Although not found as commonly as clarification, most
of the individual technologies described earlier are
in general use through this industry. The use of any
particular component or system will depend on the wastes
to be treated, space constraints, funding availability,
and other factors which involve management judgment.
(3) Estimating the Industry's Investment Needs Requires
Data on Four Key Variables
In the next section the industry's costs are developed
and arrayed for purposes of economic impact analyses. At
this point, part of the methodology for developing those
costs will be presented. A full presentation of the cost-
ing routine and logic is found in Appendix G of this
report.
Pollution abatement costs were generated for each
survey respondent as a function of the following infor-
mation provided in the questionnaire:
Metals present in the wastestream
Process water flow through each discrete
finishing operation
Amount, type and value of existing pollution
abatement equipment
Availability of physical space either inside
or outside the plant for locating the prescribed
system.
-------
The first two variables are predictors of the type
and size of the firm's required pollution abatement com-
ponents. The second two variables serve as moderators
on the total dollar estimate of the prescribed system.
As summarized in the second section of this chap-
ter the majority of finishers use the four common metals
plus additional processes in which cyanide frequently
is a key agent. This generally requires the application
of a Best Practicable Pretreatment Technology that in-
cludes :
Oxidation of cyanide
Reduction of chromium
Clarification-filtration of metals.
Before the costs of these individual components comprising
this treatment technology are generated, two additional
steps occur in the automated cost routine:
Individual treatment components, if presently
in place, override the specification from the
program output. This means a plant needing
a clarifier receives one if, and only if, one
is not present. If the individual components
in place are not identified, but their capital
replacement is, that dollar value is credited
to (e.g., subtracted from) the new estimated
cost. In the cost model this is the assumption
-------
of full credit for equipment in place. There
are no data to test or to prove that field
equipment currently perform to the standard,
or might not require replacement. But it is
clear through the survey data that most equip-
ment is new, sized appropriately and the same
components predicted by the costing routine.
In the absence of data to the contrary plants
are costed only for needed equipment not in
place.
Full installed cost of the treatment system
depends on the location and ease of the in-
stallation. All firms with available exterior
space are costed with an outdoor clarifier
with attendant estimates of construction and
land costs included. If interior space is
available and metals removal is required,
the system specifies a diatomaceous earth
filter.
(4) Pollution Abatement Component Costs Were Developed
By Correlating Flow Volumes to Costs
Pollution abatement component costs were generated
for each plant model by identifying the key drivers
-------
of equipment size and cost. It was found through care-
ful review of the detailed model plants that the best
predictor of equipment cost was the requisite size
(volumetric capacity) of a component. The key driver
of size was the flow through the component in gallons
per hour.
To yield a set of predicator cost equations,
it was necessary to array (regress) the costs (fully
loaded) developed by the Technical Contractor against
a second, continuous variable. In this case the variable
is process flow volume.
As shown in Exhibit V and Exhibit VI, on
the following pages, the log of total invest-
ment costs for full BPPT requirements corre-
lates somewhat with the log of system capacity.
- For clarifier plants, the correlation
coefficient is about 0.68.
For filtering plants, the correlation
coefficient is about 0.76.
The experimental scaling factors are the
following:
Clarifier plants scale with system ca-
pacity with an exponent of 0.46.
Filtering plants scale with system
capacity with an exponent of 0.47.
-------
EXHIBIT V
U.S. Environmental Protection Agency
CAPITAL COST OP FILTRATION UNITS
103
,4
FILTRATION CAPACITY (GALLONS PER HOUR)
-------
EXHIBIT VX
U.S. Environmental Protection Agency
CAPITAL COST FOR CLARIFIERS WITH pH ADJUSTMENT
m
5
••
CAPACITY (GALLONS PER HOUR)
-------
Both of those scaling factors are slightly less than
the 0.6 factor traditionally used; the difference
is attributed to the large fixed costs for instrumen-
tation which does not scale with capacity.
The variation of the data points around the
least squares regression line is due to the
fact that BPT systems may not require all
the system components:
pH adjustment
Hexavalent chromium reduction
Cyanide destruction
Clarification or filtration .
Exhibits VII through X, on the following
pages, plot the estimated investment for
major BPPT system elements versus the waste
water treatment flow of that element. The
exhibits show:
Correlation of investment versus capacity
for cyanide destruction is approximately
0.9 .
- Correlation for hexavalent chromium
reduction units is about 0.8.
Correlation between investment and flow for
the solids removal equipment is also very
good, about 0.9.
-------
EXHIBIT VII
U.S. Environmental Protection Agency
CAPITAL COSTS FOR CYANIDE OXIDATION UNITS
200.000
180,000
160,000
140,000
120,000
to
K
O
Q
100,000
u
-I
<
*-
••
80,000
60,000
40,000
20,000
5,000
10,000
1,000
UNIT CAPACITY (GALLONS PER HOUR)
-------
EXHIBIT VIII
U.S. Environmental Protection Agency
CAPITAL COSTS FOR HEXAVALENT CHROME REDUCTION
CAPACITY (GALLONS PER HOUR)
-------
EXHIBIT IX
U.S. Environmental Protection Agency
RELATIONSHIP OF TOTAL SYSTEM FLOW BATE
TO INVESTMENT FOR LEAST COST (1) INDOOR
PLANTS-FILTER MODE
1.000
u.
100
1,000
too
SYSTEM FLOW RATE
(GALLONS PER HOUR)
<1» INVESTMENT REPRESENTS BPPT - BPT - NO SMALL PLATER EXEMPTION,
NOTHING IN PLACE
-------
EXHIBIT X
U.S. Environmental Protection Agency
RELATIONSHIP OF TOTAL SYSTEM FLOW RATE
TO INVESTMENT FOR LEAST COST OUTDOOR
PLANTS-CLARIFIER MODE
52 100
m
Ul
100 1.000 10,000 100.000
SYSTEM FLOW RATE
(GALLONS PER HOUR)
(1> INVESTMENT REPRESENTS BPPT - BPT - NO SMALL PLATER EXEMPTION,
NOTHING IN PLACE
-------
(5) Given the High Correlation of Flow to Cost, Flow
Based Equations Were Programmed into an Automated
Costing Routine
All of the prior exhibits on flow volumes to com-
ponent costs demonstrated strong linear association
between the variables.
The equations account for between 60 and 80%
of the variability between investment cost
estimates and volume of water treated in
their appropriate regression of flow.
The pH adjustment equation was derived from
the computer model cost estimates as well
as from industry sources such as manufac-
turers and distributors of neutralization
systems because the computer model did not
separate pH adjustment costs from costs for
combined pH adjustment/batch clarification
equipment.
On a per component basis, the flow relationships to
the costs of cyanide destruct units and hexavalent
chromium reduction units are both strong: for cyanide
units, the average absolute difference is 17%, with the
equations 7% lower than reported costs. For hexavalent
chromium units, the regression equation predicts costs
about 16% higher than generated by the Technical Con-
tractor.
-------
These results, plus the cost comparisons cited in
Appendix G, support the use of regression equations
for applying characteristic treatment components and
costs for all model plants available in the survey.
4* INVESTMENT COSTS FOR 205 JOB SHOPS/ 40 PRINTED BOARDS
PLUS THE CAPTIVES WERE DEVELOPED AND FORM THE DATA
BASE FOR SUBSEQUENT INDUSTRY ECONOMIC ANALYSIS
The principal regulatory scenario was costed for each
segment of the metalfinishing industry. For job shops,
Printed Board manufacturers, and captives, pollution abate-
ment cost estimates were generated for installing:
Cyanide oxidation, chromium reduction and clari-
fication for firms above the cut-off. Included in
the total capital cost is the construction of a
sludge drying bed scaled to the volumetric capacity
of the clarifier.
Cadmium, lead treatment and amenable cyanide oxi-
dation for plants below 10,000 GPD.
For estimating captives' investments the basic job shop cost
method was somewhat altered:
Data on individual processes and line descriptors
were not available; however, operations and fin-
ishing metals were. This enabled treatment com-
ponents to be invoked for specific trace metals
and chemicals.
-------
Space availability data were not available, the
operating decision rule was to assign all captives
indoor diatomaceous earth filters.
Specific treatment components already in place
were not identified for captives—only their
dollar costs. This value was subtracted from
the new, projected investment cost before assigning
costs.
Sludge removal was handled by costing a sludge
drying bed scaled to the plant's discharge volume,
plus a sludge contractor haul factor at $.25 per
gallon for 20% sludge from the bed.
Summaries of these costs are presented below:
(1) Job Shops for Full Compliance Face Investment
Requirements Approaching $7 5,000 on Average
Two tables are presented below for job shop capital
requirements to meet the Pretreatment scenario. Table
III-l distributes the mean investment cost by water use
intervals. Table III-2 distributes the cost by metal-
finishing employment categories. Either table could
serve as a basis for displaying sample and industry
costs. For purposes of this report wetmetalfinishing
employment intervals will be the primary data display
mechanism because it is sensitive to changes in costs,
arrays data by a measure that correlate well with other
-------
TABLE III-l
Mean Investment Capital To Meet a Pretreatment
System Arrayed Across Water Use Categories (GPD)
Size of Firm Mean Cost ($000's)
0 - 10,000 20.5
10.000 - 16,000 80.7
16.001 - 20,000 111.1
20,001 - 30,000 126.0
30,001 - 40,000 119.2
40,001+ 184.3
$ 76.1
TABLE III-2
Mean Investment Capital To Meet a System
Arrayed Across Metalfinishing Employment Categories
Size of Firm Mean Costs ($000's)
1-4 $ 37.4
5 - 9 70.4
10-19 95.3
20 - 49 106.9
50 - 99 170.2
100 - 249 164.9
$ 76.1
parameters (sales, water-use) and allows the best array
of sample findings to the population.
-------
(2) Printed Board Manufacturers Face Pretreatment
Costs Somewhat Lower Than Job Shop Costs
The mean capital cost to jobbers for a full Pre-
treatment system was approximately $75,000. Small firms
face a $20,000-$30,000 investment and the larger oper-
ations face, on average, a $150,000 expense. Printed
Board manufacturers require somewhat different equipment,
use less production water and thereby face lower capital
costs. Few firms regardless of flow required a hexa-
valent chromium reduction unit, whereas almost all need
a separate clarifier for the chelated waste streams.
Table III-3, shown below, arrays the capital
costs by the wetmetalfinishing sizing intervals. Most
small plants face capital costs in the $20,000-$25,000
range with the largest plants at $100,000. For the
sample plants as a whole, the mean capital requirement
is estimated to be $56,500.
TABLE III-3
Mean Investment Capital To Meet Printed Board
Manufacturers Pretreatment Standards
Arrayed Across Metalfinishing Employment Categories
Size of Firm Average Costs ($000's)
1-4
5-9
10-19
20-49
50-99
100-249
$ 24.3
118.7
$ 56.5
24.3
21.7
52.3
68.4
-------
(3) Captive Facilities Face Pretreatment Costs That
Are Several Times Greater Than Jobbers
Of the total 1,614 respondents to the captives
survey, not all provided sufficient data for costing
nor are all indirect dischargers requiring a Pretreat-
ment system. There are 497 cases that did not provide
water use data. There were also 381 cases that were
predicted to face a $0 investment because of prior ex-
penditures for pollution abatement equipment. For
purposes of displaying future investments, the 381 prior
investment cases were dropped and costs were developed
for all cases affected by these regulations. The sample
numbers 536.
Table III-4 below presents the total capital cost
of a Pretreatment system for captive establishments
arrayed against wetmetalfinishing employment categories.
The overall mean capital is $250,000 with costs basically
linear with respect to employment. One aberration is~-
the 10-19 man interval in which costs are disproportion-
ately high. These sample cases use 4 times the water
as the 5-9 man operations and have also made dispro-
portionately little prior investments in pollution con-
trols.
-------
TABLE III-4
Mean Investment Capital to Meet a Pretreatment System
Arrayed Across Metalfinishing Employment Categories
(536 Captive Facilities)
Size of Operation # of Cases Mean Cost ($000's)
1-4 181 $ 54.0
5-9 115 133.0
10 - 19 106 762.4
20 - 49 93 181.2
50 - 99 23 252.0
100 - 240 12 285.6
250+ 6 514.8
536 $ 251.9
(4) Annualized Costs for A Plant Are Approximately
One-Third the Estimated Total Capital Cost
Annual costs reflect interest charges at 12%, with
a 10-year payback period. Also included within the an-
nualized figure are costs for the pollution system's
utilities, labor and maintenance (averaging 12% of
total capital). In addition, a capital cost recovery
factor of 2% is included as are depreciation (5 year,
straight line) and the annual sludge haul cost. These
data are portrayed for each industry sector in Table
III-5.
-------
TABLE III-5
Mean Annualized Cost to the Industry
of the Pretreatment Regulation
(Arrayed by Wetmetalfinishing Employment)
Printed
Board
Job Shops
Makers
Captives
($000's)
($0001s)
($0001s)
1-4
15.1
3.0
$ 22.4
5-9
19.1
3.0
49.3
10 - 19
40.6
3.0
245.8
20 - 49
44.3
5.5
66.8
50 - 99
70.8
6.6
91.3
100 - 249
79.2
11.1
107.6
250+
—
—
202.1
34.4
5.6
$ 91.2
* * * * *
This completes the presentation of the model plant
Pretreatment compliance costs. Closures due to these costs
appear in the next chapter.
-------
-------
IV. SAMPLE CLOSURE RESULTS
This chapter presents the calculated closure rates for
firms in the metalfinishing industry sample data base. Re-
sults for the job shop sectors proceed directly from the
automated closure routine, while results for captive oper-
ations proceed from an analysis of administrative and struc-
tural features of the respondents.
All results presented within this chapter are sample
specific: i.e., no industry-wide estimates are offered.
In the next chapter, Economic Impacts, sample results are
extrapolated to the total industry. In order to make those
extrapolations, a method for correcting impacts due to base-
line closures as well as a method for yielding weighted
population impacts must be developed. This chapter is or-
ganized, therefore, into three primary sections:
Baseline closure analysis
Sample closure rates
Extrapolation decision rules.
1. BASELINE CLOSURES INDEPENDENT OF THE FINANCIAL REQUIRE-
MENTS OF POLLUTION ABATEMENT INVESTMENTS CAN BE FACTORED
OUT OF THE SAMPLE SO THAT CLOSURE ESTIMATES ARE THOSE
DUE TO THE ACT
It is unacceptable to project sample closure rates
directly to the population without making a set of necessary
-------
corrections. One correction involves taking into account
closures that should occur independently of future pollution
abatement investments.
Two methods are available for dealing with the manner
of probable baseline closures in the existing data base.
One, is to compare financial profiles of known closures to
those of models and cull sample plants from the data base
that match closures. A second design is to review the raw
financial data of the models on a "pre-investment basis" and
through the application of a decision rule test for the firms
unlikely to remain in business independent of investments in
pollution controls.
Analytically the first method is the stronger, more
desirable approach. However, data retrieval problems coupled
to prohibitive cost precluded the effort. The baseline ana-
ysis relied, therefore, on the application of a decision
rule and the automated closure routine.
Detailed review of the reported financial condition
of the job shop sector of the industry revealed how ex-
tremely vulnerable the industry as a whole was to incremental
capital expenditures. The majority of firms providing de-
tailed financial data showed either a negative pre-tax con-
dition or pre-tax positions that showed poor returns on
sales. An analytic decision rule was to impose a minimum
capital burden of $100 on all plant models and a 1.0 cover-
age ratio test to see the effect on the pre-investment
closure rates.
-------
Of the 205 plant models assigned the $100 capital bur-
den, 28 or 13.7% of the job shop sample were labelled closures.
For the balance of the report, these 28 cases are defined
as the baseline closures, leaving 178 plant models on which
economic impacts due to the act can be computed.
A comparable test was run on the printed circuit board
data base. From the 40 plants that were costed for impact
work, 5, or 12.5% of the plant model sample were defined as
baseline, pre-investment closures. Impacts are computed
then on 35 plant models.
2. SAMPLE CLOSURE RATES CAN SERVE AS STRAIGHT PROPORTIONAL
CLOSURE RATES FOR THE POPULATION
Appendix D presents the detailed analysis of the re-
lationship between survey data and population parameters.
Within that analysis, several important points were developed:
Model plants and non-model plants show sufficient
similarity to allow closures for the models to
stand for the sample as a whole.
Total sample respondents show some key differences
on sales and net worth values in comparison with
the non-sampled universe. There is the sugges-
tion that the sample respondents are financially
stronger than the average for the industry.
-------
Due to the oversampling of smaller firms in the
telephone follow-up, on average that group of
non-respondents is consistently smaller (employ-
ment, water use and sales) than the mail respondents.
This suggests that the group available for costing
may represent the larger production operations
but there are no data to suggest that non-respondents
are less financially secure firms than the respon-
dents, or would experience significantly different
closure rates.
Closures had always been found or presumed to re-
side within the smaller operations. Although
there is a trend within the data to suggest smaller
operations are somewhat more likely to be impacted
than larger firms, the trend is not statistically
significant. Closures are predicted as a constant
throughout the sample.
Recent analyses within the Agency arrayed job
shop closure rates across water use categories,
sales and employment intervals. The result of
that Chi Square analysis rejected the hypothesis
of independence between rows or columns and left
the conclusion that the sample overall result can
stand for any row or column by which the sample
is arrayed.
-------
All of the preceding supports the approach of representing
industry impacts in the same proportion as observed impacts
from the plant models.
3. SEVERAL INVESTMENT AND COMPLIANCE SCENARIOS WERE
MODELLED FOR BOTH JOBBERS AND FOR CAPTIVE ESTABLISHMENTS
The financial closure model permits plant impacts to
be estimated under a variety of different price, cost and
investment conditions. As values for these modeling para-
meters change, so, too, do the attendant closure rates. In
order to present useful and representative findings, several
decisions were made on freezing these modeling parameters
at specific values:
One regulatory scenario was used: full Pretreat-
ment for plants above 10,000 GPD, lesser require-
ments for those below.
Two financial burden schedules were used: a nor-
mal condition of 5 year repayment at a 12% cost
of capital, and a special loan program (e.g., SBA)
with a 20-year repayment at a 7% cost of capital.
A mid-range cost pass through is allowed. Here
each firm raises its prices by exactly that amount
corresponding to the incremental annualized cost
of the investment.
-------
Equity infusion test in the firms that fail the 1.5
coverage ratio criterion is limited to the one time
infusion of capital computed as the total full-time
owner's compensation plus profits after tax, minus
$15,000.
The parameters were selected to represent the best approx-
imators of probable compliance requirements for the industry
and the likely financial constraints on firms.
(1) Job Shops Could Experience Closure Rates in the
5% to 20% Range
In the presentation and discussion of sample re-
sults below, each closure condition used the 1.5 cov-
erage ratio, 100% credit for equipment in place and a
one-time equity infusion by the owner(s).
For the 205 plant models there was a distribution
of impacts reflecting:
44 closures
28 baseline closures
9 equity infusion saves
124 non-closures.
In absolute terms, 30% of the closures appear in plants
of fewer than 10 full time people, 30% of the closures
found in fiams of 10-19 people; and another 31% in
firms of 20-49 people. Firms of 50 people and above
account for the final 9% of the closures.
-------
As a function of water use intervals, 27% of the
calculated closures are in firms using up to 10,000 GPD
Comparable closure rates hold for the 10,000 - 25,000
GPD range and for 25,000 - 75,000 GPD. Closure rates,
then, are insensitive to linear changes in plant size
as measured by employment or water use.
When an SBA-type analysis is run on the 205 models
closure rates drop markedly. With reduced capital cost
and five times the loan repayment period, only 11 model
are forecast to close for an industry closure rate of
5.4%. As developed in the next chapter the total fund-
ing needed through SBA to support such minimal closure
rates is in excess of $30 million.
(2) Printed Board Manufacturers Show Sample
Closure Rates of 2% - 3%
Forty cases in the sample of 100 Printed Board
firms gave all the financial data needed for impact
purposes. Of the 40 models, there were 33 indirect
discharges: of this number there are 5 baseline
closures, 25 non-closures and 1 plant closure. On
this basis 2% - 3% of the independent printed board
manufacturers should experience plant impacts severe
enough to warrant the closing of an operation.
-------
(3) Very Few Captive Operations Are Likely to Divest
Their Finishing Production
Under the regulation, 75% of the entire sample of
captives face price increases on their finished
goods of up to 1%. Another 20% face price increases
of between 1% and 10%. Altogether there are 24 cases
or 5% of the costed sample that might be impacted
through higher requisite prices on their finished goods.
From the analysis of price increases and sales
categories, there are 20 with sales below $10 million
and 16 with sales of less than $5 million. These 16
models are firms that are relatively small, and by oper-
ational definitions the sub-set of plants capable of
divesting. A second cross-break of these same cases
is against the risk category. Of the 16 cases of in-
terest the pollution control investment increases by
50% the total prior capitalization of 14. This narrows
the potentially affected universe to 14 cases or 3%
of the sample. These 14 cases are now clearly the
smaller operations facing relatively large price in-
creases. In addition, they have relatively few em-
ployees in wetmetalfinishing and are the group most
able and most economically motivated to divest. For
purposes of this analysis 3% of all captive operations
stand for the proportion of the industry that might divest
their in-house finishing in light of Pretreatment com-
pliance requirements.
-------
*****
This concludes the presentation of sample closure re-
sults for the three sectors comprising the industry. In
the next chapter industry impacts are developed for the
total universe of indirect discharges.
-------
-------
v. ECONOMIC IMPACTS
This chapter extends the closure results of the prior
chapter to the population of all firms affected by the metal-
finishing regulations. To do so accurately involves dis-
tributing closures due to the regulation by a suitable sizing
measure: In this case, the wetmetalfinishing employment in-
tervals. It requires also showing industry economic impacts
due to the regulation as opposed to closures due to the pres-
sures of the marketplace. In sequence, then, the subjects
of this chapter cover:
Closure rates
Industry impacts
Price behavior
Total compliance burden.
The sample results were presented by job shops, Printed
Boards and captives; the industry economic impacts will be
presented in the same order.
(1) Job Shops Could Experience a 15% - 20% Loss in
Capacxty
The first table below, Table V-l, presents total
plant closures under the Pretreatment scenario with al-
lowance made for baseline closures. The industry clo-
sure rate here is 19.9% on a weighted basis.
-------
TABLE V-l
Total Plant Closures in the Job Shop
Sector Under the Regulation Arrayed
by WMF Employment Intervals
Number of Firms
Size of
Dischargers
Possible
Firm
Total
to POTW
Closures
1-4
1,156
1,045
223
5-9
682
658
141
10-19
546
524
112
20-49
357
339
72
50-99
159
142
30
100-249
41
26
6
2,941
2,734
584
*
The total number of plant closings due to the
Pretreatment scenarios also represents impacts on
sales and employment. In Table V-2, appearing below
page, the lost sales and lost employment of the regu-
lation are presented.
TABLE V-2
Sales and Employment Losses Due to the
Regulation Job Shop Closures Arrayed
by WMF Employment Categories
Size of Lost Sales* Lost Employment*
Firm Closures (Millions) (Thousands)
1-4 223 $ 57.3 0.7
5-9 141 44.7 1.2
10-19 112 66.9 1.8
20-49 72 83.3 2.7
50-99 30 55.4 2.3
100-249 6 27.7 0.9
584 $335.3 §76
Taken by multiplying the closures by the mean value for
the interval.
-------
This regulatory scenario has the effect of dis-
lodging 15.9% of the industry's production volume and
14.0% of its total employment.
(2) An SBA Loan Program for Job Shops Could Mitigate
Impacts Substantially ~~
There is the possibility that individual firms
may succeed in their application for special federally
supported funds (SBA). In this event, the loan re-
payment period is extended to 20 years and interest
cost reduced to 7%.
Under the regulation and after baseline firms are
removed, 9 models or 5% of the cases are predicted to
close. On an industry-wide basis, this means 137
of 2,734 job shops discharging to a POTW might close
due to Pretreatment requirements. A summary of these
impacts appears in Table V-3 below.
TABLE V-3
Sales and Employment Losses Due to the
Regulation Job Shop Closures, SBA Financing
Arrayed by WMF Employment Categories
Size of
Firm
# in
Population
# of Lost Sales Lost Employment
Closures (Millions) (OOP's)
1-4
5-9
10-19
20-49
50-99
100-249
1,045
52
33
26
17
7
2
$10.7
.2
.2
.3
.6
.5
.3
658
524
339
142
26
8.3
11. 6
14.7
6.2
2.0
2,734
137
$53.5
2.1
-------
SBA financing has the effect of reducing total
plant closures by 77% (584 to 137), reducing lost sales
by 84% ($335 to $53.5) and lost employment by 78%
(9,600 to 2,100).
(3) Printed Board Manufacturers Face Impacts Consider-
ably Below Those Expected in the Job Shop Sector
The presentation of industry-wide impacts for the
Printed Board sector will parallel that of the job
shops. Under the Pretreatment scenario, closure rates
weighted and corrected for baseline closures are 3.1%.
Table V-4, immediately below, arrays closures under
the Pretreatment scenario. As was found in the review
of job shop closures, there are no significant differences
in closure rates by size intervals. The population
receives a 3% closure across all sizing intervals.
TABLE V-4
Estimated Plant Closures for
Printed Board Makers
Size of
Dischargers
Possible
Firm
Total
to POTW
Closures
1-4
16
13
0
5-9
62
50
2
10-19
78
63
2
20-49
171
139
4
50-99
57
46
2
100-249
12
12
0
250+
4
4
0
400
327
10
-------
The economic significance of these 10 estimated
closures is summarized in Table V-5, below. These
data show that as many as 321 people and sales of $9.4
million could be displaced.
TABLE V-5
Sales and Employment Losses
for Printed Board Makers
Size of
Firm
5-9
10-19
20-49
50-99
Possible
Closures
2
2
4
2
Lost
Employment
12
25
124
160
Lost Sales
($000's)
$ 500
1,100
3,800
4,000
10
321
$9,400
Under the regulation, overall closure rates are
found to be 3% of the industry. Plant closings account
for the loss of 321 positions and sales volume of
$9.4 million.
(4) An SBA Loan Program for Printed Board Makers
Would Reduce Impacts to Zero
Under the 20 year and 7% interest rate assump-
tions of an SBA loan program, the total number of
model plant closures is 0 out of 40 plants. The in-
dustry should experience no disruption were a federally
supported loan program in place, and all applicants
acceptable.
-------
(5) Impacts In The Captive Sector Are Estimated To
Be Small But Measurable
"Closures" for the captive sector were derived
through a partially qualitative assessment of firms
likely to divest the operation. That analysis identified
those firms facing high investment costs, with low plant
sales and large predicted price increases (10%+).
Under the regulation, some 14 cases out of 536
indirect dischargers were identified as potential clo-
sures. Under the definition of a captives closure this
means certain types of operations could stop in-house
finishing and purchase the service from suppliers in
the job shop market.
In many respects, projecting the captive closures
is a worst case scenario: captive operations are pro-
bably integral to a plant's production function. Clo-
sures probably will not occur.
Table V-6, on the following page, arrays sample
captives by wetmetalfinishing intervals and displays
the total number of captive closures by interval. Sales
and finishing employment losses are projected in Table
V-7, following Table V-6.
-------
TABLE V-6
Projected Total Captive
Closures by the Regulation
Number of Firms
Size of
Dischargers
Vulnerable
Firm
Total
to POTW
Operations
1-4
2,372
1,833
55
5-9
1,164
884
26
10-19
1,103
884
26
20-49
955
748
22
50-99
271
203
6
100-249
157
131
4
250+
55
39
1
6,077
4,722
140
TABLE V-7
Employment and Sales Effects of
Captive Closures Due to the Regulation
Size of
# of
Mean Sales*
WMF
Firm
Closures
(Millions)
Employees
1-4
55
$ 15.9
120
5-9
26
13. 6
150
10-19
26
29.8
330
20-49
22
45.0
630
50-99
6
17. 5
390
100-249
4
19.2
570
250+
1
11.1
420
140
$152.1
2,610
* Value Added by Finishing
-------
Were these 140 captives to divest their finishing oper-
ations, 2,600 wetmetalfinishers would be in the labor
pool and some $152.1 million of finishing work added
to the demand side of the job shops.
(6) Compliance With The Regulation Represents a Direct
But Generally Manageable Economic Impact on The
Indirect Discharging Segment of the Metalfinishing
Industry
As a summation of the specific industry impacts
of the regulation for the metalfinishing industry,
Table V-8 below arrays total costs and annual costs
for each segment of the industry.
TABLE V-8
Total Economic Impacts of Pretreatment
Compliance for the Metalfinishing
Industry by the Regulation
Investment Annual
Segment Costs Costs
(Millions) (Millions)
Job Shops $ 187.6 $ 62.5
Printed Boards 18.5 6.8
Captives 1,134.4 424.6
$1,340.5 $493.9
A large proportion of the capital and annual cost
is incurred in the captives sector. These operations
will spend 5 times the amounts projected for the other
-------
segments combined. The average estimated capital
cost for captive shops is $240,000 and the average
estimated capital cost for the job shop is $87,400.
On the macro level, the study findings mean the
following:
Price for metalfinishing goods and services
is expected to rise on the order of 7%. This
is a level that is required on average by the
industry to pass on the incremental annual
costs of the abatement system for Pretreatment.
The figure is on the order of 2% for Printed
Board makers and less than 1% for all other
manufacturing establishments with in-house
finishing operations.
For the independent segment of the industry
(jobbers plus Printed Board makers) 19% of
all firms now in business might close as a
result of the investment requirement of meet-
ing the Pretreatment standard. Given that
demand remains high and that product substi-
tution is unlikely, the following should hold:
Some new firms will enter the marketplace,
perhaps begun by production managers of
a captive operation
-------
Each remaining firm in the industry can
probably either raise his price more than
7% or expand his production capacity to
meet the demand
Predicted closures will be less than cal-
culated if:
Water use is controlled; reduced by
good-houskeeping or engineering changes
Abatement equipment is homemade rather
than professionally supplied
Production equipment runs past its
depreciated life.
Price impacts on the finished goods due to capital
investment in pretreatment equipment are expected
to be on the order of 1%. Given that no industrial
sector attributes more than 10% of the cost of the
finished good to metalfinishing, cost increases
of up to 10% in finishing should be reflected in
small point of sale price increases.
If plant closings do occur, it is not anticipated
that they will be felt directly within the com-
munity or region. Metalfinishing job shops do
not represent a large proportion of the total
production employment within any one city. Were
closings to occur, some job transfers to the
surviving firms would have to occur.
-------
At the national and international level, economic
shifts in the domestic metalfinishing industry
are not expected to have any noticeable effect
on trade balances. A somewhat different con-
dition holds on Printed Board products. This
is so for two reasons. First, finished boards
are being imported and second, domestic man-
ufacturers send out and then reimport their
own finished wiring boards. Depending on
trade policies, domestic production of Printed
Boards could increase despite the incremental
cost of Pretreatment.*
* "An analysis of the Market for Printed Boards and Related
Materials." 1976 Technical Marketing Associates, prepared
for the Institute of Printed Circuits.
-------
-------
VI. LIMITS OF THE ANALYSIS
The purpose of this chapter is to discuss the issues
that bear upon the "power" of the study; the data and analytic
constraints that must be made explicit in order for the es-
timates of industry impacts to be held in perspective. Ac-
cordingly, three topics require review:
Utility of data
Analytic methods
Strength of conclusions.
Each point will now be developed in sequence. Key to this
review is one central fact: study results derive from a
plant-specific microeconomic model. Therefore, the applica-
bility of results rests with how well the data, logic and
assumptions of the model mirror the realities of actual
plant operations.
1. DATA HAVE TO BE EVALUATED ON THE BASIS OF QUANTITY
AND QUALITY
In this section, we treat two data related issues:
sources of data and the quality of data.
(1) The Data From the Survey
Appendix D is devoted to an exhaustive review
of the development of survey instruments, response
-------
rates and sample bias. Here the focus is directed
more toward the implications for the analysis of data
limitations rather than a review of methodological
issues. In this vein, the following needs to be made
explicit.
Although the respondents to the survey pro-
vide sufficient data for analysis, the 444
can be viewed as one slice drawn from the
population. Had a different set of firms
chosen to respond, the results conceivably
could be different. Random selection theory
says that in enough trials, sample data
must converge to the population's parameters.
But although sample selection was designed
to be random, patterns of respondents might
contain biases.
The phone survey to non-respondents was de-
signed to test this issue explicitly. The
follow-up effort focused special attention
on smaller firms. Finding differences be-
tween the respondents and non-respondents
was inevitable. But financial data were
not sought since they were too sensitive,
and no conclusion can be drawn on whether
respondents are more or less financially
sound than non-respondents.
-------
Identifying 205 plant models for the closure
analysis did not fit the rigorous random
selection rules for the sample as a whole.
These cases were used because they provided
all requisite data for analysis, not because
they necessarily reflected the sample. Anal-
yses, however, on models and non-models as
well as on respondents and the entire balance
of the targeted sample suggest that the models
are a strong cross-sectional representation
of the industry.
Data are from a single point in time. There
is little capability to appreciate trends
over time or to reflect the changing capac-
ity of any one firm to handle the pollution
control investment. An approximator is to
cost part of the system as a proxy for invest-
ment over time; but this is clearly not the
same as having a dynamic closure model that
varies sales, profits, taxes, long-term
debt and cash flows.
Costs are an important analytic component.
We have not utilized the specific computer
generated cost estimates of the Technical
Contractor. Rather, we have built his cost
-------
data into our linear regressions and developed
cost equations on a per component (installed)
basis. The linear regression is a simplified
A to B relationship of cost to water usage.
As shown in the Appendix, however, compari-
sons of cost estimates to outside vendors
yield generally good agreement.
(2) Quality of the Data
There are two primary considerations in discussing
data quality; their reliability and their validity.
Reliability is satisfied by knowing that the Fame re-
spondent would provide the same response to a question
at Time2 that he did in Time^. Resurveying the sample
in six months to assess the reliability issue is impos-
sible. But if data are valid, they are, by definition,
reliable.
Answering the question of data validity requires
exploring a set of data interrelationships. This is an
approach to establishing validity by judging how well
sets, or independent estimates of the same variable, agree
(convergent validity). Examples of efforts to establish
the data's validity are presented below:
-------
Data from the survey on specific parameters tend
to agree with prior, independent estimates. The
sample provided information on employment and
sales which, when extrapolated to the population,
are not significantly different from estimates
on the same variables available from the U.S.
Department of Census.
Financial data from the survey were compared
against comparable data elements available on in-
dividual plants through Dun & Bradstreet records.
The strong agreement on data items within a group
(i.e., model plant data in 1975 and 1977) as well
as across groups (i.e., respondents are not sig-
nificantly different from the balance of the sample
universe) supports the presumption of valid re-
sponse data to the survey.
Throughout the analysis, limitations of the data are
cited and the analytic assumptions introduced to the com-
putations are made explicit. In addition, the conscious
effort of the analysis has been to control error by making
results more, not less conservative. Decision rules were
generally established to be more rigorous than they might
be in practice. As examples, not plant models were assumed
to reduce flow in order to come in below the cut-off; all
plants were costed for professionally designed, engineered
-------
systems. Both rules may exaggerate compliance costs and
probably plant impacts. Industry impacts could also be
mitigated if any number of other factors proved to hold in
practice: e.g.,
Owners have capital and access to capital in ex-
cess of that allowed by the model
Owners would reduce their compensation to $10,000
or $7,500 for the one year, not $15,000
More, rather than fewer, firms have treatment
equipment in place
Most firms engineer their own treatment system
or purchase second-hand equipment rather than
purchase outright from an industrial waste treat-
ment supplier.
Use of a coverage ratio of 1.5 is a moderately rigorous re-
quirement coupled to the bank's requirement that the owner
guarantee the loan. It is quite apparent that many factors
go into a bank loan decision. There may be cases where
finishers receive loans because of history of repayment and
pro-forma's even though the coverage ratio falls below 1.5.
2. THE FINANCIAL CLOSURE METHODOLOGY IS BUILT ON DATA
AND LOGIC BUT IS NOT ENTIRELY FREE OF ASSUMPTION
A model is a set of algebraic statements, objective
functions and decision rules incorporating data, designed
-------
to yield an outcome. Appreciating all ingredients of the
predictive model, its input data and algorithms are the key
to assessing the quality of the model's output. Without
critically reviewing each part of a model, it is not pos-
sible to judge the credibility of the model's estimates.
(1) The Capabilities of the Model Are Built From and
Complement High Quality Data
Considerable effort was made to balance the anal-
ytic requirements of the economic closure model with
the quality of the source data available from the
field. Just as the pollution control cost program
could not generate accurate and complete component
costs without a full set of technical information, so
too the economic model needed adequate financial data.
But certain simplifying steps were taken in the interests
of obtaining responses that have to be fully shared and
understood.
No previous year's financial statements were
available. Only the sales trend for the
firm is known. As a consequence, there is
a limitation in the ability to tell if any
one firm is at the beginning, middle, or
end of a boom or bust.
-------
Completely detailed financial reports could
not be requested because of the time limita-
tions of a self-administered survey. The
statements were abbreviated and omitted cer-
tain line items that might have altered the
calculations of debt, profitability, and
return.
Coverage ratios, rather than pure cash flow
measures, were the key closure criterion.
Although the use of coverage ratio as a
predictor can be justified, other measures
for which we had no data could also have
been used. Closure estimates might be dif-
ferent were a different criterion used.
Return to the owner is an important economic
criterion and was set using a combination of
Profit After Tax plus owner's compensation.
Clearly, there are opportunity costs to
staying in metalfinishing and to alterna-
tive uses of capital. As a consequence,
there is no proof that all predicted clo-
sures will choose to close, nor that all
designated non-closures will opt to make
the investment to remain open.
-------
(2) Some Elements of a Full Economic Impact Analysis
Have Not Been Included
At this point, there is no impact analysis of new
sources: firms likely to enter the marketplace to
provide the displaced supply of the closures. To
some degree, then, the structural recomposition of
the industry cannot be appreciated.
Also omitted, as of now, is the user charge com-
ponent of pretreatment costs. User charges are to
be developed by POTW's and applied through appropriate
formulae to the various point sources using the muni-
cipal system. That cost component is absent now, and
may be factored into subsequent cost/impact analyses.
To the extent it increases the costs of compliance for
pretreaters, total compliance may be somewhat under-
stated. However, through prior surveys, User Charges
are known to be a small component of the total operat-
ing expense of a plant and not a prime driver of clo-
sures. In a separate report the economic impacts of
hazardous waste disposal requirements (RCRA) will
be costed and applied to the industry.
(3) Some Assumptions Had to be Made
In the logic and calculations of the financial
closure model, a specific set of assumptions had to
-------
be made for the sake of analysis. Certainly, this is
true for any analysis. In some respects, appreciating
the magnitude of the findings is dependent on accept-
ing some of these assumptions:
For the sake of calculating closures, it
was necessary to introduce the decision rule
of a "one-shot" equity infusion by the indivi-
dual full-time owners. This was done in order
to prevent inclusion of a firm as a closure
if it lacked several hundred to several thou-
sand dollars in investment capital. But by
so doing, survey results indicating the reluc-
tance of many owners to reduce their compen-
sation were overriden. Again, the actual
decision-making preferences of individual
firm owners is not known. It is possible
that no set of questions could predict that
behavior; perhaps the owner himself will not
know until the decision is imminent.
All firms with reported equipment in place
were not costed for the impact analysis if
their equipment matched the treatment re-
quirements of each pretreatment scenario.
It is not known whether existing installed
equipment performs up to the standards of
-------
the equipment costed by the Technical Con-
tractor. If it does not, a certain number
of firms might have to be added to the clo-
sure analysis and closure estimates could
increase.
(4) Baseline Closures Have Been Treated Somewhat
Judgmentally
The basic function of the economic impact analysis
is to relate the capital burden of abatement compliance
to the viability of the industry. Such an analysis
requires mechanisms for distinguishing industry im-
pacts due to the Act, from those other market/economic
factors that also determine success and closure rates
in the industry. This might be accomplished by identi-
fying segments of the industry already quite marginal
and likely to close for reasons totally separate from
the incremental operating burden of pollution control
investments. Such firms are labeled "baseline closures."
After this group is factored out of the population, all
subsequent closures can be attributed to the effects
of compliance.
The method used to cull baseline closures from the
sample was to apply a constant capital burden of $100
to all models to test for pre-investment vulnerabilities.
This approach eliminated 28 jobbers and 5 Printed Board
-------
firms. While there is no proof that these marginal firms
truly will close, it is interesting to note that the
estimate parallels some other data. These 33 baseline
models are 10% of all independent firms. As a percent,
this baseline closure rate matches closely the annual
turnover rate found in the Dun & Bradstreet industry
files for SIC 3471 and 3479 (10% annually 1975-1977).
3. CLOSURE ESTIMATES FROM MODELING ARE QUITE ROBUST AND
CAN SERVE AS POPULATION PREDICTORS
It is at this point that the overall assessment of
the study effort is drawn. In light of the method selected,
the tests applied and the results generated in virtually all
respects, the effort met its goals. In sum, the following
elements support this conclusion:
Primary field data for characterizing the industry
were sought. To this end, three separate surveys
were commissioned and executed. Response rates
for the mail efforts were on the order of 39% for
the captives and 45% for the jobbers. The core
data for analysis are, therefore, the largest base
for analysis ever available.
Estimates of impacts were to be derived through
the application of an automation routine using
actual field data of representative plants. This
analysis is dependent on three factors;
-------
Accurate Costs
Valid financial reports
- Comprehensive variable modeling.
Estimates of pollution abatement costs were
verified for internal consistency and external
accuracy. They satisified both.
Eliminating probable baseline closures from the
sample results has the effect of limiting impacts
just to the cost of Pretreatment. Culling the
28 cases from the data base of 234 models yields
more than 200 models. Tests of models and non-
models, and then respondents to non-respondents
established the legitimacy of these 200+ cases
for drawing population estimates.
Applying an automated financial closure routine
introduces many advantages and a few drawbacks.
The primary drawbacks to the routine are two-fold:
(1) the model is more a static than a dynamic
model, and (2) it is limited to a pure capital
decision matrix. The implications are as follows:
Time trends cannot be appreciated
Interactive effects of key variables cannot
be measured
"Soft" variables are not part of the routines'
specification, i.e., owner's attitudes, local
-------
markets or enforcement policies are not
reflected in the logic of the model.
Results of the routine, however, show a basic
insensitivity to minor variations in input speci-
fications. As an example, overall closure results
are about the same whether sales or profits go up
or down 10%, whether price pass through is 5%,
10%, or 15%, or coverage ratio 1.4, 1.5 or 1.6.
In sum, the model is robust with respect to al-
ternative variables and insensitive to minor shifts
in data values.
All plants, regardless of process water volume,
are required to treat their lead and cadmium.
Any plant predicted to close might survive if it
could productively divest its lead and cadmium
plating. There are no- data on this possibility,
nor does it lend itself to rigorous modeling.
*****
This chapter has presented the limits of the analysis.
The Appendices that follow provide detailed discussions on
the field survey, the costing model and the study design.
-------
APPENDICES
A. THE METALFINISHING JOB SHOP
SECTOR SURVEY
B. THE PRINTED CIRCUIT BOARD INDUSTRY
SURVEY
C. THE CAPTIVE METALFINISHING INDUSTRY
SURVEY
D. SAMPLE DESIGN AND SURVEY ISSUES
E. AUTOMATED FINANCIAL CLOSURE
METHODOLOGY
F. THE POLLUTION ABATEMENT COST
GENERATING PROGRAM
G. VALIDATION OF THE POLLUTION ABATEMENT
-------
-------
THE METALFINISHING JOB SHOP SECTOR SURVEY
This appendix presents the survey results, instrument
and data for the metalfinishing job shop sector survey and
arrays the pooled results of the respondents. In Appendix
D, all the validity tests and extrapolation rules are dis-
cussed at length so they are not covered here.
For purposes of presentation, this Appendix is orga-
nized in three sections:
Sample results
Survey questionnaire
Raw response data
All data, other than capital costs, are presented here so
that the reader might appreciate directly the findings
and conclusions presented in the text.
1. APPROXIMATELY HALF OF ALL METALFINISHING JOB SHOPS
LISTED IN THE DMI ARE PROJECTED TO FALL WITHIN THE
REGULATIONS OF THE ELECTROPLATING CATEGORY
More than 5,500 metalfinishing establishments are
listed in the DMI. Our projections, based on the survey
results, show that 2,941 firms or 54% of the population
do regulated processes.
-------
The total size of the universe subject to regulation
was derived by extrapolating the survey results in the
following manner:
Eligibility returns from the phone follow-ups
were extrapolated to all survey non-respondents.
These data were added to the eligible responses
from the mail survey to form the total eligible
sample.
Combined results were than multiplied by the
original fixed interval sampling value of 2.5
to yield the estimate of the projected population.
The data for the extrapolation are presented in
Table A-l below.
Table A-l
Estimate of the Universe of
Metalfinishing Job Shops in
the Electroplating category
(Arrayed by Metalfinishing Size)
Size
Mail
Phone
Weighted
Interval
Results
Results
to DMI
Correcte
1-4
65
53
1,089
1,156
5-9
80
32
643
682
10-19
109
28
515
546
20-49
111
10
337
357
50-99
46
18
150
159
100-249
12
3
39
41
250+
0
0
0
-
Missing
21
0
169
-
Total
444
144
2,941
2,941
The total estimated population of job shops affected by
the regulations of the Electroplating Point Source Category
is 2,941 firms. The largest cluster of firms is in the 1-4
man interval with almost 40% of the total.
-------
More than 80% of the industry consists of firms em-
ploying fewer than 20 men in metalfinishing production.
Table A-2 below, arrays the industry on key descriptive
elements. Shown here are employment, sales and plant water
use. All entries have been extrapolated by weighted means
multiplied by cell frequencies.
Table A-2
Total Industry Employment
Sales & Water Use (000's)
Size
Total
Total
Total
Interval
Employment
Sales
Plant Water
1-4
7.6
$ 30.0
13.9
5-9
9.3
22.7
15.3
10-19
11.6
27.9
17.7
20-49
16.2
42.1
38.7
50-99
13.4
28.1
22.6
100-249
7.0
19.2
5.7
65.3
$170.0
113.9
This extrapolation yields an industry picture as follows:
65,000 people work in job shops with an average shop
having 22 employees
Sales for the industry are $1.7 billion with the
average shop selling slightly more than a half
million ($580,000).
On a daily basis the industry uses 114 million gallons
of which 90 million is for metalfinishing production
use.
-------
2. SAMPLE FINDINGS PROVIDE A VALUABLE APPRECIATION OF THE
METALFINISHING INDUSTRY AND ITS PROBLEMS
A respondent was included in the study if he performed
any of the following processes:
A—Electroplating (common metals)
B—Precious metals
C—Reserved
D—Anodizing
E—Coatings
F—Etching, engraving
G—Electroless plating
H—Printed Circuit Boards
To clarify our understanding of the mix and prevalence
of these production processes, each survey respondent was
asked to check off all metalfinishing processes performed at
his plant.
Fully 77% of all survey respondents do at least
electroplating of common metals. The second most frequent
process is Coatings (55%), followed by Polishing and Grinding
(44%) .
Regardless of the size of an establishment, these same
three processes occur most frequently. Table A-3, on the
following page, arrays the processes against the entire sample,
and then by the six size intervals.
-------
Table A-3
-Frequency of Performed Process
By Size of Firm
Firms With Employment of
Total
Processes
Sample
1-4
5-9
10-19
20-49
50-99
100-249
Electroplating
77.7%
71.9%
77.6%
77.1%
82.9%
71.7%
76.9%
Precious
23.6
23.4
31.8
14.4
28.8
23.9
15.4
Anodizing
23.9
12.5
17.6
22.0
35.1
30.4
38.5
Coatings
55.3
35.9
49.4
59.3
64.0
65.2
46.2
Etching
24.5
18.8
22.4
21.2
27.9
39.1
23.1
Printed Boards
2.4
1.6
5.9
—
2.7
2.2
7.7
Polishing
44.0
57.8
38.8
41.5
47.7
32.6
53.8
Number of
Respondents
440
67
85
118
111
46
13
Exploring the potential significance of produc-
tion processes resulted in cutting the data in two ways:
Separating single versus multiple process
firms
Identifying total number of processes done
On the first point, the data showed that only
19% of the sample (82 firms) did just one process.
Of these 82 firms doing just one process, 50 (61%)
do just electroplating.
More than three-quarters of the sample does no
more than three separate production processes.
-------
(1) Ownership Patterns Both Describe the Industry and
Affect the Decision Rules of the Impact Analysis"
Prior economic impact analyses modeled owner-
investment decision making with respect to meeting the
costs of pollution abatement controls. In these analy-
ses, the following assumptions were made:
That an owner would reduce his compensation
to stay in business
That his compensation was large enough to
allow a significant equity infusion
There were sufficient numbers of owners will-
ing to do so to make a difference in the
estimated closure rates.
The survey provides data on all these items.
Since the variable "ownership structure" pertains first
to an understanding of the industry's composition, and
then to an appreciation of the potential economic im-
pacts upon it, data are ordered by:
Ownership patterns
Owner's compensation
Owner's attitudes
For the entire sample, the median number of owners in
a firm is 2, of whom 1.5 work at the establishment full
time. Individuals own about one-third of the firms (31%)
as do families (34%) and small groups (31%). Fully 90%
of all firms are owned by four people or fewer.
-------
Larger firms tend to be owned by families or
groups whereas smaller establishments are much more
likely to be held by an individual, small business man.
Ownership patterns are presented in Table A-4 below.
Table A-4
Ownership Patterns by Size
of Metalfinishing Establishment
Size Total Employment 100-
Ownership
1-4
5-9
10-19
20'
-49
50-99
249
Individual
52.5%
32.9%
33.6%
22
.0%
18.6%
25.0%
Family
27.1
38.0
29.0
37
.0
41.9
-0-
Small Group
18.6
26.6
33.6
38
.0
27.9
41.7
Another Firm
1.7
1.3
2.8
2
.0
11.6
33.3
Total
99.9%
98.8%
99.0%
99
.0%
100%
100%
In order to characterize more accurately individual
owner's compensation, the number of owners working full
time in each type of establishment must be identified.
Data were gathered on total number of owners, those
working full or part time, and the dollar value of the
owner's compensation. One assumption that must be made
for this analysis is that the bulk of the value given for
owner's compensation is distributed evenly across each
owner working full time. To the extent that owners work-
ing part time at the facility draw sizable portions of
the reported compensation, our estimates will overstate
the full-time owner's compensation.
-------
Table A-5, below, arrays firms by size, total
number of owners and the reported total compensation for
all owners.
Table A-5
Owner's Compensation by Firm
Size and Number of Owners
Total Employment
1-4
5-9
10-19
20-49
50-99
100-
249
(Total Owner's Compensation $000'
s)
Individual
1
$17.1
$26.1
$26.1
$37.2
$ 45.3
$66.1
2
23.5
25.2
48.0
56.3
58.0
-0-
Family
3
35.6
36.3
36.3
77.1
82.3
-0-
4
74.5
34.7
37.6
69.7
61.1
-0-
5
-0-
70.1
40.9
46.7
103.1
-0-
Small
6
-0-
22.5
36.0
30,0
-0-
-0-
Group
7
-0-
-0-
-0-
86.4
-0-
-0-
8+
-0-
-0-
-0-
-0-
98.6
453.0
From related calculations on the survey returns, the
number of full-time owners by type of establishment
is the following:
Virtually all firms owned by one person have
just one full-time owner. Therefore, com-
pensation for full-time owners will remain
the same as the first line of Table A-5.
-------
For all firms owned by families, e.g., those
having 2, 3, and 4 owners, the mean number
of full time owners is 1.79 (S.D. = 0.9).
These data range from 1.6 full-time owners
in small shops to 2.1 in the largest.
In firms owned by small groups, e.g. , those
with 5, 6, 7, or 8+ owners, the mean number
of full-time owners is 2.3 (S.D. = 1.4).
ay introducing these corrective terms for full-time
ownership, Table A-5 can be recomputed to yield the
mean compensation for each full time owner across the
different firm size categories. In Table A-6, below,
the reported total owner's compensation has been recom-
puted to yield the individual full-time owner's
compensation.
Table A-6
Total Annual Compensation for
Individual Owners Working Full Time
\8iEe
Ownership"""--".^
1-4
Individual Owner's Compensation
5-9 10-19 20-49 50-99 100-249
1
$17.1
$26.1
$26.1
$37.2
$45.3
$66.1
2
14.4
15.6
25.8
30.6
28.1
-0-
3
21.8
22.5
19.5
41.9
39.9
-0-
4
45.7
21.5
20.2
37.8
29.6
—0-
5
-0-
39.8
21.0
20.1
26.9
-0-
6
22.5*
36.0*
30.0*
-0-
•0"
7
-0-
-0-
-0-
37,2
-0-
-0-
8
-0-
-0-
-0-
-0-
25.8
98.4
~Unadjusted
A-9
-------
(2) Owner Attitude Data Do Not Support the Assumption
o? Reduced Compensation To Stay in Business
There were 286 respondents who answered the item:
"What is the likelihood that you might reduce the owner's
compensation to help secure a bank loan (for a waste-
water treatment system)?"
The scoring ranged from "very unlikely" to "very
likely." Presented below is a summary of attitudes:
For all 286 respondents, 183 or 64% said it
was very unlikely, or unlikely. Only 46 or
16% scored it likely or very likely.
Splitting the sample by size or type of firm
did not change the response pattern by much:
88 respondents (31%) already have some
treatment equipment in place. Fully
68% of them say it was very unlikely or
unlikely that they would reduce compensa
tion to help pay for more.
198 respondents (69%) have nothing in
place. Of these 198, 133 or 67% also
say it is very unlikely or unlikely
they would reduce compensation to pay
for a system.
Owners of larger firms are just slightly
more likely to consider reducing their
compensation than are owners of smaller
shops. On the following page, is a
summary table of the responses to the
question by size of firm. The answers
"unlikely" or "very unlikely" have been
recombined to a single "No" response.
There are only 2 72 rather than 286 cases
because 14 respondents gave no employ-
ment size data.
Table A-7, on the following page, summarizes
just the negative attitudes.
-------
Table A-7
Proportion of Sample Indicating Reluctance
To Reduce Owner's Compensation
1-4 5-9 10-19 20-49 50-99 100-249 Total
Number
Answering 31 52 73 74 33 272
Combined
"No's" 20 30 48 46 23 174
Percent 64.5 57.6 65.7 62.1 69.7 77.7 64%
This presentation of owner attitudes toward
compensation, reduction roust close with a caveat.
People who returned the questionnaire could have had
many different motivations for participating, two of
which could be:
They were sufficiently on target with abate-
ment requirements that they felt comfortable
describing themselves to the EPA.
They felt themselves so vulnerable that the
survey provided them a vehicle to bring their
plight to the attention of the agency.
There is a strong possibility that the responses to
the item on reducing owner's compensation are biased:
biased in the direction of showing vulnerability to
the regulations through restricted personal freedoms
to absorb the incremental costs of compliance. It is
not surprising that many reported they would not or
could not reduce their compensation if many respondents
-------
judge the compliance process as punitive, burdensome,
and disruptive.
* * * *
This concludes the summary of selected survey findings.
The next sections contain the survey instrument and the study
data.
-------
NATIONAL ANALYSTS
& vision of Boos, Allen & Hamilton
Philadelphia* Pa.
Study #1-557
Fall. 1978
METALFINISHING STUDY
Respondent's Name: 1
Title:
Organization: -
Street Address:—
City; StaU; - Zip:
Instructions
There are six sections in this questionnaire dealing with your
firm; its products, markets and operations. Please answer all
questions in each section. If you are not certain about a question
perhaps one of your staff knows the answer. Make every effort
to return the completed questionnaire to us as soon as possible.
A postage paid return envelope is provided. If you have questions
that we can answer, feel free to place a collect call to
Mr. Nat Greenfield at the Booz, Allen Office in Washington. He
can be reached at (202) 293-3889.
For purposes of confidentiality, please answer the following
question. Do your answers include material you consider
(CIRCLE APPROPRIATE CODE)
xes
—I—
No
-------
SECTION 1: PLANT DESCRIPTORS
The four questions in this section deal with the products and characteristics of your
firm. Your answers are important to our understanding of the diversity of the metal-
finishing industry.
1. From the list of metalfinishing activities shown below, please circle the codes
for all the activities normally performed in your firm.
(CIRCLE
CODES)
Electroplating of common metals (for example,
copper, nickel, zinc, chromium, cadmium)
1
Electroplating of precious metals (for example,
gold, silver, platinum)
2
Anodizing
* 3
Coatings (for example, chromating, phosphating,
or immersion plating)
4
Chemical etching, milling, and engraving
5
Printed circuit boards
6
Polishing, grinding
7
Other (Please Explain):
0
NOTE
IF YOUR SHOP ONLY DOES POLISHING AND GRINDING WITH .NO
WET METALFINISHING PROCESSES, THEN ANSWER NO FURTHER
QUESTIONS AND PLEASE MAIL BACK THE QUESTIONNAIRE IN
THE SELF-ADDRESSED ENVELOPE.
2. Please indicate the total number of people working full-time at this location.
Then give us the number of employees working just on the wet metalfinishing
lines by each shift.
(PLEASE
WRITE
NUMBER OF
EMPLOYEES
HERE)
Total # of full-time people ¦
Shift 1 wet metalfinishing production employees ¦
Shift 2 wet metalfinishing production employees ¦
Shift 3 wet metalfinishing production employees »
-------
Please describe your physical plant in terms of the following uses of ft.oor space
(in square feet).
(PLEASE
WRITE IN
NUMBER OF
SQUARE
FEET)
Total area of the plant
Total area used by all production
operations
Total area used by wastewater
treatment facilities
Total area available for expansion
inside the plant
Total area available for expansion
outside the plant
£
Many shops in the metalfinishing industry that discharge an effluent may already
be covered by a regulatory agency. Which of the following types of authorities
regulate your effluent?
(CIRCLE ALL
THE CODES
THAT APPLY)
Local (including city, county
or region)
1
State
2
None of the above
9
Don't know
V
-------
SECTION 2: MARKET CONDITIONS
The five questions in this section deal with the market in which your firm operates.
Your answers to these questions will help us understand how competitive the metal-
finishing industry is.
1. Each of the following items has two possible answers. Indicate only the one
that best fits your firm. You may find that sometimes both answers are true
or that neither is quite right. Try to select just the one that comes the
closest. (PLEASE CIRCLE CODE NUMBER)
,
A. Does your firm specialize in services to a major industry (i. e., automobile,
aerospace, etc.) or do you service many different industries ?
Specialize in service to an
industry
1
Service many industries
2
B. During the year are most of your sales to a few steady customers or to
many different customers?
Few steady customers
1
Many different customers
2
C. Do your customers send you many different kinds of products (all shapes
and sizes) or do you get basically the same products most of the time?
Many different products
1
Basically the same products
2
D. Do you generally attract customers because you can offer low prices or
because you can take on any assignment?
Offer low prices
1
Take any assignment
2
E. Do you face a lot of competition for your customers or relatively little?
Lot of competition
1
Relatively little
2
F. Do you think captive operations also compete for your customers ?
Yes, they do
1
No, they don't
2
-------
2. The last time you raised your price (for whatever reasons) what percent price
increase did that represent?
%
same'
Fell off
1
Remained the same
2
4.
Today, IF YOU AND ALL YOUR COMPETITORS had to raise prices, how much
do you think you could raise them before your business might be badly hurt?
(PLEASE GIVE YOUR ANSWER AS A PERCENT)
% Price Rise
5.
If business fell after a price increase, your customers could be doing several
things. B.lo» LJ . li.« of fir. Ihing. th.y do. H.„. judf ho»
likely each one is by circling a number next to each possibility.
Very
U nlikely
Unlikely
Maybe
Likely
Very
Likely
Customers might buy more from
captives
1
2
3
4
5
Customers might eliminate metal-
1
2
3
4
5
Customers might start their
own inhouse, captive lines
1
2
3
4
5
Customers might shop around
more for the best price
1
2
3
4
5
Customers might use some other
finish for metalfinishing
1
2
3
4
5
The fourteen items in this section will help us understand the different activities that
occur in metalfinishing plants. We are aware that many shop* handle many different
operations. Sometimes you may have to give us your best estimate for some of the
questions.
1. Altogether how many total hours per day are spent in wet plating and/or wet
finishing operations:
Hours / Day
2. Altogether how many days per week are spent in wet plating and/or wet
finishing?
Days/Week
-------
3. We would like to know the degree of automation in your operation. From the
list below, please circle the code that best fits your plant.
Programmed control 1
Fully automated 2
Semi-automated 3
Manual 4
4. From the list of electroplating operations shown below, please check off all the
ones that you normally do.
Electroplating
A. Copper Solder Platinum metal group
Nickel Lead Iron
Chromium Tin Brass
Cadmium Gold Bronze
Zinc 'Silver Other (write in)
From the list of other metalfinishing operations shown below, please check off
all the ones that you normally do.
B. Anodizing
Coloring
Phosphating
Chromatin#
Other Finishing Processes
Electroless on plastics
Electroless on metals
Chemical milling
Non-aqueous plating
JBright Dip
"Chemical Etching
"Electrochemical
Milling
Stripping
For each metalfinishing operation checked off above, please indicate the metals
you etch, mill, strip, or plate electrolessly.
C.
_Copper
_Nickel
"Chromium
"Cadmium
"Zinc
_Solder
Lead
"Tin
"Gold
"Silver
Platinum metal group
Jron
"Brass
JBronze
"Other (write in_
-------
5*
How many cleaning, plating, finishing and rinse tanks do you have on your
floods) ?
# of Process Tanks
6. How many separate production lines do you have set up normally to handle
your metalfini3hing operations?
# of Production Lines
For each production line identified above, we would like a description of what
is finished and bow it is done. Please enter the finishing sequence (i. e..
coooer nickel chrome) whether rack or barrel, time, and the total number
0?taS:s set up for th^ line. An example has been provided as a guide.
Line #
Plating/Finishing Sequence
Rack or Barrel
(Circle One)
Hours/Day
in Operation
Total Tanks
on the Line
Example
l
R B
a.
LQ.
2
R B
R B
3
4
R B
5
R B
6
R B
7
8
R B
R B
For each production line, we would like a description of how you finish the
products run on that line. Since different jobs are run on the same line, please
use average or typical values for time and thicknesses.
Line #
Immersion Tims*
(Topical)
Thickness of Finish*1*
Applied or Removed
(Tvoical)
Amperage of
Finishing
Tanks***
1
2
3
4
5
6
7
8
* In minutes
** In mils or thousandths
-------
9.
If you have any data on area plated or finished, it would be very useful to us
in our effort to describe industry operations. Please write in your area data
below, or attach it to the back of the questionnaire.
Line
Area Plated, Finished
or Removed
Area in sq. units / Unit Time
1
2
3
4
5
6
7
8
Total Plant
10. Please fill in the table below showing your plant's water use for a typical day
during 1975. Use gallons per day (GPD) if available. If your information is
in cubic feet, please note it in the table.
Water Use
GPD
\otal Plant
Metal Finishing
Processing Water
Other:
Cooling
Boiler
Sanitary
-------
Now please indicate where your discbarge water goes.
A. (CIRCLE THE CODE WHICH BEST DESCRIBES YOUR ANSWER)
Municipal sewer system
1
River, lake. pond, other
2
Both
3
B. Do you have the option of switching from your present means of water
discharge to another?
Yes
1
No
2
If yes, please describe the nature of your option:^
If you discharge to a municipal sewer system, would you please write in your
1975 total sewer costs and the name of the agency, department, or authority
that sets the formula for sewage rates?
$
Sewer Costs ' Agency Name
How many pounds of sludge do you produce a month?
# of Pounds/Month:
How is the sludge disposed?
(CIRCLE ALL
THE CODES
THAT APPLY)
Land fill
1
Into water or sewer
2
Incinerator
3
Lagoon
4
Trash pickup
5
Other (Write in):
0
Don't know
-------
SECTION 4: FINANCIAL ISSUES
-I
The four questions in this section deal primarily with the financial condition of firms
in the industry. Most of the items can readily be answered by using your 1975 balance
sheet and profit-and-loss statement. Remember that your answers will be held
strictly confidential, if you indicate so.
1. Would you please indicate how your firm is organized?
Who owns it?
(CIRCLE
CODE
NUMBER)
How many owners
are there?
How many of these
owners work:
Full-time
Part-time
An individual
1
A family
2
A small group
3
j Another firm
C<)
Other (PLEASE WRITE IN):
0
2.
From 1972 to 1975, how would you describe the changes in your annual sales?
(CIRCLE THE CODE NUMBER)
Sales were increasing steadily
1
Sales were decreasing steadily
2
Sales moved in cycles
3
Sales were about the same
4
3.
For the six items shown below, please enter the 1975 year-end values from your
profit-and-loss statement (or best estimate).
1. Sales
2. Rent or lease payments
3. Owner's/officer's compensation
(include salary, bonus, and
dividends)
4. Depreciation (building and
equipment)
5. Profit before tax
S. Profit after tax
1975 Dollars
$
$
-------
4.
Listed below are five items found in your balance sheet. Please enter the
1975 year-end values (or best estimates).
1975 Dollars
1. Current assets
$
2. Fixed and other assets
$
3. Current liabilities (include
accounts payable, working
capital loans from banks, etc.)
$
4. Long-term debt
$
5. Company net worth
$
5.
Many shops have made capital investments in their plant (e. g., building, land,
and production equipment). From your balance sheet, please enter the book value
shown for these assets, and indicate how much more you plan to invest over the
next five years (please do not include planned investments for pollution control'
Book
Value
Remaining
Life
Expected Investment
Over Next
Five Years
a. Building
$
yrs.
$
b. Production equipment
$
yrs.
$
c. Land
$
$
SECTION 5:
WASTEWATER TREATMENT SYSTEM
N£2£.
ONLY FIRMS HAVING A WASTEWATER TREATMENT SYSTEM NOW (OR
EXPECTING TO HAVE ONE IN THE NEXT SIX MONTHS) NEED TO COMPLETE
THIS fi-PfrrTON. AT T, HTTTRPS MAY GO ON TO SECTION 6...
This section will let us see how many firms already have invested in a pollution control
system. It also will clarify the industrywide effects the guidelines could have on
metalfinishers.
1. Shown below are the features of a wastewater treatment system. Please circle
the code number for each feature that makes up your system.
pH adjustment
1
Lagoon
6
Flow equalization
2
Separate cyanide stream
7
Chromium reduction
3
Separate hexavalent-chrome stream
8
Cyanide destruction
4
Countercurrent rinse
9
Pr e cipitator -clarification
5
Reverse osmosis, evaporation, ion
exchange or other advanced treat-
0
ment technologies
-------
Please provide the following information about your wastewater system.
A. How much did it cost to purchase and install?
$
B. In what year did you make the last major addition to the system?
Y ear;
C. What is its designed treatment capacity? Please record in gallons per day.
Gallons/Day Capacity:
D. How much does it cost each year to operate? (Include costs for labor,
energy, chemicals and upkeep.)
Annual Cost to Operate 9
F. Did you contract for any part of the design, construction and installation
of the system or did you do it aU yourself?
(CIRCLE
CODE
NUMBER)
Contracted for some
1
Did all myself
2
G. Did you reduce your water use to put in the system?
(CIRCLE
CODE
NUMBER)
Yes
1
No
2
Don't know
V
NOTE
IF YOU MAY HAVE TO UPGRADE OR EXPAND YOUR WASTEWATER SYSTEM
IN THE NEAR FUTURE (I.E., 2 TO 3 YEARS). PLEASE GO ON AND COMPLETE
SECTION 6. IF YOUR EXISTING SYSTEM COMPLIES FULLY WITH THE REGU-
LATIONS, YOU HAVE FINISHED THE QUESTIONNAIRE. YOU ARE INVITED TO
ADD COMMENTS ON THE BACK PAGE BEFORE MAILING THIS BACK TO US IN
-------
SECTION 6:
INVESTMENT OPTIONS
NOTE
FIRMS HAVING NO WASTEWATER TREATMENT SYSTEM NOW, AND FIRMS
THAT MIGHT ADD TO THEIR SYSTEM IN THE FUTURE ARE REQUESTED
TO FILL IN THIS SECTION.
The five questions in this section help us understand how the gmdelines will affect you
and the entire industry. Remember that your answers wxU be kept stnctly confidential
if you wish. We are not asking what your firm will spend for pollution control. We
only want to know how you are approaching the investment ecision.
1.
; 2.
You may have an estimate for the design, purchase, and installation of a new
wastewater system or to add to the one you already have. If so. please write
in that estimate below.
$
Purchasing a wastewater system could depend on the ability of your firm to
raise capitkl. From the list belo« please circle all the code numbers for
sources of capital open to you for the purchase.
Source of Capital
(CIRCLE ALL
CODES
THAT APPLY)
Profits (cash flow) from the business
1
Personal funds (increase equity)
2
Loan from customers/suppliers
3
Small Business Administration Loan
4
Commercial bank loan
5
Other (PLEASE SPECIFY):
0
None
9
-------
3. Purchasing a system could also depend on having a place to install it. From the
list below please circle the code number{s) of the spaces available for a system.
(CIRCLE ALL
THE CODES
,TTTAT APPLY1
On presently available floor space
1
On space presently used for plating or
finishing operations
2
On specially constructed facility in
the plan, e.g., balcony
3
Outside the plant on my property
4
Outside the plan on land I would have
to buy
5
No place to put it
6
4. If you lacked space to add to, or to install, a wastewater system, several options
might be open to you. Below is a list of three possibilities. Please judge how
likely each one is by circling a number next to each possibility.
Very
Unlikel-v
Unlikelv
Mavbe
Likelv
Very
Likelv
a.
Take out a production line
to free up floor space
1
2
3
4
5
b.
Pay to alter the facility, for
example, by knocking out walls
or building a balcony
1
2
3
4
5
c.
Pay to relocate to a bigger
facility with more floor space
1
2
3
4
5
5. If you had the room to put in a wastewater system, but couldn't raise the capital
right now, you might still have several options. Below is a list of four pos-
sibilities. Please judge bow likely each one is by circling a number next to
each possibility.
Very
Unlikely
Unlikely
Maybe
Likelv
Very
Likely
a.
Add to working capital by
selling off some of the assets
of the business
1
2
3
4
S
b.
Reduce the owner's compensa-
tion to help secure a bank loan
1
2
3
4
5
c.
Close down the business,
retire or do something else
1
2
3
4-
5
d.
Try to find a buyer for the
business, or set up a merger
1
2
3
4
5
-------
SECTION 7: OPINIONS AND IMPRESSIONS
ATe wish to encourage you to make comments in this section. Please take this
opportunity to express your opinions on:
This questionnaire:
The economies of your firm:
The regulatory process:
EPA'a policies:
THANK YOU VERY MUCH. PLEASE PUT THIS IN
-------
NATIONAL analysts
METAL FINISHING STUDY 1557-11
QUESTION NO.1-1 WHICH OF THESE METAL-
.FINISHlNG-ACXjVITlES-AftE-NOftMALLX
PERFORMED IN YOUR FIRM?
- - - - NUMBER OF FULL-TIME PEOPLE
100=
TOTAL 1-4 5-9 10-19 20-49 50-99 2*9 -
[fj&t_JJNDER S1Q0M S250M iSQOH »1M1L »2.5
KWE HOOM -249M -499M -999M -2.4 MIL*
-461- -64 B5__.il» ill >6.
__A61 6V M __ Ua .1X1 M 11
100.0 100.0 100.0 100.0 100.0 100.0 100.0
09
86
13
NUMBER -ANSWERING.
100.0 100.0 100.0 100.0 100.0 100.0
10
65
66
46 66 SI 92.
E L£ C TROfcLAI J CDMHO]
METALS
24
1 £
lit.
21 17 32
CLECTROOJ.ATIMG- OF PRECIOUS-
METALS
109
39 _14
_110 t.
21
52
255 2| 42 70 __ 71 30 *_
53
9*
C0AI1NGS
.25 31 19 3
12 1
CHEMICAL -ETCHING. MILL1 NG &
ENGRAVING
113
,11 1 5
2.4 1.6 5.9
jet INTEO-ClRCUlt. BOARDS
1.9 4.9
2.7
2.2 T.T
1.1
37 33
It.
*9 53 11
203.
POLlSHlNGi-GBltlDING.
2 3 _
1 3.5
AIMER.
4.5 B.7
-------
NATIONAL ANALYST*
MfTAL MNIfrHINO STUDY
ium/t* participants
1397-11
out 57 I OH HO. I-/A TOTAL NUMBER Of FULL-
TIME CMTLOms
TOTAL
total
441
1-4
44
- - NUMBER OF FULL-TIME PEOPLE T&TAL SAL t S
100- 230- 300b UNDER S100M 1230* S300M *1MIL *2.3
!-! 10-19 20-4» 3D-»» 24» 4»» MOKE %IQUA -IHiH -49M -?8»« -J.i B1L»
• 3
in
in
44
13
3H
• 9
92
• 4
49
11
NO ANMCR
21
NUMBER ANMCKtMQ
NOME
1-4
3-»
10-19
20-49
30-99
100-249
250-4*9
440 44 »5 111 111 44 11
100.0 100.0 100.0 100.0 100.0 100.0 100.0
3
.7
• 4 44
14.1 100*0
as
i»«i
118
24.•
111
25. 2
46
10*9
11
1*0
63
100.0
lit
100.0
111
ioo.o
44
100»Q
19
109.0.
32 ti at 82 47 12
100.0 100.0 IUQmU IB0*0
2
3.1
14
43*4
1
1*1
10
13 41 9
2ltl »B*2 iPii
1
32 33
37.4 _M»2
1 23
1»2 i»»4
.1 ti
1
1*2
2
it*
12
1S.».
1
_2.1
1
*,}
39 12
J2»0_2JO.
( 29 4
3 7
IP
900 OR MORE
AVERAGE
23
14
32
70 133
10
14
32
44
13B
002
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY
SURVEY PARTICIPANTS
I597-1J
QUESTION NO.1-28 NUMBER OF MET METAL-
:MUSM1NC -PRODUCTION EMPLOYEES ON 5HIFT 1.
-TOTAL
NUMBER OF FULL-TIME PEOPLE -- ---TOTAL SALES
100- 250- 3006 UNDER S100M S290M S500M S1M1L S2.5
Jr4_ 5-9 10-19 20-49 50-9S __2^S 49? MORE SIOOM -249M -499M -999H -2.4 MILf
TOTAL
NO ANSWER
NUMBER ANSWERIN6
NONE
1-4
9-9
10—19
20-49
90-99
100-249
290-499
900 OR MORE
AVERAGE
461
46
64
10
0S US
111
46
1)
419 94 76 109 107 44 19
100.0 100.0 100.0 100.0 100.0 100.0 100.0
-IH
9
-5.6
1
liJ.
196 91 49 41 10
-ST.6__t4.4_64.5—37.6 9.3.
91 26 94 22
.21.9 54.2 31.2 20.6
1
. 2.J
4
1
7.7
90
2l.7_
94 42 19
31t2__39«9 22i9_
61
IV, 7_
10
2,*_
99 20 7
J0i(__4>-LJ}iL
6 4
X9»A- 39ii_
1
¦ 2l_
1
7.L
11
19 28 49
94
89
92
86
49
13
47 81 S3 80 46 12
100.0 100.0 100.0 100.0 100»0100.0
4
6.9
39 47 29 13
13 .Q ifl.O 30 .1 16.3
1
_Zj2_
1
JjI.
4 29 28 16
8.9 30.9 33.7 20.0
1 2
2*2 16.7
9 28 29 16
11.1 33.7 31.3 34.8
1
8.3
2 25 23 4
2.4 31.3 90.0 33.3
1
1.3
S 3
10.9 25.0
1
_lti_
19 26 40
-------
NATIONAL ANALYSTS
METAL FINISHING STUOY
SURVEY PARTICIPANT 5-
1997-11
QUEST ION NO.I-2C NUMBER OF MET METAL-
_£iNISH2NG_PRQ0UCI104L£MPLQYE£S_0N_SMlET_2
-XOIAL-
- - - - NUMBER OF FULL-TIME PEOPLE TOTAL SALES
tOO- 290- 9006 UNDER'SXOOM S250M S500M S1MIL S2.9
_Ir* 5-9 ID-19 2Q-49 10-99 249 488 MOKE S100M -?*9M -499M -999H -2.4 MtUt
TOTAL
461
64
•9 11*
111
46
13
34
•9
92
•6
49
19
NO ANSWER
47
10
NUMBER ANSWERING
NONE
1-4
5-9
10-19
20-49
90-99
100-249
414 94 76 110 107 49 19
.100.0.100.0-100.0_ 100.Q_lQQ.0_10Q.Q_lflQ.flL
249 94 69 69 48 10
-6Q*1-_10Q
9 17 2
11.9 97*0 16.7
1 12 5
1.9 26.1 41.7
290-499
900 OR MORE
AVERAGE
11 26
19 18
-------
national analysts
METAL FINISHING STUDY (557-H
SURVEY PARTICIPANTS
\
QUESTION NO.1-20 NUMBER OF WET METAL-
FINISHING PRODUCTION EMPLOYEES ON SHIFT 3
- - NUMBER
TOTAL 1-4 __ 5-9 10-19
OF FULL-TIME
29-4?_SJLt»9
PEOPLE
100- 250- 9006
249 499 MORE
UNDER
S100M
- T 0
S100M
-249M
T A L
S250M
-499M
SAL
S500M
-999M
E S -
SIMtL
-2.4
<2.5
MIL+
TOTAL
~61 64
•5 ua
111 46
13
54
89
92
86
49
13
NO ANSWER
SO 10
9 9
4 1
7
9
10
6
3
1
NUMBER ANSWERING
411 94
100.0 100.0
76 109
100.0 IOOjO
107 45
100.0 100.0
1)
100.0
47
100.0
• 0
100.0
•2
100.0
80
100.0
46
100.0
12
100.0
NONE
>52 54
•5.6 100*0
73 102
96.1 95.6
• 7 24
01.3 53.3
5
38.5
46
97.9
76
95.0
75
91.5
65
81.3
24
52.2
7
58.3
1-4
25
6.1
3 7
3.9 6.4
11 3
10.3 6*7
1
7.7
1
2.1
4
5.0
7
6.5
7
8.8
4
8.7
5-9
IS
>.2
9 >
8.4 6.7
1
7.7
6
7.5
5
10.9
1
8.3
XO-If
14
3*4
11
24.4
3
23.1
2
2.5
9
19.6
2
16.7
20-49
7
1.7
4
S.9
>
23.1
4
8.7
2
16.7
50-99
100-249
290-499
>00 OR MORE
AVERAGE
1
1 9
10
1
5
7
-------
( NATIONAL ANALYSTS
METAL FINISHING STUDV
survey participants
1957-11
QUESTION NO*1-2 NUMBER OF MET METAL
FINISHING PRODUCTION EMPLOYEES ON
SHIFTS 1*2* ANO 3
- - NUMBER
OF PULL-TIME
PEOPLE -
100- 230- 300t
---TOT
UNDER' SI OOM
A L
S250M
SAL
S500M
E S -
SMIL
m m
*2.5
TOTAL
1-4
5-9 10-19
20-49
90-99
249 499 MORE
S100M
-249M
-499M
-99VM
-2.4
H1U
TOTAL
461_
44
6%
85 US
111
46
13
54
89
92
86
49
13
NO ANSWER
10
9 •
*
1
7
7
9
6
2
1
1
J
I
3
5
m
l
~ IT
S4
.14 HO
_1°T
43
13
47
•2
S3
80
47
12
100.0
100.0
100.0 100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
NONE
6
3
1
4
1.4
9*6
1.3
8.5
1-4
129
91
39 26
9
1
1
36
38
IS
10
1
1
SO.9
»4.4 SI.3 2J.i
fc*4
2.2
7.7
76.6
46.3
21.7
12. 5
t;i
8.3
5-9
• 1
3* 31
¦
2
7
29
20
10
1
19.4
47.4 2B.2
7.5
4.4
14.9
JS.4
24.1
12*5
8.3
10-19
96
S3
99
6
15
43
20
6
1
23*0
44.2
32*7
13.3
IS*}
51.8
25.0
12*9
1.3
20-49
79
95
16
2
2
38
21
3
14.0
J1.4
39.6
1J.4
2.4
47.5
44.7
"75.0" 1
90-99
2»
20
9
2
IS
2
T»fiT
4*.4
3«.9
2*5
38*3
16.7
100-249
5
9
1
4
1.2
38.5
2*1
3J.I
290-499
fOO ON MORE
AVERAGE
16
2
4 9
20
43
SO
3
6
10
20
43
65
004
J
-------
NATIONAt ANALYSTS
METAL FINISHING STUDY 1997-11
SURVEY PARTICIPANTS
QUESTION NO.I-3A WHAT IS THE NUMBER OF
^SOU&BE -fEET _g£_ELQQg„SPACE. IH_ _tHE..IQTAL_
AREA OF THE PLANT*
TOTAL
total 1"4
NUMBER OF FULL-TIME PEOPLE TOTAL SALES
100- 290- SOPS UNDER S100M S290N »>QOM S1M1L «2.9
5-9 10-19 20-49 90-99 2*9 499
_I5 lit U1 4* 1I_
MORE SIOOM -249M -499M -999M -2*4 MIL*
54 <9 92 86 49 13
HP ANSWER
.17.
JUHBERJlttStfEftliKL
LFSS THAW «.OOQ SO. FT.
9.000 TO 9.999
10»000 TO 19>999
-lfl-»OTO TO ITiitt.
40.000 OR MORE
AVERAGE
.*44
60
f3 UI 106_
_4J_
100.0 100.0 100.0 100.0 100.0 100.0 100.0
_42L
JL
23.2 70.0 91.• 7.T 1.9
7.7
Alfl.
.12 31.
_46.
Jfc.
24.• 20.0 37.3 39.3 19.1
lia
24.4
J5
* 9 49 41_ 6
0.0 IKS 41.9 "IT. T 14.0
14. «
JL
_ | 36 14 9
6.0 34.0 32.6 i#75
10.¦
.» 11 23 7
4. i nf75 fTi5 53.8
mi; 4273 9406 12398 20484 39114 99992
93
87
91
82
47
13
100.0 100.0 100*0 100.0 100.0 100.0
41
29
77.4 33.3
9 34
9*9
il
2.4
9
7.7
17.0 39.1 37.4 11.0 2.1
2 23 39 37 9
i.i li.i, ki.t 45.1 16.6
1 1 8 24 21 2
T7v 171 878 IT,i 4477 15.4
1 10 20 10
1.1 12.2 4,2.6 76.9
4138 6966 10878 20707 36206 63307
-------
f
national analysts
METAL FINISHING STUOT 1557-
SUBVFV PARTICIPANTS
11
QUEStION NO.[-}B WHAT IS THE NUMBER OF
SOUARF FPET l* FLOOR SPACE IN TOTAL
AREA USEO BY ALL PRODUCTION OPERATIONS*
NUMBER
OF FULL-TIME
PEOPLE - -
100- 230-
5006
TOT
UNDER S100M
A L
S250M
SAL
S500M
E S -
S1MIL
S2.5
total
1-4
5-9
10-19
20-49
50-99
249 499
MORE
S100M
-249M
-499H
-999M
-2.4
MIL*-
TOTAL
461
64
•5
118
111
46
13
54
89
92
86
49
13
NO AM*WER
21
6
5
4
s
>
1
4
3
5
1
NUMBER ANSWERING
436
58
80
114
106
43
13
53
85
89
81
48
13
100.0
100*0
ioo.o
iod.6 ioo.o
104.0
100.0
100.0
100.0
IOO.O lOO.U
1U0.U
100.0
LESS THAN 5*000 SO. FT.
155
49
58
27
12
2
49
48
24
5
2
35.6
*4.5
u.r
"IT. J
15.4
92.5
56.5
27*0
6.2
15.4
9*000 TO 9*999
109
6
19
48
23
3
4
26
34
18
6
25.0
15.)
23.8
"42.T
21.7
7.0
7.5
30.6
38*2
22.2
12*5
10*000 TO 19*999
96
3
9
32
45
8
2
11
28
36
10
1
22*0
5*2
3*8
28.1
42*3
18.6
15.4
12.9
31*5
44.4
20. i
7.7
20*000 TO 39*999
5)
5
18
23
5
3
16
24
4
12.2
4.4
17.0
53.5
38.5
3*4
19.8
50.0
jo. a
60*000 OR MORE
21
2
8
9
4
6
8
6
5.3
r.T
7.5
20. 9
30. 8
7.4
16.7
46.2
AVERAGE
11750
5146
3970
8956
16253
27363
38857
2679
5118
8298
16179
25862
44695
ool
-------
NATIONAL ANALYSTS
METAL FINISHING STUOY <5*7-11
SURVEY PAftII£igAai&^
QUESTION NO.1-3C WHAT IS THE NUMBER OP
SQUARE PEET OF FLOP* SPACE IN TOTAL AREA
USCO BY WASTEWATER TREATMENT FACILITIES*
- - - - NUMBER OF FULL-TIME PEOPLE ---- ---TOTAL SALES
100- 290- 9006 UNDER 9100M S250M S500M »1M1L 62.9
TOTAL" 1*4 5-S 10-19 20-49 50-99 2*9 *99 MORE 9100M -249M -'»99M -999M -2,* MIL*
TOTAL Ml ** .ML —U? ill 1» 94 «9 92 96 49 11
UGLAHSHU ft! J1 9 M J ft 2 i 9 * 6 2 I
NyMBEILAN SVER119 *1ft »? 7ft 151 *S 11 *9 «i 99 »» 12
100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
NONE 1*3 27 39 42 3« lfi 1 Ik IS U 11 I i
99.T 90.9 SO.O St.9 99.9 ».0 9*1 54.2 49.2 *2.0 41.8 19*2 16.7
!-*> sa- FT, JJL & 10 ¦ J £ S 3 * I
7.9 11*1 19.2 7.4 7.5 12.9 11*1 9.7 7.5 2*2
100-499 TO 19 14 1 • lfi ft 1 I II M .. ? I 1
16.9 24.9 29.T 16.7 9.4 10.0 27.9 14.6 22*2 19*2 11.9 6*5 9.9
SM=?U 42 ! Z 12 II A 2 4 9 9 9 9
10.1 9*4 2.6 11.1 12.9 19*0 19*2 9.9 9.9 10*2 11*9 19*6
1lO0Q-4i£M II 2 t 29 19 IS 2 2 S IS 16 25 1
21.4 9.9 10.9 21.9 29.9 97.9 49*9 10.4 11.1 21,6 20.0 43.5 59.9
*.oob QR MORE 11 s> .2 9 2 2. ,6 i.
4.1 4.6 6.6 12.5 2*9 2*9 6*9 19*0 16.7
AVERAGE M B 191 212 99S_1421—2249 1214 211 429 742 1020 2RI5 2621
-------
national analysts
METAL FINISHING STUOY 1997-11
iUKVtt-UUJClCMU—
OUESTION HO.I-90 WHAT IS THE (UMBER OP
TOTAL-ABE A..
AVAILABLE FOR EXPANSION INSIDE THE PLANT*
NUMBER OF FULL-TIME PEOPLE
.-TOTAL SALES"""
moom tmiL ai.i
TOTAL
TOTAL
4*1-
1-4
— 44
5-9 10-19 20-49 90-99 249
_B9 It*—111 44 U_
499 MORE S100M -249M -+99H -999H -2.4 MIL*
1* AS 12 » 1L
NO ANSWER
10_
100.0
100*0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
o
o
•
e
100.0
100.0
u/uir
««
*1
92
91
71
at
•
IB
i)
74
94
11
4
79.2
74.9
*9.9
00.9
72.4
72.0
• 1*9
74*0
79*9
94.4
70.0
70*2
94.9
SO. FT.
29
>
9
4
4
*
S
2
4
1
9#4
0*9
4.7
9.9
9.7
12.0
4.0
2*2
7*9
2*1
t.aoo.}f«9«
30
A
11
•
•
9
2
9
9
•
*
9.9
7.1
14.7
7.0
7.9
11.9
4.0
io.a
9.4
10.0
12*9
«
1
A
7
9
9
1
|
s
S
*
4
4
7.B
>•*
8.0
t.l
9.5
11.9
9.1
*•0
4*0
9*4
7.5
I2*i
94.4
10.000 Oft MORE
19
1
1
, 9
4_
1
1
1
I
2
4
1
1
>•0
l.B
1.2
i>*
9.7
2.4
9*1
2*0
1*2
2*2
9*0
2*1
9*1
AVEMftC
J«#4 141 Ml II.* litl l> 170 9709
749 *72 »01 1114 I21» 4»91
OM
-------
national analysts
METAL FINISHING STUDY (557-11
SUavC V-£ARX4C*£ANt&:
QUESTION NO.I-9E WHAT IS THE NUMBER OF
3UA»f FFET OF FLOOK SPACE IN TOTAL AREA
AVAILABLE FOR EXPANSION OUTSIDE THE PLANTf
- - - - NUMBER OF FULL-TIME PEOPLE - - - -
-TOTAL SALES--
TOTAL
1-*
5-9
10-19 20-*9 50—99
2*9 *99
MORE HOOM
—2*9M
—*99M
-999M
-2.*
MIL*
TOTil
*61
4*
. J9
11S 111 *4
13
9*
•9
92
at
*9
13
MO AN&MEN
41
12
10
4 11 4
7
10
9
e
*
41*
92
79
112 100 *0
13
*7
79
• 7
78
*9
13
100.0
100*0
100.0
100.0 100.0 100.0
100.0
100.0
100.0
100*0
100*0
100.0
100.0
manf
2*0
34
SI
AS 90 19
¦
3*
**
97
*3
19
4
>*•0
49*2
44.0
94.0 90.0 *7.9
41.9
72.3
59.7
49.9
99*1
*2.2
*6.2
l-*«f HQ, FT.
m
1
A
* 4 1
2
A
A
2
2
.*•»
1.9
• ¦0
3.4 9.0 2.9
*.3
7.4
4.9
2*4
*•*
21
S
5
10. 2. 1
3
*
5
*
l.i
9*4
4.7
S.9 2.0 2.9
6**
9.1
9.7
9*1
3.000-9.99*
92
7
4
19 17 *
*
11
12
10
8
1
12.4
13*5
(.0
13.* 17.0 10.0
4.9
13.9
13.4
12.8
17.8
7.7
in.OOfl OK MOBF
11
3
7
IB 24 IS
9
*
14
7
19
16
4
19.4
5.1
9.3
14.1 24.0 37.9
38.9
a.9
17.7
1.0
2*.*
39.4
*4*2
AVFBAGF
*•71
_2801
*397
7112 13820 14794 27717
5275
931*
3101
10*30
17*15
28708
011
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY x 1997-1)
SURVEY PART4C4PANT4
QUESTION NO. 1-4 MANY SHOPS IN THE METAL-
-E-INl SH INS -I NOUSTRY—THAT DISCHARCE-AM
EFFLUENT MAY ALREADY BE COVERED BY A
REGULATORY AGENCY. WHICH TYRE OF AUTHORITY
«E«ULATC tVOUR- S*fLUSMTI
NUMBER OF FULL-TIME PEOPLE - - - - ---TOTAL SALES -
100- 290- 900fr UNOER SIOOM 1290M tSOOM SIM1L (2.9
-TOTAt 1-4 5-9 10-19_20-49 JQ-99—2*9 AA9 mobC tiooM -?4«M -*Q9M -««9M -3.4 mil*
TOTAL 461 44 89 11B 111 44 13 94 89 92 86 49 1)
NO ANSWER
NUMBER ANSWERIN6 499 59 84 118 111 44 13 92 87 92 86 49 13
' lO0»D_lftO«O J.0Q.0_J00.0_10fl.0_1011.0_Jl0D.Q 100.Q 100.0 lOa.O 100.0 100.0 100.0
LOCAL 3*7 40 48 101 92 39 11 41 71 79 72 40 12
BOtl 61.• 61a0 B9 .6 _J2.8 76.1 8V.fi 7».i >1.6 A3.9 83.7 81.4 92.3
STATE 1ST IB 33 37 43 24 7 16 33 27 26 27 6
34 .7 30*9 31.1_ 31.4__9«*1_92 *2 93.8 Uil 12*3 21U 3Q.2 99*1 14^.
DON'T KNOW 34 12 6941 7799
7.9—20*3 7.1_ 7.6 3.6 2.2 LIjlS 1*4 iii UL
NONE OF THE ABOVE 9 4 1 112
. JU1 i.l •( L»i Ui 2jl3_
-------
national analysts
METAL FINI SHINS 5T00Y (997-11
SURVEY PARTICIPANTS
QUESTION NO.II-1A DOES YOUR FIRM SPECIALIZE
SERVICES TO A MA JOB IMOUSt»Y-OR-PO-XOU
SERVE MANY OIFFERENT INOUSTRlEST
-TOTAL-
TOTAL
_461
NUMBER OF FULL-TIME PEOPLE - -
100- Zifl-
1-4 S-9 10-19 20-49 90-99 2*9 *99
- - ---TOTAL SALES---
-9006 UNDER S10QM S?50M S500H ilMIL I2.L
MORE S100H -249M -499M -999M -2.4 MIL*
64
.89 1H111
tt
13
_44_
JUL
_li-
J«L
49
AX.
.HQ-ANSHER-
12
JHMRER-ANSVERIMGL
INOUSTRY
IMP'KI
_44S
_84
116^ 111 46
11_
100.0 100.0 100.0 100.0 100.0 100.0 100.0
.11
-1SL
33
.1®.
_ia_
23.2 26.8 17.9 30.2 16.2 21.7 38.9
-349
-Ml
.69
81.
9X.
_36_
T6.8 73.2 82.1 69.8 83.8 78.3 81.9
_S0
il
Jtl
86
A» IL.
100*0 100.0 100.0.100.0 100.0 100.0
JA
21 21.
JL2_
24.0 18.2 22.8 24.4 20.4 46.2
_11
JL2
Jtl
65
39
76.0 81.8 77*2 75*6 79.6 S3.8
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY <597-11
SURVEY PARTICIPANTS—
QUESTION HO*11'l» OURINC THE YEAR ARE
customers or to many different customers*
- - - - NUMBER OF FULL-TIME PEOPLE ---- ---TOTAL SALES*--
ma. >10- *Oat UMPCB tlOQM «?-9 io-i9 ao-4» so-»» a*» 499
_»sa«—an as u
MORE S100H -249M -499M -999M -l.H MIL*
¦« *2 L6 Ait IX.
NO ANSWER
_1_
_1_
-NUMBER-ANSWKR4H
-EEW -SiriOY CUSTOMFBS
-AS* 63-
-113
-Ul-
*&_
-12-
100.0 100.0 100.0 100*0 100*0 100*0 100.0
-193-
12
.SO.
.14.
_U.
U.) 90.• 46.4 91.) )0.6 26.1 98.3
MANY fllFEERENT CUSTQMEAS,
26 J .
JkL
_TT Ii_
97.7 49.2 91.6 AS.7 69.* 79*9 41*7
JU_
Jl.
w
_&6_
4«
_U_
100*0 100*0 100*0 100*0 100*0 100.0
-IX-
JttL
-13L
-14.
98*9 *4.9 42*4 3S*4 31.9 30.8
-IL.
49
93
93
33
41*9 99.1 97*6 61*6 60*8 69*2
-------
NATIONAL ANALYSTS
METAL FINISHING STUOY 1597-1)
—nam mncmim
QUESTION NO.II-1C DO YOUR CUSTOMERS SEND
DO YOU SET BASICALLY THE SAME PRODUCTS
MOST OF THE TIMEt
NUMBER_QC_£ULL-T I ME PEOPLE -
--'—TOTAL SALES-.-
TOTAL l-«
100- ISO- 900S UNDER 6100N 8290M SSOOH S1N1L 62.9
5-9 10-19 20*49 90-99 249 499 MORE S100M -249M -499M -999M -2.4 MIL*
TOTAL
461
64
•9 lit
111
44
19
94
•9
92
86
49
IS
NO ANSWER
NUMBER ANSWERING
496 63 69 117 110 46 13
100,0 100.0 100.0 100,0 100.Q 100.0 100.0
94 69 91 86 49 13
100.0 100.0 100.6 100.0 100.0 100.0
MANY DIFFERENT PRODUCTS
349 41 62 91 90 3S *
76.2 69.1 72*9 77.• 61.S 62.6 69.2
BASICALLY THE SAME PRODUCTS
109 22 23 26 20 6 4
23.6 34.9 27.1 22.2 16.2 17.4 30.8
36 64 76 67 41 8
66.7 71.9 89.7 77.9 83*7 61.9
16 29 13 19 6 9
33.3 26.1 14.3 22.1 16*3 38.9
019
V.
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY 1997-11
—SURVEY PARTICIPANTS—s =
OUESTtON NO.11-10 00 YOU GENERALLY ATTRACT
CUSTOMERS-BECAUSE YOtl CAN OfPf 10W-PR1CES
OR BECAUSE YOU CAN TAKE ON ANY ASSIGNMENT)
- - - - NUMBER OF FULL-TIME PEOPLE --.-TOTAL SALES
JOO-
2«0-
SOQfc
UNDER
SlOOtt
S?«OM
S4O0M
SI MI L
TOTAL
1"4
5-9
10-19
20-49
90-99
249
499
MORE
S100M
-249M
-499M
-999M
-2.4
MIL*
TOT At
4*
_BS
11#
II1
**
1*
«4
>«
•2
at.
49
»*
»»
7
7
»
i
4
1
9
1
1
W'WCn *iftfMCP ,aur
lift
97
H
HI
ia«
43
13
4B
aa
B7
86
48
12
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
Accra i nw Mtrrt
1»a
1*
14
1*
so
16
6
19
22
26
20
16
7
29.2
33*9
22* *
90.6
27.9
37.2
46*2
39.6
29.0
29.9
23.1
33.3
56.3
TAKF AMV lUIRIWIIT
910
it
66
ZL
79
27
7
29
66
61
66
32
9
70. *
'66.7
77.6
69.4
72.9
62.9
93.9
60.4
79.0
70.1
76.7
66.7
41.7
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY
SURVEY PARTICIPANTS
1397-11
QUESTION NO.II-IF 00 YOU THINK CAPTIVE
-OPEAAT IONS ALSO COHPEJE EflR-YOUR CUMQMEflS1
- - NUMBER OF FULL-TIME PEOPLE - - - - ---TOTAL SALES
100- 250- SOOfc UNOCR S100M «2}0M SSOOM UHIL *2.»
TOTAL
461
64 85 US
111
46
13
54
09
92
86
49
13
NO ANSWER
14
2 3 9
2
1
1
3
2
2
1
NUMBER ANSWERING
4*7
62 02 113
109
45
13
33
06
90
84
40
13
job.o ioo.o ion.a ioo.o ioo.o ioo.o
\oo.o
100.0
100.0
100.0
lOO.O
100.0
100.0
YES
»4
S3 41 74
76
37
0
26
49
36
64
35
10
63.1 J1.2 30.0 4J.5 69.7 B2.2
61.3
49.1
37.0
62.2
76.2
72.9
76.9
NO
16)
29 41 39
33
•
J
27
37
34
20
13
3
36.5 U.I SO.O 34.)
17*0
30.5
90.9
37*0
23.0
27.1
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY
SUBVfY PARTICIPANTS
1997-11
QUESTION NO#II-l SUMMARY
TOTAL
TOTAL
NUMBER OF FULL-TIME PEOPLE. TOTAL SALES
100- 290- 900* UNDER S100N S230M »SOOM S1MIL >2.)
1-* 1-9 10-19 20-49 50-99 249 *99 MORE tlOOM -249H -499M -999M -2.4 NIL*
*4
¦9 lit
111
46
19
94
•9
92
•6
49
19
NO ANSVE*
NUMBER ANSWERING
TYPE 1 COMPANY
TYPE 2 COMPANY
499 69 99 117 111 46 19
100.0 100*0 100.0 100.0 100.0 100.0 100.0
112
24.4
9 19 99 91 19 2
7.9 21.2 29.2 27.9 41.9 19.4
9
1*1
9
2.4
94 99 92 94 49 19
100.0 100.0 100.0 100.0 100.0 100.0
9 21 2J» 29 20 2
9.4 29.6 27.2 29.1 40.9 19.4
1
1*1
1
111
1
1*2
1
7.7
ALL OTHER
942 99 67 91
74.9 92.1 Tl.l 69.2
79
71.2
27 11
99.7 94.6
31 67 66 60 29 10
94.4 79.9 71.7 69.9 99.2 76.9
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY 1557-11
illBVEY PARTICIPANTS
QUESTION NO.I1-2 THE LAST TIME YOU RAISED
-3COUR-RRICC—1FQR-HHATEVER BE A SONSJ—MHA.I
PERCENT INCREASE DID THAT REPRESENTT
-TOTAL-
TOTAL
- *61-
NUMBER OF FULL-TIME PEOPLE ---TOTAL SALES -
100= 280- *001, UMOEft S100M »2S0H tSOQM tIMIL Uli.
1-4 5-9 10-19 20-49 SO—99 249 499 MORE SIOOM -249M -499M -999M -2.4 HJL+
MO~ANSWEft~
-22-
64
-6_
•j li a
UL
_A6_
_11_
Jl
020
54
_ftS_
_22_
_SA_
_41_
_11
100.0
100.0
100.0 100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
ir« Tuik « orr.
21
¦
5 6
1
1
10
4
2
2
1
5.2
13.•
6.1 5.3
.9
7.7
18.9
4.6
2.2
2.4
2.2
1-7 PCT.
193
13
19 45
40
21
6
11
30
36
30
20
8
34.9
22.4
23.2 39.5
37.7
50.0
46.2
20.a
34.5
39.6
36.6
43.5
61.5
8-12
191
26
39 45
51
18
5
22
37
37
40
20
3
44.0
44.*
47.6 39.5
48.1
42.9
38.3
41.5
42.5
40.7
48. a
43.5
38.5
11-17
44
S
10 13
11
J_
1
5
9
12
6
5
10.0
S.6
12.2 11.4
10.4
7.1
7.7
9.4
10.3
13.2
7.3
10.9
18-22
19
4
6 4
2
4
6
3
3
4.3
6.9
7.3 3.5
1.9
7.5
6.9
3.3
3.7
21 PCT. OR NORF
T
2
3 1
1
1
1
1
1
1.*
3*4
3.7 .9
.9
1.9
1.1
1.1
1*2
AVERAGE
9.06
9.1* 19.}) 6.66
9.17
7.79
7.46
8.60
9.36
9.14
9.09
8.02
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY 1397-11
S1J8VFT PA8TICL&HUS
QUESTION NO.(1-3 AS A RESULT OF THAT
-»ai£E_lNCBEASE4 47 19 11 > 191 *4 12 .. 92 84 43 13_
100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
JT£L1 QEF 120 I • 17 22 J J 19 4 10 22 22 23 19 1
27.S 31.6 21.S 23.9 30.9 *3.2 30.B 21.7 23.3 23.9 27«4 42.2 7.7
SIS 38 S3 ts 74 . 23 J *6 « TO _£1 26 12
72.2 68.4 78.3 7S.2 69.2 St.* 69.2 73.3 74.7 76.1 72.6 57.3 92.3
INCREASED 1 V
.2 .9
"021
V.
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY I517-1>
SURVEY BAHTjCiamTS '
QUESTION NO.II-A TODAY* IF YOU AND ALL
»«.«¦ wiiwnMt Tft »«irrs.
MOM MUCH DO YOU THINK YOU COULD RAISE
THEM BEFORE YOU* BUSINESS MIGHT BE SADLY
HURTT
NUMBER OF FULL-TIME PEOPLE - TOTAL SALES
100- 250- 5006 UNDER S100M S250H S500N S1M1L >2.5
TOTAL L-* a-J_10TlS 2Q-49__5Q-8? 24t ft22 MORE aiOOH -249H -499H -999H -2.4 MIL*
TOTAL «*l «« «9 US 111 46 IS 54 89 92 86 49 IS
NO ANSWER 37 12 7 6 4 8 6 5 2 4 5 1
NUMBER ANSWERING 424 92 78 112 107 38 IS 48 84 90 82 44 12
1QQ.0 JLSfi*0_lSQ.P.Ji>0.0 lfip*.fi_UUUB IWtP 10Q«P IQOtQ
LESS THAN 9 PCT. >• 8 7 11 6 2 2 964551
*. 0_19_.A 9.0 A. 8 5 « 6 Si 3_»i4 111# 111 i»4 feii 1 Lti .ill.
S-7 PCT. 91 9 12 27 21 IS 6 * 1* 22 15 14 6
21*3 9.4 15.4_.24.J—1?.6 3AjZ_44.2 JUi 16t7 »t?—?lt? ?0'0
8-12 128 1* 20 )0 42 12 2 12 25 29 31 12 3
30 .2_ .30 . 8 29 . 6 26 »J_M. 3 JL.6 lit* Ziifi Hsi 32 »2 HiS iltl j5t0
13-17 >2 10 7 13 14 5 1 8 13 10 8 5 1
12.3 19«i i.0_li.6_.13#l 13.2 7.7 !».? -M»I »«» U.4 BO.
18-22 58 7 13 16 12 4 1 5 13 13 10 5 1
13.7 _U.5 Ut7 14.]^ll»2__lO,l 1,1 lOi* liji L4xS Ui2 LLtA 8_il_
23 PCT. OR MORE 97 6 19 15 12 2 1 10 13 12 13 3
13.4 11« 5 24.4 11*4 11.2 ».» 7lI 20.8 15.5 LiiJ lisl ill
AVERAGE 12.78 19.90 19.14 12.46 12.20 10.S4 9.91 13.46 14.42 13.18 13.09 10.97 8.67
H21.
V.
-------
r NATIONAL- ANALYSTS
METAL FINISHING STUDY (557-11
emuev »tat|f-iBtMTt
QUESTION NO.I1-5 SCALE RATING OF DEGREE
OF 1 IKFLIHOOD* IF f "fluffs FFI.L AFTEI A
PRICE INCREASE* THE POSSIBILTIES THAT
YOUR CUSTOMERS MIGHT BUY MORE FROM CAPTIVES
- - MUM BE ft OF FULL-TIMF
ppnpi f - - - -
.
TOT
* L
HAL
e s -
TOTAL
1-4
5-9 10-19
20-49
50-99
100- 250- 5006
249 499 MORE
UNDER
S100M
S100M
-249M
S250M
-499M
S500M
-999M
61MIL
-2.4
>2.5
MIL*
TOTAL 4*1
64
•9 11S
111
46
13
54
• 9
92
86
49
13
NO ANSWER 2*
4
5 11
4
1
3
7
5
1
1
NUMBER ANSWERING *32
100.0
9B
100.0
BO 107
100.0 100.0
107
100.0
45
100.0
13
100.0
51
100.0
B2
100.0
87
100.O
85
100.0
48
100.0
13
100.0
1-VERY UNLIKELY 83
19.2
II
22.4
1* 20
20.0 18.7
20
IB.7
9
•20.0
2
15.4
B
15.7
13
15*9
18
20.7
15
17.6
10
20.8
3
23.1
2-UNL1KELY 95
22*0
11
19.0
14 29
17.5 27.1
25
21*5
11
24.4
2
15*4
12
23*5
15
16*3
25
28.7
21
24*7
11
22.9
2
15.4
3-MAYBE 1*1
92.6
IB
51.0
24 >0
>0.0 2B.0
39
36.4
20
44.4
5
36.5
15
29.4
25
30.5
24
27.6
31
36.5
19
39.6
5
38.5
~-LIKELY 69
14.0
B
13.B
15 IB
1B.B 16.•
17
15.9
3
6.7
2
15.4
9
17.6
17
20.7
11
12.6
11
12*9
6
12.5
1
7.7
S-VERY LIKELY 44
10.2
B
13.8
11 10
15.B 9.3
0
7.5
2
4.4
2
15.4
7
13.7
12
14.6
9
10.3
7
8.2
2
4.2
2
15.4
MEAN 2*76
2.7B
2.69 2.71
2.72
2.51
3.00
2.90
3.00
2.63
2.69
2.56
2.77
02S
-------
national analysts
METAL FINISHING STUDY
SURVEY PARTICIPANTS
I557-1>
QUESTION NO*II-5 SCALE RATING OF DEGREE
Of LlKCHHOOO* Ig—BUSIMESS-ECLL-AFXEJt-A-
PRICE INCREASE* THE POSSIB1LTIES THAT
YOUR CUSTOMERS MIGHT ELIMINATE NETAL-
-XOlAL l-V
4*1 64
TOTAL
NUMBER OF FULL-TIME PEOPLE - -
100- 250-
_3jta_I0=l.l_ZQ=*9_Sfl-a9 249 4SS
-TOTAL SALE5---
iOOfr UNDER tlOOM S2»0M »SOON (1NIL 62.5
MOBE tlDOH -J49M -499H -999M -2.4 MIL*
•9
11* 111
46
13
54
69
92
86
49
13
NO ANSWER
NUMBER ANSWERING
l-VERY UNLIKELY
2*4MLIKELY
3-MAYBE
30
10
431 94 81 109 107 45 13
_100.Q_10a.0_lQ0.0__lQa.0_lM,0 100.0 lOOfP
107 17 22 32
Z4.B_31.J_Z7.2_ 2?.4
20 13
L8*7 2Ji?
66
_20.
3 14 24 *7 6 6
_9*3—19.. 8._.22»0 ...25*2 13.3__46.Z_
4-LIKELY
102 11 U 30 23 11 3
_» *3. _20 « V __!» . % . 17 .1__U *5 _2 W«»__23ul_
79 12 19 13 It 10 1
_ll»3 22»2._23ji3 U».9 16 «8 22 • 2 1m1_
37 9
13*2 16*1-
• 10 19 5 3
.*• 9 9* Z 17# 8 U * 1 23«1_
HEAN
2*75 2.«3 2.69 2.90 2.»0 2.73 3.0S
51 84 66 84 49 13
100.0 100.0 100.0 100.0 100.0 100.0
15 21 18 21 6
29*4 25.0 20i9 25.0 16.1
1
7.7
5
j.a
13 23 20
».< 26. J 23. 8_
7 4
i4.i 30.a
9 23 24 16 U 3
17.6 27.4 27.9 19.D 22.4 23.1
13 16 12 17 13 3
21t5 1?»0 14*0 20*2 26. * 23*1
9 11 9 10 10 2
.11*4 IAaJ UUi 11.9 20.4 15*4
2.92 2.80 2.66 2.70 3.20 3*08
Mi.
V
-------
f NATIONAL ANALYSTS
METAL FINISHING STUDY
ciibucv a»tiriDiurc
1997-11
OUESTION NO.11-5 SCALE RATING OF DEGREE
OF LIKELIHOOD* IF *FH. 4*TEP *
PRICE INCREASE* THE POSSIBILTIES THAT
YOUR CUSTOMERS MIGHT START THEIR OWN
fiMtuc I ture
- - NUMBER OF FULL-TIME PEOPLE
100-
TftTAl 1-4 4-9 10-19 20-49 SO-99 249
290- 5006
499 MORE
---TOT
UNDER S100M
S100M -249M
A L
S250M
-499M
SAL
S500M
-999M
E S -
S1MIL
-2.4
S2.9
NIL*
TOTAL
Ail 64 •> 1IB 111 *6
13
54
89
92
86
49
13
NO ANSWER
IS 11 1 ( t 1
5
9
8
2
1
NUMBER ANSWERING
*2* S3 80 109 103 49 13
100-0 100.0 100.0 100*0 100.0 100.0 100.0
49
100.0
84
100.0
84
100.0
84
100.0
48
100.0
13
100.0
l^VERY UNLIKELY
*0 12 19 24 23 7
21.1 22.A 23.a 23.9 21.9 19.6
12
24.5
17
20.2
15
17.9
22
26.2
4
8.3
1
7.7
2-UNLIKELY
103 la 11 2T 26 11
24.2 90.2 13.• 24.B 24.8 24.4
7
93.a
10
20.4
20
23.a
24
28*6
14
16.7
14
29.2
4
30.8
I-MAYBE
106 13 20 27 26 12
24.9 24*9 29.0 24.8 24,8 2**7
2
1.5*4
16
32.7
20
23*8
19
22*6
25
29.8
9
18.8
2
19.4
4-LIKELY
T9 9 19 16 19 *
|?.l 9.4 23.B 14.7 14.3 20.0
3
21.1
4
a.2
19
22.6
13
15.5
15
17.9
11
22.9
9
38.5
9-VERY LIKELY
94 7 11 13 19 6
12.7 11.) 11.¦ 11.9 |4.1 11.1
1
1.1
7
14.1
a
9.4
13
H.i
8
9.5
10
20.8
1
7.7
MEAN
2.76 2.60 2.90 2.66 2.74 2*91
2.89
2.67
2*77
2.82
2.68
3.19
3.08
a»
-------
( MTfofflmWV 1997-11
«">«w •invium .
QUESTION MO.I1-9 SCALE RATING OF DEGREE
fff ^ f»fi ||«». |> BiKfiiPsc mi »IFt A
MICE INCREASE* THE P0SSIBILT1ES THAT
YOUR CUSTOMERS MIGHT SHOP AROUNO FOR THE
NUMBER OF FULL-TIME PEOPLE
100- 290- 900*
YrtTAI «-i «-0 in-J« «A.«« JtO too KOBE
UNOER
sjaaM
¦ T 0
9100M
-749M
T A L
9250H
-499M
SAL
S900M
-999M
E S-
S1MIL
-».4
92.9
MIL*
TOTAL
4*1 *4 B9 IIS 111
4S
19
94
99
92
86
49
13
NO ANSWER
21 9 1 • 2
2
9
7
1
NUMBER ANSWERING
4*0 99 84 110 10*
1AO.O 100.0 lOO.O lOO.O 100.0
49
J.UO.Q-
19
100.0
92
-ICJQjQ-
96
lOO.O
• »
100.0
96
100.0
48
100*0
19
100.0
I-VERY UNLIKELY
12 3 2 2 1
2.7 9.9 2.4 ,1.9 .9
2
4.1
1
7.7
2
9.9
2
2.9
9
3.5
1
2*1
1
7.7
2-UNLIKELY
11 I 9 1 «
>-» I.I 1.1 .9 1.7
2
3.8
2
2.9
2
2.4
4
4.7
3 "MAYBE
>1 3 10 11 4
7.0 9.9 11.9 10.0 9.7
2
1
7.7
1
9.9
6
7.0
9
9.4
6
7.0
1
2.1
4-LIKELY
111 19 22 29 29 12
29 .2 Utl 26.2 24.4 Ztit 2ijl_
1
7.7
16
90.9
19
22.1
29
27.1
22
29.6
14
29.2
3
23.1
5-VERT LIKELY
279 99 47 *7 71
ft2*>_JtI*4_.96*0 UiL
90
U.1
10
76.9
29
99.9
97
66.3
49
97.6
94
62.8
32
66.7
9
69.2
MEAN
4.42 4.19 4.90 4.44 4.91
4.4B
4.46
4.91
4.49
4.33
4.47
4.99
4*46
AM
-------
NATIONAL ANALYSTS
METAL PINlSHINft STUOY I397-1>
IURVIY PARTICIPANTS
OUESTION NO*I1-9 SCALE RAT INS Of DEGREE
OF LIKSHMOOO. If BUSINESS FELL AFTER A
PRICE INCREASE* THE POSSIS1LTICS THAT
YOU* CUSTOMERS MIGHT USE SOME OTHER FINISH
FOR MSTALMNISMIMO
- - - - NUMBER OF FULL-TIME PEOPLE ---TOTAL SALES---
100- 230- 3004 UNOER SIOOM SZ90M S300M S1MIL S2.9
TftTAL 1-4 10-19 iO-49 10-99 249 MS MORE »10OM -249M -499M -999H -2.4 M1L»
TOTAL *•! ** ¦> "> U1 *» 92 •* *»
NO ANSWER 27
NUMBER ANSWER tNfi 4S4 33 SI 110 10S 49 19 90 S3 ST S4 49 19
1qqtb |on.a i«>,p mo.o loo.o loo.o loo.o iDo.a 100.0 100.0 100.0 100.0 ino.o ,
1-VERY UNLIKELY 4S 6 12 11 » 4 1 * 7 ? 11 2 1
lflUl—10.* LA. 8 1Q.Q 1.9 1>I XmI 11 »Q Ila2 Lafl LIU 4*1 7.7
2-UNLIKELY *4 14 19 14 19 * 1 T 11 14 11 9 2
14.7 29.9 16.0 14.9 12.0 19.9 1*7 14.0 12.» 14.1 19.1 10.2 13.4
9-MAYBE »• 12 IS 24 27 10 9 12 29 IS IS 10 4
22.4 21.S 22.2 21.» 25.0 22.2 29.1 24.0 27.1 1S.4 21.4 20.4 90.S
4-LIKELY 107 11 17 2t 26 10 « 10 22 27 IS 19 4
¦_ *4.7 20.0 21 20.0 29.9 91.0 21*4 26*3 90.S
9-VERY LIKELY 11* 12 21 90 99 19 2 12 22 29 26 i» 2
25.* _2I« J 90.4 )bl 13 H*Q »~? HtS—Uii
MEAN 9.44 9.1S 9.27 9.46 9.96 9.9S 9.94 9.1S 9.4S 9.92 9.44 9.S6 9.91
422.
v,
-------
NATIONAL ANALYSTS
METAL FINISHING STUOt 1557-11
SURVEY—PARTICIPANTS ,
QUESTION NO.III-X ALTOGETHER HOW MANY TOTAL
-HOURS. PES - DAY ARE- SPENT IN -WET _P LA TING
AND/OR WET FINISHING OPERATIONS*
-TOTAL -
TOTAL
46L-
NUMBER OF FULL-TIME PEOPLE --rTOTAL SALES
1 00=l_-25fl=._5QQfr UNDER ilQOM i2 5QM »OQM »1MIL *2.5
1-4 5-9 10-19 20-49 50-99 2*9 499 MORE *10OM -249M -499M -999M -2.4 MIL*
-64
_B5-
118-
-111.
.46_
li
.54_
JL2_
97
_4S_
_U_
NO- ANSWER
20
10.
-NUMBER- ANSWERING
t-TO-BHQURS
9 10 16.
-441.
59.
B5 lOt
108
-45,
.13,
—17JTO 24_HOURS.
AVERAG
100.0 100.0 100.0 100.0 100.0 1C3.0 100.0
211.
59-
.62 4#
.32 8.
47.8 84.7 72.9 44.4 29.6 17.•
14? ? 20 47 45_
33.8 15.3 23.5 43.5 41.7 >5.6 23.1
81
.13.
21,
JL0_
IB.4 3.5 12.0 2B.7 46.7 76.9
UtJ4_6.Bl_B.94ll.31 13.M_17.Z8_ 2Q.1L.
_5i
At.
_82
JtL.
_11_
100.0 100.0 100.0 100.0 100.0 100.0
40 57 37 32 4
75.5 67.1 41.6 39.0 8.5
12 23 40 30 16
22.6 27.1 44.9 36.6 34.0 46.2
_J2_
JUL
JJ-
1.9 5.9 13.5 24.4 57.4 53.8
_Li4l1 £±16 n.» ».22 18«2L.
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY
tUKVf Y-P A4UICIBAHTS-
1997-11
QUESTION NO.I11-2 ALTOGETHER HOW MANY
-MVS-PER-WEEK AWE SBENT—IN -WET—PLATING
ANO/OR WET FINISHING*
-TOTAL-
TOTAL
- - NUMBER OF FULL-TIME PEOPLE ---TOTAL SALES
U>0= |«n. »n«L iiuncn'pom mny t4
•a
92
ib
49
_11_
mtwrnwc
THAU 1 hkY
JJ1.
.60.
.•1 117 111.
_44_
iL
100.0 100.0 100.0 100.0 100.0 100.0 100.0
JUL
JJl.
91
Ji 1L
iL
100.0 100.0 100.0 100.0 100.0 100.0
-I JOJ-OAYi-
-A.0AYS-
_Z__DAI5_
-AVERASC-
.9 *.7
.40i_
.32 7* 107-
_»*_
A 2
1L
*0.1 66.7 91.4 91.9 >9.2 91.3 *4.6
.2 6_
.10 10_
7.7 9.3 7.4 8.3 9.0 «.7 19.4
1.1 3.3 1.2 1.9
_*.94_-4.50 _ 4.99 9.03 5.0a_3.09_3j.QL
9.7
_AL
JUL
¦ 2
_ZA_
12
90.6 93.0 90.1 BS.4 87.6 92.3
3.1 7.0 7.7 10.5 12*2
rrf
2.2 1.2
4*42 4.96 9.05 9.05 9.10 s.oa
029
V
-------
MATIOMAL ANALYSIS
METAL FINISHING SIUOV
tUftVt¥~*AflT ItlPAMTft
I99T-11
OUfST ION III-J WHAT IS THC DEGREE Of
AUTOMATlOM IN YOU* PLANT OPERATION*
TOTAL
441
TOTAL . 1-4
NUMBER OF FULL-TIME PEOPLE ---- TOTAL SALES---
100- 250— SOOt UNOER ilbOM *250M J500M S1MIL J2.3
5-9 10-19 20—49 $0-99 249 *39 *IQ8l£ J1D0H -2MM. -AS9.M -S9JJ1-2.4 Mik*.
*4
•9 11*
111
46
1)
54
¦ 9
92
<~9
13
NO ANStfCR
NUMBER ANSWER INO
PROGRAMME0 CONTROL
FULL* AUTOMATED
SEMIAUTOMATED
MANUAL
494 99 19 117 110 46 1}
100.0 100.0 100.0 100.0 100.0 100.0 1CIQ.0
11
2.9
n
7.5
10J
22.7
304
*7.0
1
1.2
«
10.2
93
6
9.1
9
7.7
14 27
14.5 21.1
70
79
3
2.7
11
10,0
31
2«.2
65
3
4.3
9
19«t
13
2a.3
21
. 3
)».S
4
30.8
92 *« 91 S3 49 13
lCO.QUOO*Q.abQjQ_lQQ»CLig&j0-JQ-£ifL
iti.
1
1 •!._
3
4
6 • 6
<~
>• 7
4
iti
I
7,7
5 12 3
S«9 24.5 J3.]_
6 IT 20 30 13 4
11.5 _.1?. 1 _22 1*1 ... 2i t5
89,• *2.4 64.1 99.1 49,7 _30,B
46 70 62 46 20 9
JI9.5 73 tl 6Lii 94 si. *ftil _i8iL.
030
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY (997-11
SUKVSV- RAM4CINANM :
QUESTION NO.II1-4 TYPES OP FINISHING
OPERATION* NORMALLY BCINE
NUMBER OF FULL-TIME PEOPLE TOTAL SALES
100- 290- 900S UNDER S100M S2S0N S900M SlHlL S2.9
TOTAL 1-* J-9-10-19 2Q^49_S0-9S £49 *98 MOW IIOOM" -249M -499M -999H -2.A ULL±_
TOTAL 441 *4 99 lit 111 *6 13 94 99 92 S6 *9 13
NO ANSWER
NUMBER ANSHERINO 499 S3 99 lit 111 *9 13 94 »9 92 94 49 13
iafl. 4
44.1 AO.3 >9.9 99.3 73.0 42.2 44.2
34 99 43 99 32 B
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY
t557-11
QUESTION NO.M1-3 HOW MANY CLEANING#
»LAT-IMG»-£4NlSHlNG ANO_RINSE_JANtS DO—
YOU HAVE ON YOUR FL00*1 SIT
TOTAL
TOTAL
-—441.
- - - - NUMBER OF FULL-TIME PEOPLE ----TOTAL SALES-
L00-_i50- apQ4 UNOFH «lQOtl t?SOM SSOQM »1MII
1-4 5-9 10-19 20-49 50-99 2*9 *99 MORE SIOOM -249M -499M -999M -2.*
>2 .5
HQ ANSWER
64 IS lH-
ll 2 1_
_X11.
Ji6_
-u_X
Jt2_
_82_
_ftA_
_*2_
MIL*
Li_
100,0 100.0
100,0 100.0 100.0
100.0
100.0
100.0
100. 0
100.O
100.0
100.0
100.0
in m i r«
92
2T
22 24 7
4
1
21
16
16
B
2
2
20.4
43. 5
26.2 21.1 6.9
8.7
8.3
39.4
18.6
17.6
9.4
4.3
16.7
n-n
194
33
40 55 31
13
3
29
47
36
33
11
4
49.1
53*2
4T.6 41.2 35.2
28.3
25.0
54.7
54.7
39.6
38.S
23.4
33.3
IM
2
21 3% 41
17
4
2
23
39
31
19
1
2«.T
3*2
23.0 30.7 41.7
37.0
33.3
3.8
26.7
42*9
36.5
40.4
6.3
iao no MONF
«
1 ia
12
4
1
13
15
5
7.8
1.2 16*7
24.1
33.3
1.9
15.3
31*9
41.7
AVFRAGE
41
14
30 30 §¦
76
104
23
26
35
51
»6
109
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY 1557-11
SURREY PARTICIPANTS
QUEST ION NO.II1-6 HOW MANY SEPARATE
PRODUCTION LINES DO YOU HAVE SET UP
NORMALLY TO HANDLE YOUR
OPERATlONSt
METALFINI SHING
- - NUMBER Of FULL-TIME
ti
1
S3
---'TOT
A L
SAL
E S -
TOTAL
1-4
5-9
10-19
20-49
50-99
100- 250-
249 499
5006
MORE
UNDER
S100M
*100M
-249M
S250M
—499M
S500M
-999M
S1MIL
-2.4
S2.5
MIL*
TOTAL
*41
64
•5
118
111
46
13
54
89
92
86
49
11
NO ANSWER
19
6
3
5
4
4
3
3
1
NUMBER ANSWERING
<~*2
100.0
98
100.0
62
100.0
113
100.0
107
100.0
46
100.0
13
100.0
50
100.0
86
100.0
89
100.0
-- tfy
100.0
"4*
100.0
13
100.0
NONE
24
5.4
10
17.2
8
9.8
4
3.5
1
.9
8
16.0
6
7.0
5
5.6
1 TO 3
26*
59.7
45
77.6
55
67.1
75
66.4
49
45.8
15
32.6
7
53.8
37
74.0
61
70.9
52
58.4
46
54.1
14
28.6
t
61.5
~ TO 6
102
23.1
2
3.4
14
17.1
28
24.8
36
33.6
16
34.8
4
30.8
J
10.0
14
16.3
25
28.1
22
25.9
19
38.8
1
7.7
7 OR MORE
52
11.•
1
1.7
5
6.1
6
5.3
21
19.6
15
32.6
2
15.4
5
5.8
7
7.9
1»
20.0
16
32.7
4
30.8
AVERAGE
3.12
1.53
2.56
2.77
4.10
4.89
3.77
1.58
2.63
3.07
3.78
5.12
4.23
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY <557-1J
SURVEY PARTICIPANTS
QUESTION NO*111-9 REQUEST FOR DATA ON
ARE* PlATIBt Fl*ISH|g_pft REMOVED
- NUMBERFULL-TlfcE PEOPLE ---TOTALSALES
100- 290- 500* UNDER.SI00M S250M J500M S1MIL <2.5
TOTAL 1-4 5-9 10-19 20-+9 >0-99 249 499 MORE »100M -249H -499M -»99M -2.4 MIL*
TOTAL 461 64 85 118 111 46 13 54 89 92 86 49 13
NO ANSWER
NUMBER ANSWERING 461 64 85 118 111 46 13 54 89 92 66 49 13
100.0 100.0_100 f 0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
YEi» SOME DATA ARE ENTERED OR 125 13 16 33 36 11 6 6 26 29 26 14 8
SUPPLIED £7.1 20" 3 18.8 28.0 32.4 23.9 46.2 11.1 29«2 31»5 30.2 28.6 61.5
NO. NO DATA PROVIDED 336 51 69 85 75 35 7 48 63 63 60 35 5
72.9 79.7 81.2 72,0 67.6 76.1 53.8 88.9 TO.8 68»5 69.8 71.4 38.5
-------
metal finishing stuoy 1557-1>
SURVEY PARTICIPANTS
NO ANSWER
IS
»?
15
27
9
4
l
10
14
13
4
3
1
NUMBER ANSWERING
!•»
51
TO
91
102
42
12
44
75
79
70
46
12
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.o
100.0
100.0
100.0
MOMF
1
1
1
.5
2.0
2.3
,„s Tli4„ . mrm
42
n
19
10
s
1
35
29
21
9
2
1
10. •
•2.4
54.3
20.9
9.4
7.1
• •5
79.5
34.7
26*6
11*5
4*3
• «3
5.000 TO 19.9*9
94
4
24
17
25
4
2
. 4
31
23
IB
5
3
24.4
11.•
57.1
29.7
22.5
ft.i
14.7
15.2
41.1
24.1
23.1
10.9
25.0
QUESTION NO.111-10 WHAT IS YOUR PLANT'S
MATER USE FPU A TYPICAL DAY DUR1N6 1975
FOR TOTAL PLANTT
TOTAL
NUMBER Or FULL-TIME -PEOPLE - -- - --.-TOTAL SALES-""
100- 290- 100* UNOER S100M I250M S500H S1MIL Sj.5
1-4 5-9 10-19 20-49 #0-99 249
J* PS 1JJ JLU ±* 11
499
MORE tlOOM -249M -499M -999M -2i4MIL*
54 >9 92 H 49 »
75 1 S tl It 5 1
l?tS 2»0 4.1 29.7 JM 11.9 nr
JtOiffiMLJQ WftT*
-109»099 HQ6E-
12.7
41
I 11 11 9 2
1.4 12.1 21.6 2H4 16.7
TK?——F.I—».? l6*i io.6 4A .6
525 14 HQ 445 445 1555 1717
11 21
13
22
24
17.3 27.4 10.1 1.7 14.7
2 10 17 15 1
2.7 12.7 2l.* 12.6 KT
a 10 20 5
l.i 12.ft 41.J 41.7
>0 125 3S* 447 1510 1518
AVERAGE IHUNDREDS)
-------
national analysts
METAL FINISHING STUDY (337-1)
SURVEY PARTICIPANTS <,
QUESTION NO.I11-10 WHAT IS YOUR PLANT'S
FOR MCTALFINISH1NS PROCESSING
WATERY
NUMBER
OF FULL-TIME
PEOPLE
100- 230-
TOTAL SALES-
SOOt UNDEft 3100H 3250M S500M S1MIL
62*3
TOTAL
1-4
3-9
10-19
20-49
30-99
249 499
MORE S100M
-249M
-499M
-999H
-2.4
MIL*
TOTAi
461.
64
. 85.
118
IJLI_
46
13
34
89
92
86
49
13
NO ANSWER
lit
31
30
. 42
35
2
24
29
25
32
11
1
NUMBER ANSWERING
298
JI
35
76
76
33
11
30
60
67
54
38
12
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
NONE
3
2
1
1
1
1*0
6.1
1.3
3.3
1.9
LESS THAN Si000 GAL. PER DAY
103
28
33
22
11
5
1
24
29
20
11
4
2
33.2
84.8
60.0
28.9
14. 5
14.3
9.1
80.0
48.3
29.9
20.4
10*5
16.7
3.000 TO 19**99
6a
2
20
21
16
3
2
3
20
21
9
3
3
22.0
6*1
36.4
27.6
21.1
a.6
18.2
16.7
33.3
31.3
16.7
7.9
25.0
20<000 TO 49*999
37
i
1
20
27
3
1
10
18
18
4
2
19.1
3.0
1.8
26.3
33.5
14.3
9.1
16.7
26.9
33.3
10. 5
16.7
30.000 TO 99»999
32
1
8
15
5
2
1
5
10
11
10.7
1.8
10.5
19.7"
14.3
18.2
1.7
7.5
16.5
26*9
109.000 OR MORE
33
3
6
17
5
3
5
16
5
11.1
6.6
48.6
43.3
4.5
9.3
42.1
41.7
AVERAGE (HUNDREDS1
456
21
74
433
399
1369
1667
32
99
395
369
1338
1348
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY
SURVEY BAKTICteAIOS-
1997-11
QUESTION N0.III-11A WHERE DOES YOUR
TOTAL
-XOtAL-
461
-1"4
*4
- - NUMBER OF FULL-TIME PEOPLE ---TOTAL SALES
100- 2*0- »00t UNDER-S10SM S290M S300N HHIL »2.9
-5-9 10-14 20-49-30-99—249 499 MQBE.J100M--249M .-499H -999N -2.4 MIL*.
•9 US
111
IS
54
•9
91
a*
49
11
NO ANSWER
NUMBER ANSWERING
499 9* M 11S 110 46 IS
_loo.oaoo.
7
Tift
12
14.0
9
19*4
BOTH
12
_2afc_
9
l*l_
1 9
..I ItJ.
3
4.9
1
.lift.
2
2tl
9
?«9
9
>*1
-------
national analysts
METAL FINISHING STUDY 1557-11
—SURVEY-RART4CI RANTS—
QUESTION NO.IIt-llB DO YOU HAVE THE
_IMKtlQM_OE _SMlICHINt_£tOH-*QUB_P®£SENT
MEANS OF MATER DISCHARGE TO ANOTHERT
NUMBER OF FULL-TINE PEOPLE - - - - --.-TOTAL SALES
-100- 250= IQQfr UNDER UPON I230H tSOOM «1HIL 82.S
TOTAL 1-4 9-9 10-19 20-49 $0-99 249 499 MORE S100M -249H -499M -999H -2.4 MIL*
-^*61 *4 #5 lid-_lll 46 IS 54 &S 92 BA 49 t*
-2 -2 1-
61 »K._IU.._.U0 —46 IS 51 sa 90 gft 49
100.0 100.0 100.0 100.0 100.0 100.0
100.0
100.0
100.0
100.0
100.0
100.0
ioo.o
YF*
11 1-13 5 2
1
2
1
6
1
i
2.9 1.6 1.2 2.6 4.5 4.J
7.7
3.9
2*2
7.0
2*0
7.7
NA
439 60 12 113 10$ **
12
49
as
09
SO
49
12
*7.1 9S*4 98.• 97.4 95.5 95.7
92.5
96.1
100.0
97.a
93.0
98.0
92.3
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY 1597-11
—SURVCY-MRtlClBAMIS
QUESTION N0.I1I-UB1 (IF 'YES* t Q.llBI
-¦WMAT-1S-THE—NATUKE-Of YOUR OPTION!
TOTAL 1>
- - - - NUMBER OF FULL-TIKE PEOPLE ---- ---TOTAL SALES
100- 230- >00t UNDER SIOOM S250M SSOON S1MIL *2.»
TOTAL S*9 -i0nJ#- J0^*3—SOsSS—249 499 KOBE tlOOM -Z*9H -+99M -999M -2m* NIL»
NO ANSWER
NUMBER ANSWERING 1) 1 I 1 > I 1 2 2611
IOO«0-100*0.100*0_llKUQ.lBO*«_lPQftQ.lQa»Q 100*0 lOO.O 100.0 100.0 100.0
TO 6R0UN0 VIA FILTER BEOS
TO RIVER* LAKE* STREAM* ETC* S 111 > 1
SI.a S3.3 jt0>0 100*0 ; UUfi IflSjA.
OTHER OPTIONS
• 1 1 2 2 2
UiLMo. SLiog,o^»,t._*a«e _iwi9
2 2 3 1
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY 1557-11
. -SURVEY—PART IC1PAMTS .
OUESTION NO.II1-12 (IF DISCHARGE WATER
-60eS~T999
. tUOOO-TO-SZtUS.
_S3.000TQS5.999.
_S6*000.OR-MORE
AVERAGE.
-2*2.
II.
. 46_
75
7l_
_27_
.1.1
100.0 100.0 100.0 100.0 100.0 100.0 100.0
.102.
.30
-26 27.
. 14.
36.2 76.9 56.5 36.0 19.7
3.7
.33
.10.
12.4 IS.¦ 17.4 13.3 7.0 14.6
.69.
25_
24.5 5.3 15.2 32.0 35.2 14.• 18.2
32
11.3
_44.
15.6
5 9 14 3
10.9 12.0 19.7 11.1
9.1
i5_-
HU 2»J.
6.7 18.3 M.6 72.7
131 1727 _ 3601.11969 16017..
JL
61
63.
iZ
-JL2_
100.0 100.0 100.0 100.0 100.0 100.0
2S
^29_
_LZ_
.12.
75.6 47.5 27.0 23.1
-A!L
10
6.3
1_
18.2 16.4 15.9 11.5
3.1
Ii_
.25
-16_
6.1 23.0 39.7 30.8 12.5
-11_
11.5 12.7 21.2 6.3 12.5
I
.33-
1.6 4.8 13.5 71.9 87.5
345 1118 1738 3558 13236 15050
040
V.
-------
r national, analysts
METAL FINISHING STUDY
SUftVFY PARTICIPANTS
(557-11
OUESTION NO*II1-13 HOW MANY POUNDS OF
SLUDGE DO YOU PRODUCE IN A MONTH*
TOTAL
- - NUMBER
. 5-9 10-19
OF FULL-TIME
20-49 50-99
PEOPLE
100- 290-
249 499
5006
MORE
---TOTAL
UNDER S100M S250M
SlOllM -249M -499H
SAL
S500M
-999M
E S -
S1MIL
-2.4
» a»
S2.5
NIL+
TOTAL
«*1
64
es lit
111
46
13
S4
•9
92
66
49
13
NO ANSWER
179
19
SO 49
41
IS
•
17
30
39
30
21
T
NUMBER ANSWERINC
2S2 49
100.0 100.0
S5 69
10Q.0_LQ0.0
63 31
100.0 100.0
5
100.0
37
100.0
39
100.0
53
100.0
56
100.0
26
100.0
6
100.0
NONE
9i
94.6
21
46.7
21 19
16.2 27.S
21
33.3
9
1
20.0
14
37.S
21
3S.6
IB
34*0
23
41.1
6
26.6
1
16*7
1 TO 99
TO
24.1
17
»T*«
22 17
40.0 24.6
9
14,1
4
12.9
20
94.1
IS
30.9
12
22.6
a
14.3
1
3*6
100 TO 999
*1
21.6
7
IS.6
9 22
16.4 SI.9
13
20.6
S
16.1
1
20.0
3
6.1
17
26.8
16
30.2
•
14.3
4
14.3
4
66.7
1*000 TO 9(999
16
12.S
2 •
3.6 11.6
13
20.6
9
29.0
1
20.0
2
3.4
4
7*9
12
21.4
11
39.3
10*000 ON MORE
17
6.0
1 3
1.6 4.3
7
11.1
4
12.9
2
40*0
1
1*7
3
5.7
9
6*9
4
14*3
1
16.7
AVERAGE
2240
»5
•76 972
S607
4266
4440
27
446
2149
4560
9003
1667
0*1
l.
-------
( national analysts
METAL FINISHING STUDY
Cittt/rv PAMiciPanTS
1997-11
"N
QUESTION NO.111-14 1 IF SLUDGE PRODUCED.
Q.13I HOW IS THE SLUDGE DISPOSED*
TOTAL
1-4
- - NUMBER OF FULL-TIME
5-9 10-19 20-49 §0-99
PEOPLE
100- 290- 9006
249 499 MORE
TOT
UNDER S100M
S100N'—249M
A L
S290M
-499M
SAL
S300M
-999M
E S -
S1MIL
-2.4
S2.9
MIL*
TOTAL
It*
24
34
30
42
22
4
23
33
39
33
20
9
NO ANSWER
number answer ins
114 24
100.0 100.0
34
100|0
30
100.0
42 22
100.0 100.0
4
100.0
23
100.0
33
100.0
39
100.0
33
100.0
20
100.0
9
100.0
LAND FILL
76
41*9
7
29*2
14
41.2
13
30.0
22
92.4
13
99.1
1
29.0
7
30.4
12
31.6
13
37.1
20
60.6
13
65.0
3
60.0
INTO water or sewer
2?
14.7
3
12.5
6
17.6
9
10.0
9
21.4
3
13.6
1
29.0
4
17.4
9
23.7
4
11»4
9
19.2
2
10.0
incinerator
1
• 9
1
2*0
1
2.6
lagoon
•
4.3
1
4.2
1
2.0
1
2.4
9
22.7
1
4.3
1
2*6
1
3.0
3
19*0
1
20*0
TRASH PICKUP
90
46.»
13
34.2
20
93. #
29
93.0
13
31.0
•
36.4
3
79.0
12
92.2
22
97.9
IS
91*4
13
39.4
9
29*0
2
40.0
REFINERY
3
1*6
1
4.2
1
2.9
1
29.0
1
4.3
1
2.6
1
20.0
RECYCLED
&
3.3
2
4.0
1
2.4
1
4.9
3
• •6
1
9*0
OTMER
2
1.1
1
2.9
1
2.4
1
3.0
DON'T KNOW
1
~ 9
1
2.4
1
9*0
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY C957-1I
SURVEY PARTICIPANTS ,
QUESTION NO.IV-1A WHO OWNS YOUR FIRMf
TOTAL
H"M»f OC FUU.-TJ HE-PEOPLE r _ - -
-TOTAL SALES---
100-
TOTAL 1-4 9-9 10-19 20-49 30-99 249
»(
499
SOOt UNDER S100M S290M S300M S1MIL S2.9
MORE S100M.-249M -499M -999N -2*4 MIL*
4*1
»
110 111
11
94
•9
92
U
49
IS
NO ANSWER
.41
11
11
NUMBER ANSWERING
AN INDIVIDUAL
A FAMILY
420 36 79 10T 100 4S 12
100.0 100*0 100.0 100.0 100*0 100*0 100*0
131 29 » 9* 22 • »
>1*2 51.• 32.9 33.6 22*0 IS.6 29*0
141 IS 30 . SI ST IS
SS.t 24.9 3S.0 29*0 37.0 41.9
90 12 ST SO 4T 12
100*0 100.0 100*0 100*0 100*0 100*0
22 27 26 20 9 3
44*0 32*9 29.9 29*0 19*1 29.0
16 .33 27 27 IS 2
32.0 40.2 31.0 33.S 3S*S 16.7
A SMALL GROUP
129 11 21 36 3S 12 9
30.7 19.« 26.6 33.6 3S.0 27.9 41*7
11 19 33 30 13 »
22.0 23*2 *7.9 37.9 27*7 41.7
—F
2.4
—i 1 r
3.S 14*9 16.7
ANOTHER FIRM
16
3.3
1
l.S
1
1.3
3
2.S
2 9 4
2.0 11.6 33.3
OTHER
3
.7
1
1.3
1
1.0
1
2.0
1
1.2
1
1*1
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY 1557-11
—SURVEY PARTICIPANTS *
QUESTION NO.IV-IB HOW MANY OWNERS ARE
JMESCJ
- - - - NUMBER OF FULL-TIME PEOPLE - - - - ---TOTAL SALES---
100- 250- SOOfc UNDER. S100M S250M S500M »1M1L S2.9
IOTAL 1-* 5^9.-10-19—2050-89 2*8 4W naat- tiooH -749M -4Q9M -999M -?.4 MIL*
TOTAL 461 6* 85 lit 111 46 15 54 *9 92 06 49 15
NO ANSWER 46 44 14 10 94 146592
NUMBER ANSWERING 415 60 *1 104 101 57 9 53 55 $6 91 40 11
loo.o 100.Q_1M.Q_19Q..fi_JJ».0 1QQ.0 VOO.9 100.0 100.0 100*0 100.0 100.0 100.0
1-3 337 54 71 «5 ~7$ 24 5 4« 74 72 61 26 6
81.2 9Q.Q.JLL. 7 51.7 77.2 64.9 55.6 90.6 67.1 »3«7 7>«3 65.0 54.5
4-7 65 5 9 15 20 10 3 4 10 13 16 10 3
ia»i • tj__11a.14.4e ji.j 7.5 11.> i».i 19.a 25.0 27.3
a OR MORE 15 1143 .3 1 111442
3.-1 1.7 1.2 3.1 3.0 B.l_U.l U9 U2 U2 4.9 10.0 IB.?
AVERAGE 2.46 1.93 2.21 2*37 2.77 3.14 3.22 1*94 2.21 2.30 2.S4 3.25 4*00
044
V
-------
NATIONAL ANALYSTS
METAL FINISHING STUOY 1557-11
SURVEY PARTICIPANTS—
QUESTION NO.IV-1C HOW MANY OF THESE
-¦OWNERS-WORK- -FULL"sT IME »
NUMBER OF FULL-TIME PEOPLE - - ---TOTAL SALES
100- 250- 5006 UNDER-»100M S250M S500M S1MIL *2.5
TOTAL
IOJAL-
4*1
-l*». 24* -US-
44 *5 lit 111 46 13
MORE S100M.
54
*24VM
•9
-4V9M
•2
•IfW
86
49
Mil*
13
NO ANSWER
51
7 • 12 • a 5
2
B
5
3
9
3
NUMBER ANSWERING
410
1Q0.0
57 77 106 103 37 9
1QQ.0 1Q0.0 10Q..0 100.^ 100.0 100.0
52
lOO.O
• 1
100.0
•7
100.0
63
100.0
40
100.0
10
100.0
NONE
22 • 4 5 * 1
5-4 lfc.A 5.2 4.7 1.9 J.7
4
7.7
8
9.9
1
1.1
2
2.4
2
5.0
1-3
367
¦9.1
47 72 97 95 30 5-
¦ 2.1 «.S 91. S 92.2 Bl.l 42.§
41
92.3
70
•6.4
•4
96.6
76
91.6
31
77.5
•
•0.0
4-7
1
m f
2 14 4 5 2
3.S 1.3 3.C 3*9 13.9 25.0
3
3.7
2
2.3
5
6.0
6
15*0
1
10.0
• OR MORE
2
• 5
1 1
2.7 12.5
1
_ 2.5
1
10.0
AVERAGE
1.66
1.19 1.49 1.97 1.63 2*30 3.25
1.27
1.37
1.67
1.86
2.28
3.10
-------
national analysts
METAL FINISHING STUDY
SURVEY PARTICIPANTS
1557-11
QUESTION NO*IV-tO HOW MANY Of THESE
OWNERS MONK PART-TIMEt
- - NUMBER OF FULL-TIME PEOPLE ---TOTAL SALES-
100- 250- 500* UNOER 4100N S250M 4500N S1MIL Si.5
5-9 10-lS_Z0=*9 ja-98 m *«» MORE «100M -349M -499M -999M -2.fc MIL*
TOTAL
JOIAL-
4*1
64
•5
lit 111
46
11
54
89
92
•6
49
IS
NO ANSWER
101
12
14
25
2*
II
14
16
16
16
NUM6ER ANSWER INS
)M 52 49 91 «5 95 I
-loo«o_ioo&q-ioo.o-ioa.aaflo.a_iaa.a_iaa.a_
47 75 76 70 35 10
loo.o ion.n ton.o lao.o loo.a ioo.o
NONE
270 40 50 70 62 24 •
75.0 76 • 9 _J2. 5 75.3 72 .9 72.7 100.0
>6 53 57 52 25 »
76.6 70.7 75.0 74.3 75.4 90.0
1-3
•4 12 19 23 22 5
27.5 24.7 25.9 24.2
11 22 19 17 7 1
23.4 29.3 25.0 24.3 21»2 10.0
4-7
¦ OR MOKE
2
.6,
1
JL*2_
1
JjflL
1
1.4
1
JiL
AVERAGE
.34
>29
.95
•91
• 34
•44
• 30
• 41
• 24
• 39
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY 1557-11
tUftVC*-PAftX4C!PAMTS—
1
QUESTION NO.IV-2 FROM 1*72 TO 1979» HOW
LD--YOU-DCSCRJBE—IMS-CHANGES—IN--YOUR ..
ANNUAL SALES*
TOTAL SALES-
-TOTAL
TOTAL
461-
- - NUMBER Of FULL-TIME PEOPLE - -
100=—240s—
1-4 5-9 10-19 20-49 90-99 249 499 NONE S100H -249M -499N -999H -2*4
64
2
•5
Ait lit
6
-46-
-19-
_5A_
_ML
_S2_
Ji.
NU+
AS IX.
NUMBER ANSWERING
445
62 89 112 107
4$
19
54
97
91
85
49
19
100.0
100.0 100.0 100.0 00.0
100.0
100.0
100.0
100.0
100.0
100.0
100*0
100.0
SALES HERE INCREASING STEADILY
152
21 29 40 94
16
4
17
26
98
28
17
a
>4.2
99.9 90.1 99.7 91.•
40.0
90.B
91.5
29.9
41.a
92.9
94*7
61.9
SALES HERE DECREASING STEADILY IB
• • 7 11
1
2
9
6
4
10
9
1
a.s
12.9 9.6 6.9' 10.9
2.2
15.4
16.7
6.9
4.4
11.8
6*1
7.7
SALES MOVED IN CYCLES
14 28 41 47
21
6
12
99
90
>6
29
4
36.9
22.6 99.7 >6.6 49.9
46.7
46.2
22.2
¦"*0.2
>>•0
42*4
46*9
90.8
SALES HERE ABOUT THE SAME
B4
16 IS 24 19
9
1
19
ia
19
11
6
"11.?
25.1 21.7 21.4 14.0 11.1
7.7
24.1
20.7
20.9
12.9
12.2
NOT IN BUSINESS ALL 0* PART
T
9 4
9
2
Of THIS TIME PERIOD
1.*
4.9 4.i
9.6
2*3
-------
NATIONAL ANALYSTS
METAL FINISHING STUOY ($57-11
CllBUEV »ABTiri«AMTS >
QUESTION NO.IV-3 WHAT IS YOUR 1975 YEAR-END
VALUE FROM YOUR PROFIT AND LOSS STATEMENT
FROM SALEST
- NUMBER
OF FULL-TIME
PEOPLE - -
100- 250-
---TOTAL SAL
5006 UNDER S1Q0M S250M S500M
E S -
61MIL
>2.5
TOTAL 1-4 3-9 *0-19
20-49
90-99
249 499
MORE S100M —249M -499H -999M
-2.4
MIL*
TOTAL
4*1 64 89 111
111
46
13
54 69 92 86
49
13
MA ANSWER
7* 19 16 is
4
1
NUMBER ANSWER IN6
3(3 49 67 100
97
42
12
54 89 92 86
49
13
100.0 100.0 100.0 loo.o
100.0
100.0
100.0
100.0 100.0 100.0 100.0
100.0
100.0
UNDER SlOOfOOO
94 >4 15 1
54
14.1 79.6 22.4 1.0
100.0
*100*000 TO >249.999
>9 10 41 32
1
1
89
23.2 22.2 *1.2 32.0
i.fl~
2.4
100.0
>2)0.000 TO S499>999
92 9 53
_ 21.
92
24.0 13.4 53.0
29.•
100.0
1)00.000 TO >999.999
•6 1 2 12
99
.1
86
22.9 2.2 3.0 12.0
60.6
19.0
100.0
>1.000.000 TO >2.499*999
49 1
12
29
9
49
12.• 1.0
12.4
69.0
41.7
100.0
>2.900.000 OR MORE
13 1
4
7
13
3.4 1.0
9.9
96.3
100.0
AVERAGE 1THOUSANDS!
676 >9 170 441
691
1636
3776
64 174 346 692
1461
5932
04«
k
-------
national analysts
METAL FINISHING STUDY 1557-11
SUBl/FY PART1C I PANTS '
QUESTION NO.IV-3 WHAT IS YOUR 1975 YEAR-END
_VALU£_fBQH_*QUa PRQf IT JkNO LOS£_STATEMENT
FROM RENT OR LEASE PAYMENT St
TOTAL
TOTAL
UL
1-4
_*4
- - NUMBER OF FULL-TIME PEOPLE ---TOTAL SALES
20-49 50-99 2** 499 MORE S100M -249M -499M -99VM -2.4 MIL*
„«J 46 la 84 M 22 tt ftl U_
JM-AUSNEB.
J.91-
.21.
_20_
JWH&EB _AN5SE&litfL
LESS THAW »LtOOO-
juawLJ®. ***«**.
S5.000 TO S9.999
>10.000 TO >35.999
_l J08_HQBS.
JS4 42 $0 94 91 H 12
100.0 100«0 100.0 100.0 100*0 100.0 100.0
* 9 22 17 • 2
T9.i u.® ij.4~o.4-ri;7~ir.x u.t
70
-Al-
ia
AVERAGE ITHOUSANDS>
_ _ 1* 1? *_
16.1 42.9 26.1 12.• 6.6
71 15 20 22 12
i
2.6
lie
13.I-
>•
3 IS 34 45 12 4
r.ru.6 Ji.i 44.5 JT.s jrrr
10.7
U_
4.3 12.1
17
12,
20
44.9 50.0
3> 43
46 80 «> »4 44 12
100.0 100.0 100.0 100.0 100.0 100.0
9 11 22 16 11 1
19.1 1J.I 25.9 19.0 25.0 SVT
24
20
52.2 25.0
9 27
1.2
25
"T9T6—)).l 29.4
4 22 2*
5
6.0
•
"nr
46 14 4
8.7 27.5 32.4 54.6 31.S—JKT
19
3.5 10.7 43.2
9 20 l>
7
5S.3
6B
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY 1997-11
SUBWAY PABTtftPAMTS .
QUESTION NO.IV-3 WHAT tS YOUR 1975 YEAR-END
J£ALUE_OffltL tfllA_PBOE II_ANCU^>SS-5TM£M€N T_
FROM OWNER'S/OFFICER'S COMPENSATI ONI
-JQTAL
TOTAL
461
1-*
'4.
NUMBER OF FULL-TIME PEOPLE TOTAL SALES
100- 290- 500t UNDER 9100M 9290M 9900M 91H1L >2.5
9-9 10-19 20-49 90-99 2*9
85 119 111 *6 II
499 MORE 9100M -249M -499M -999M -2*4 MIL*
94 99 92 >6 49 19
10_ANSHER_
AIT.
29.
Zt 25
20.
U_
JJL
- JtUMBER ANSWERING..
-Lt55_.IHAfiL»20AQO0
- «0iOfffl_TO_*19A»??_
990.000 TO 979.999
_990.000 Oft MORE
.9.44.
3|. 99 9J 9l„
JO
100.0 100.0 100.0 100.0 100.0 100.0 100.0
S£ 22
19
.22
29.0 97.9 92.9 23.7
_ 9
"9.9
9.1 90.0
"!_ 10 21 6.
32.9 56.3 46.6 31.? ~29,T~16.2
1
ro.sr
_ >j
16.9
s
7.9
44_ 2
l2.i S.s
9 17 20 9
9.6 19.3 22.0 " 2*.l
_ 9__ 10 16 10
9.6 IS.9 lT.4 2775
1
43
12. »
i
2.6
2
1.4
9 19 9 3
1.9"28.9 2f.l i&ttT
AVERAGE I THOUSANOS> 49 24 29 J8
99
71
77
43
79
99
91
49
100.0 100.0 100.0 100.0 100.0 100.0
30 29 14 * 6 3
"6979 3574 16.5
11 34 32
1571 33*3
29 6
25.6 43.0 37.6 35.8 13*3
1 1* 14 20 9
T73 T7T7 1*75 2vT7 I77J 1TTT
1 2 19 10 12 1
T7i 2.5 21.2 12.1 26.7 11.1
I 7 19 13 4
16
T7J 1.2 22.2 28.9 44.4
29 43 99 71 109
090
V.
-------
NATIONAL analysts
METAL FINISHING STUOY 1597-11
PURVEY PARTICIPANTS *
QUEST ION NO.IV-3 WHAT IS YOUR 1973 YEAR-ENO
VALUf FROM YOUR PROFIT AND LOSS STATEMENT
FROM DEPRECIATION*
- NUMBER OF FULL-TIME
PEOPLE - -
100- 290-
9006 UNDER*
TOT
S100M
A L
»250M
SAL
S500M
£5-
S1MIL
m •
S2.9
TOTAL
1-4 9—9 10-19 20-49
90-99
249 499
MORE S100M
-249M
-499M
-999M
-2.4
MIL*
TOTAL
461
64 as lit 111
46
19
94
•9
92
•6
49
13
MO ANSWER
140
33 32 34 20
11
3
14
21
12
a
9
9
NUMBER ANSWERING
321
11 S3 64 91
99
10
40
66
ao
78
44
10
100.0 100.0 100.0 100.0 100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
LESS THAN SltOOO
IS
» 4 2 1
1
7
2
2
1
1
4.0
16.1 7.9 2*4 1.1
10*0
17.5
2.9
J.J
1.3
10.0
Sl.000 TO *9*999
121
22 39 96 16
2
29
46
34
13
1
3fc.i
71.6 Tji.i 42.9 1*7.6
S.7
72.9
47.6
42.5
16.7
2.3
•10*000 TO S29»999
107
3 9 99 91
J
2
16
39
43
6
».}
9.7 17.0 39.3 96.0
14.3
9.0
23*9
4s.a
55.1
13.6
SSOtOOO TO S99i999
99
• 19
11
9
1
t
2
17
17
1
12.1
ft.9 16.4
31.4
90.0
2.9
1*9
2.5
2l»l
"ir.T
10.0
S60.000 TO S99.999
21
1114
12
2
1
1
1
2
19
9
6.9
3.2 1.9 1.2 4.4
94.9
*6.6
2.9
1.9
1.1
2*6
29.9
JO.O
S100.000 OR MORE
IS
4 4
9
4
2
2
2
7
9
}«i
4.t 4.4
14*9
40.0
2.9
2.5
2.*
15*9
»0.0
AVERAGE 1THOUSANDS1
92
7 7 29 29
72
206
6
19
17
29
76
22a
091
A
-------
( NATIONAL ANALYSTS
KTAL FINISHING STUOY <357-11
&UHtfFY PUTiriMKIS .
QUESTION NO.IV-3 WHAT IS YOUR 1975 YEAR-END
VALUE FROM YOUR PROFIT AND LOSS STATEMENT
FROM PROFIT BEFORE TAXT
- - NUMBER
OF FULL-TIME
PEOPLE - -
100- 230-
-- TOTAL SALES-
4006 UNDER S100M S250M S500M S1MIL
S2.5
TOTAL
1-4
3-9
10-19
20-49
50-99
249 499
MORE S100N
-249M
-499M
-999M
-2.4
MIL*
total
6V_
JS
ua
111
46
13
34
•9
92
66
49
13
NO ANSWER
. -Ill-
_?T
. 2?.
U
. .!?_
•
2
10
15
9
3
3
2
NUMBER ANSWERING
343
37
56
91
92
39
11
44
74
83
as
46
11
100.0
100.0 100.0
100.0
100.0
100.0
100.0
100,0
100.0
100.4
100*0
100.0
100*0
LESS TMAN *10.000
200
27
40
55
45
19
6
35
53
46
39
23
2
il.l
73*0
71.4
60.4
48.9
50.0
34.3
79.3
71.6
53.4
47*0
50*0
18*2
S10>000 TO >24.999
36
4
10
20
14
6
6
12
18
13
5
16.3
10. •
11.9
22.0
13.2
ls.t
13.6
16*2
21.7
18*1
10.9
S25.000 TO S74.999
62
6
3
_ 1*
i*
7
1
3
8
17
24
9
1
la.i
16.2
• .9
14.)
27.2
It.4
9.1
6.a
10.8
20.5
28*9
19.6
9.1
STStOOO TO >149*999
13
1
1
3
4
1
1
4
7
3*1
1.6
1.1
3*4
10.3
1.4
1*2
4*8
ii.i
SI50.000 OR MORE
12
2
3
2
4
1
1
2
8
3.3
2.2
3.3
3.3
36.4
1.2
1.2
4.3
72*7
AVERAGE CTHOUSANDS1
30
9
a
23
2a
57
170
6
9
17
25
40
376
092
-------
NATIONAL analysts
metal finishing study
PURVEY PARTICIPANTS
1537-11
QUESTION NO.IV-J WHAT IS YOUR 1973 YEAR-END
VALUE fllOH YOUR PftOFIT AND LOSS S?ATEMENT
FROM PROFIT AFTER TAXt
TOTAL
TOTAL
4(1
NUMBER OF FULL"TIME PEOPLE TOTAL SALES
100- 2S0- JOQ* UNOEM 1A09M 3238M 3309M 11M1U 12»J.
1-4 3-9 10-19 20-49 30-99 249 499 MORE I100M -249M -499M -999M -2.4 MIL»
64
S3
110 111
4fc
13
>4
?2
H
li
HO AN4MER
HUMBIR ANSWCA1N4
LESS THAN 919i9W
>10tD00 10 »2«>m
*23.000 TO 171.999
ST3>000 TO »149«»99
*130.000 QR MOPf
AyERAfiC I IH0MS4NMJ.
122
2*
23
29
23
10
14
339 >9 60 90 >6 IB 9
100.0 100.0 100.0 100.0 100.0 100.0 100.0
l»2 »l SO 66 49 ?3 6_
66.4 ll.t 13.3 71.3 37.0 *0.3 66.t
33 3 , 1 13 4 1
.« li.l L1.7 17.1 17.4 Io.» il.l
13
41 2 3 6 20 ¦
12.7 J.) S.O 4.7 23.3 21.1
3
1.3
6
i.i
_ U
2
2.2
1?
2 11
2.3 2.1 11.1
2 _ 1
3.3 ii.l
43 79 79 7# 47
lod.o ioo.6 ioo.o i5o.5 i5B*5 100.0
37 46 55 41 26 2
¥2;r" li.S 70.5 55.1 55.J U.2
7 10 13 18 4 1
lS.i "Ti;T~l6.7~TJ.l 1.1 Ll.I
1 3 10 13 14
—2.2 I.I 12.1 IT.Z—zrn
J'
Jl
3I_
I.J
l
t. r
it
t.4 a.r
s
u.ir
24 171
oil
V_
-------
f NATIONAL ANALYSTS
METAL FIN1SH1N6 STUDY
SURVEY Pi»Tiri»lNTS
4597-11
QUESTION N0.2V-) WHAT IS YOUR 1975 YEAR-END
VAMJE FROM vatm PROFIT AND LOSS STATEMENT
FROM LOSS BEFORE TAXt
m **
- - NUMBER
OF FULL-TIME
PEOPLE - -
100- 250-
-- ---TOTAL
5006 UNDER S100M S250M
SAL
S500N
E S -
S1HIL
62.S
TOTAL
1-4
5-9 10-19
20-49
50-99
249 499
MORE S100M
-249M
-499M
-999H
-2.4
M1L+
TOTAL
461
64
as us
111
46
13
54
•9
92
66
49
13
MO AN&MER
165
29
19 42
>0
IS
4
13
25
21
13
13
4
NtJMMF* ANSWERING
296
15
50 76
• 1
26
9
41
64
71
73
36
9
100.0
100.0
100.0 100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
LESS THAN 110*000
275
35
50 73
71
22
7
41
63
69
62
30
6
92.9
100.0
100.0 96.1
•7.T"
79.6
77.6
100.0
9H.4
97.2
84.9
63.3
•8.9
S10»000 TO S24i999
7
2
2
2
1
1
1
3
1
1
2*4
2.6
2.9
7.1
11.1
1.6
1.4
4.1
2aS
11.1
S2S.OOO TO S74.999
10
7
5
1
•
i
5.4
• •6
10.7
1.4
ll.A
2.S
•75.000 TO S149.999
2
1
1
2
• 7
l.i
5.6
5.6
S150.000 OR MORE
2
1
1
2
• 7
1.2
11.1
5.6
AVERA6E 1THOUSANDS1
4
1
2
6
11
35
1
5
22
2
094
-------
f
NATIONAL ANALYSTS
METAL FINISHING STUDY
SIHV(« PARTICIPANTS
1997-11
OUESTION NO.IV-3 WHAT IS YOUR 1*75 YEAR-ENO
uii iir fuh vma profit ana loss STATEMENT
FROM LOSS AFTER TAX*
m mm
• - NUMBER OF FULL-TIKE
PEOPLE - -
100- 230-
---TOTAL
SOOl UNDER S100M $2508
SAL
SSOOM
E S -
S1MIL
S2.9
TOTAL 1-4
5-9 10—19 20-49 SO—99
249 499
MORE >100M -249M -499M
-999M
-2*4
NIL*
TOTAL
4*1 64
69 118 111 4*
IS
94 $9 92
•6
49
13
NO ANSWER
1ST >0
34 41 SO 19
4
IS 2S 20
14
13
4
NUMBER ANSWERING
294 >4
49 77 SI 27
9
39 (4 72
72
36
9
100.0 166.6
100.0 100.0 100.0 100.0
100.0
100.0 100.0 ioo.O
loO.o
100*0
100.0
LESS THAN S10*000
277 >*
49 7* 71 22
s
39 44 71
42
30
9
94.2 100.0
100.0 9S.7 (7.7 S1.9
M.9
100.0 100.0 94.4
•6.1
•3*3
100*0
tlQtOOQ TO S24t999
7
* »
5
2
2*4
4.9 11.1
4.9
9*4
*2S*0O0 TO S14»999
*
S 1
1
S
2*0
4
(«! 9.7
1 1 1
1
"" ~
4
1.4
1.9 1.2 l.T
11*1
11*1
S1S0*000 OR MORE
AVERAGE 1THOUSANDS1
1 1
2 S •
17
.1
9
IS
1
OSS
J
-------
national analysts
METAL FINISHING STUDY 1597-11
,_£UftyE*_£Aan£l£AiUS^
QUESTION N0.1V-4 WHAT IS THE 1975 YEAR
JM.I iilEMlf OUND1M Jf OMR
BALANCE SHEETT
•CUNRET ASSETS
" rNUMBER OF FULL-TIME PEOPLE TOTAL SALES
100- 250- 5006 UNDER S100M *250M 6500M *1H1L *2.5
TOTAL 1-4 5-9 10-19 20-49 90-99 249 *99 MORE SlOOM -249M -499M -999M -2.4 MIL*
TOTAL 4*1 64 » 11* HI 46 13 »4 &? 92 86 *9 1)
NO ANSWER 141 33 36 33 II 10 * 17 22 12 6 8 4
NUMBER ANSWERING 320"" 31 49" 85 ~ 93 36 9 ' 37 6? 80 ~J$ 41 ff~
100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
LESS fHAN *20(000 34 ~ l» • 4 "" ~ 17 T2 2 T
10.6 St.l 16.3 4.7 4>.9 17.9 2.5 1.3
*20(000' TO >99*999 " 136 12 " 39 52 26 ¦ - - -
42.5 31.7 79.6 61.2 21.0 51.4 73.1 58.8 22.5
1100>000 TO $199(999 75" 1 2 22 39 8 1 6 27 3l «~
23.4 3.2 4.1 25.9 41.9 22.2 2.7 9.0 33*8 46.3 9.8
(203(000 TOSA99.999 55 ' " 6 tS 19 3 " 4 H IT
17.2 7.1 26.9 52.8 33.3 3(0 28.8 65(9
8500(000 OR MORE 20 13 9 6 1 109
6.3 1.2 3.2 25*0 66(7 1.3 24.4 100.0
AVERAGE (THOUSANDS) 210 26 43 16» 177 441 1740 30 ~56 9^ 161 4*4 2360
056
V
-------
NATIONAL ANALYSTS
METAL FINISHlNfi STUOY
SH»V£Y PfTICIPAMTS,
1557-11
QUEST ION NO.IV-* WHAT IS THE 1975 YEAR
FOUBP 1H .TQUB
BALANCE SHEETt
•FIXED AND OTHER ASSETS
TOTAL
--"TOTAL SALES---
TOTAL
NUMBER. OE_EUU=I »ME PEOPLE
100- ISO- SOOt UNDER S100M S290M >500* S1MIL *2.5
1-4 5-9 10-19 20-49 50-99 249 499 MORE (100M -249M -499H -999M -2.4 MIL+
4*1
M
•5 11*
111
46
IS
54
•9
92
86
49
13
NO ANSWER
147
»
IS
>4
19
11
II
23
13
NUMBER ANSWERING
314 29 49 S4 92 35 9
100.0 100.0 100.0 100.0 100.0 100.0 100.0
36" 66 79 T7 45 5"
100.0 100.0 100.0" 100.0 100.0 100.0
LESS THAN >20*000
90
19.9
il
44.6
20
40.9
7
1.1
6
6.5
14"
4t.3
—20—rr
55.6 25.B
T
9.9
4
5.2
15 IS hi IV
41.T 57.6 53.2 29.9
•20.000 TO >99*999
>100*000 TO S199.999
~*200t000^TO <499*999
119
37.9
23
46.9
46
57.1
25
27.2
2
5.7
—»r
22.3
r
6.9
5 n
10.2 21.4
r
11.1
1 9 22 29 E~
2.6 13.6 27.9 37.7 14.6
55
3S.0
7"
20.0
"IT
IS.9
—r
2.0
10 Ji-
ll.9 22.•
—ir
37.1
—r
33.3
5 IS 5
5.4 >7.1 95*6
—r
3.0
7 is 2* r
a.9 20.a 56.5 11.1
—r
1*3
—s n r
6.5 26.S 66.9
S500«000 OR MORE
25
B.O
1
1.2
AVERAGE ITHOUSANDS!
176
33
41
9S 176 542 76*
23
ST
951684951039
-------
r
national analysts
METAL FINISHING STUDY 1557-1)
UJfttfFY PARTICIPANTS .
1
QUESTION NO.IV-4 WHAT is THE 1975 YEAR
FIA VALUE FOR •IITEMI FOUND IN YOUR
BALANCE SHEET*
•CURRENT LIABILITIES
NUMBER OF FULL-TIME PEOPLE - -
---TOT
A L
SAL
E S -
TOTAL
1-4 5-9 10-19 20-49 50-99
100- 250-
249 499
5006
MORE
UNOER
S100M
>10QM
-249M
>250M
-499M
S500M
-999M
S1MIL
-2.4
S2.S
NIL*
TOTAL
461
64 85 US 111 . 46
13
54
89
92
86
49
13
NO ANSWER
142
52 55 31 20 12
4
16
21
12
8
9
4
NUMBER ANSWERING
>19
100.0
32 50 ar 91 34
100.0 100.0 100.0 100.0 100*0
9
100.0
38
100.0
68
100.0
80
100.0
78
100*0
40
100.0
9
100.0
LESS THAN 120>000
lot
>5*2
23 30 36 11
71.9 60*0 41.4 12.1
30
.78.9
41
60.3
26
32.5
7
9*0
>20>000 TO *99.999
110
40*8
• 20 43 44 7
25«0 40*0 49.4 48*4 20.6
1
11.1
18.4
26
38.2
48
60*0
39
50.0
7
17*5
>100.000 TO S199.999
40
12*5
1 4 24 8
3.1 4.6 26*4 23*5
I
11.1
1
2.6
1
1*5
6
7*5
14
24.4
IS
32*5
>200>000 TO >499*999
31
9.T
2 if is
2.3 13.2 38.2
3
33.3
12
15.4
16
40*0
2
22.2
>500,000 OR MORE
12
3*8
2 6
2.3 17.6
4
44*4
1
1*3
4
10*0
7
77.8
AVERAGE CTHOUSANDS!
115
15 21 85 102 351
612
13
22
40
117
295
1142
058
-------
( NATIONAL ANALYSTS
METAL FINISHING STUDY >1597-11
ciibukv PARTICIPANTS
\
QUESTION NO.IV-* WHAT IS THE 1979 YEAR
BALANCE SHEETT
•LONG TERM DEBT
- - NUMBER OF FULL-TIME PEOPLE
w m
TOT
A L
SAL
E S -
a* m
TOTAL
1-4
5-9 10-19 20-49 50-99
100- 290- 500&
249 499 MORE
UNDER
S100H
S100M
-24 9M
S250M
-499M
S500M
-999M
S1M1L
-2.4
S2*5
MIL*
TOTAL
*61
64
•5 US 111 4*
13
54
•9
92
•6
49
13
NO ANSWER
is*
30
34 SI 20 10
4
14
20
12
ft
s
4
NUMBER ANSWERING
325
100.0
14
100.0
51 ST 91 36
100.0 100.0 100.0 100.0
»
100.0
40
100.0
- it
100.0
*0
100.0
74
100.0
41
100*0
9
100.0
LESS THAN >20(000
ITT
94.5
24
70.*
32 52 43 15
62.7 59.• 47.3 41*7
2
22.2
29
72.5
42
60.9
45
56.3
38
4S.7
16
39.0
2
22.2
S20*000 TO S99*999
94
2S.9
lo
29*4
19 29 32 4
37.3 21*7 35.2 11.1
11
27.5
20
29*0
36
37*5
2&
33*3
5
12*2
SlOOiOOO TO »199>999
si
9.5
10 10 4
11.9 11.0 11.1
3
33*3
i
S.7
5
6*3
9
11*5
" 7
17*1
3
33.3
•200*000 TO *499*999
14
4.3
4 A
4.4 22.2
2
22.2
1
1.4
4
5.1
7
17*1
2
22.2
S900*000 OR MORE
9
2*8
2 9
2.2 13.9
2
22*2
1
1*3
6
14*6
2
22*2
AVERAGE (THOUSANDS)
70
IS
19 33 61 222
493
. lr
~JF
>1
56
213
490
OS*
-------
f ~
NATIONAL ANALYSTS
METAL FINISHING STUOY
SURVFY PUTtCIPMTS
1517-11
OUESTION MO.IV-* WHAT IS THE 1975 YEAR
END VALUE F« XITEMI FOUND IN YOUR
BALANCE SHEET»
•COMPANY NET WORTH
NUMBER OF FULL-TIME PEOPLE
--'-TOT
A L
SAL
E S -
w •»
TOTAL
1-4
5-9
10-19
20-49
50-99
100- 250- 5006
249 499 MORE
UNDER
>100M
S100M
-24 9M
S250M
-499M
>500M
-999M
ilMIL
-2.4
>2.5
MIL*
TOTAL
*61
64
as
US
111
46
13
54
69
92
66
49
13
NO ANSWER
ISO
31
H
31
24
14
5
19
19
13
13
U
4
NUMBER ANSWERING
311
100.0
>3
100.0
47
100.0
• 7
100.0
67
100.0
32
100.0
a
100*0
35
100.0
70
100.0
79
100*0
73
100*0
36
100*0
9
100.0
LESS THAN >20*000
*7
13.1
19
49.5
9
19.1
10
11*9
»
9.7
6
16.•
15
42.9
14
20.0
•
10.1
6
a.2
3
7.9
>20•000 TO >99*999
116
37. 3
16
48.5
2a
59.6
3S
43.7
20
23.0
3
9.4
1
12*5
16
51*«
41
56.6
31
39*2
17
23*3
4
10*5
I100>000 TO $199*999
64
20.6
2
6*1
a
17.0
24
27.6
23
26.4
S
19.6
1
2*9
19
IB.6
25
31.6
20
27*4
5
13*2
>200t000 TO *499*999
58
16*6
2
4.3
14
16.1
29
33.3
9
26.1
2
25.0
1
2*9
2
2.9
... 15„
19*0
26
35*6
12
31*6
1
11.1
>500*000 OR MORE
26
6.4
1
1*1
10
11.9
9
26*1
S
62*3
4
5*5
14
36.6
6
86.9
AVERAGE ITHOUSANOSI
212
40
61
~T4T
244
366
16«S
39
61
130
197
414
2148
060
-------
r
NATIONAL ANALYSTS
metal FINISHING STUOY
SURVEY PARTICIPANTS
1557-11
\
QUESTION NO.IV-4 WHAT
END VALUE FOR •CITENI
IS THE 1975 YEAR
FOUND IN YOUR
BALANCE SHEETt
•LOSS
- - NUMBER
OF FULL-TIME
'
I!
1 3
1
i
TOTAL
SAL
E S -
TOTAL 1-4
5-9 10-19
20-49 50-99
100- 250-
249 499
5006
MORE
UNOER
S100M
S100M S230H
-249M -499M
S500M
-999M
S1MIL
-2.4
S2.5
MIL*
TOTAL
461 *4
•5 111
111 46
15
54
•9 92
96
49
15
NO ANSWER
5 1
1
1 2
1
2
1
1
NUMBER ANSWER I NO *»6 63 •» 111 llO" 44 II 51 IT 51 55 51 IT
100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
LESS THAN >20*000 450 61 M U5 107 « IS 93 IS 90 SI 57 IT
M.7 100.0 100.0 96.5 *7.9 97.7 100.0 100.0 96.9 97.0 97.6 97.9 100.0
S20.000 TO S99 *999
4
.9
12 1
.9 i.a 2.5
2
2.2
1
1.2
1
2.1
*100>000 TO (199.999
—r
1.1
T
1*2
1
.4
S200.000 TO S499.9V9
S500*000 OR MORE
AVEDA6C ITHOUSANDS) 1
2 2 2
115 2
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY
AWTS
1557-1»
QUESTION NO.IV-5 WHAT IS THE BOOK VALUE
-Of YPUft BUlLOINOt
JOUL
- NUMBER OF FULL-TIME PEOPLE
100- 250-
1-4 5-9 10-19 JO—49 50-99 *49 *91
TOTAL SALE5---
5004 UNDER 5100H S2S0M S500M flMlL S2.5
MORE UPON -249H -499H -999H -2.4 MIL*
TOTAL
461
64
85
118 111
46
13
5*
69
92
86
49
13
NO ANSWER
128 54 65 54 68 33
42 63 53 5? 29
NUMBER ANSWERING
LESS THAN »100>000
HOO.OOO TO S499»999
85O0.000 OR MORE
133 10 20 34 43 13 5
100.0 100.0 100.0 100.0 100.0 100.0 100.0
91 9 17 28 28 3 2
68.4 90.0 85•0 82.4 65.1 23.1 40.0
39 1 3 6 15 7 3
29.3 10.0 15.0 17.6 34.9 53.8 60.0
3
2.3
3
IS.l
12 26 39 29 20 4
100.0 100.0 100.0 100.0 100.0 100.0
11 22 33 17 3 2
91.7 84.6 84.6 58.6 15.0 50.0
1 4 6 12 14 2
8.3 15.4 19.4 41.4 70.0 50.0
3
15.0
AVERAGE (THOUSANDS! 96 34 44 S8 92 301 173
43 48 51 93 289 101
062
V
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY
SUHYEA PABTlCIPAHIS
1557-11
QUESTION NO.IV-5 WHAT IS THE BOOK VALUE
OF Jfpye PRODUCTION EQU1PMENTT
TOTAL
JOIAL
NUMBER OF FULL-71mI PEOPLE - - - - - - - T o T A L £ A L E S
100- 250- 500t UNDER .S100M S250M S500H S1MIL S2.5
1-4 S-» JO-1i 20-49 50-99 149 499 MORE S100H -249H -499M -999M -2.4 MIL*
441
64
•> 11B
111
4*
13
54
•9
92
84
49
11
NO ANSWER
194
57
47 49
12
15
26
34
27
20
NUMBER ANSWERING
LESS THAN S30.000
630.000 TO S49•999
267 27 3* 70 79 31 •
100.0 100.0 100.0 100.0 100,0 100.0 100.0
7« 16 23 25 9
29.2 59.3 60.5 35.7 11.4
2
6.5
39 7 5 11
14.6 25.9 13.2 15.7
14
17.7
1
3.2
2* 55 65 66 40 6
100.0 100.0 100.0 100.0 100.0 100.0
It 26 23 8
64.3 47.3 35.4 12.1
1
2.5
6 11 12 10
21.4 20.0 18.5 15.2
650*000 TO >99•999
*100.000 OR MORE
51 3 9 16 14
_U.T 22,9 17.7
99
JIaL.
AVERAGE (THOUSANDSI
134
1
Asl.
28
2 1
_6i5_.li»5_
1 18 42
2.6 25.7 53.2
26 7
•3.9 87.5
35
72
145 394
4*1
3 13 17 15 2
10.7 23.6 26»2 22.7 5*0
1
3.6
5 13 33 37 8
9.1 20.0 50.0 92.5 100.0
28
42
59 132 392 509
063
V
-------
f NATIONAL ANALYSTS
METAL FINISHING STUDY
SURVEY PARTICIPANTS
<557-1»
a
QUESTION NO.IV-4 WHAT
LIFE OF YOU* BUILDING!
IS the remaining
- - NUMBER OF FULL-TINE
TOTAL 1-4 5-9 10-19 20-49 50-99
PEOPLE - -
100- 250- 5006
249 499 MORE
TO
UHOER S100K
S100M -249M
T A L
S250H
—«99M
SAL
iSOOM
-999H
E S -
61M1L
-2.4
12.4
NIL*
TOTAL
4*1 64 •» ll» 111
46
13
5<>
• 9
92
86
49
1J
NO ANSWER
>51 54 61 IS >2
36
7
45
64
60
ii
36
7
NUMBER ANSWERING
10* 10 IT 30 29
100.0 100.0 100.0 100,0 100.0
10
100.0
6
100.0
9
100.0
25
100.0
32
1G0.0
21
100.0
13
100.0
6
100,0
10 YEARS OR LESS
43 4 10 11 11
39.» 40.0 58.• 36.T 37.9
3
30.0
2
33.3
4
44.4
u
44.0
16
30*0
a
38.1
2
IS a 4
2
33.3
11 TO 19 YEARS
27 4 * 7 a
25.0 40.0 23.5 23.3 27.fr
1
10.0
2
33.3
2
22.2
7
28.0
7
21.9
5
23.8
2
15.4
2
33.3
20 TO 39 YEARS
34 2 1 11 9
31.5 20.0 IT.6 36.7 31.0
4
40.0
2
31.3
3
33*3
7
2*.0
7
21*9
a
36.1
8
61.»
1
16*7
40 YEARS OR MORE
4 1 1
3.7 3.3 3.4
2
20*0
2
6*3
1
1.1
1
16.1
AVERAGE
15.29 14.00 11.6S 16.77 14.90
20.90
12.67
14.67
11.76
14.72
14.52
20.92
ii.a>
OM
-------
r
NATIONAL ANALYSTS
METAL FINISHING STUDY
iUfiWFV PABTIflPAMTS
1997-1)
QUESTION N0.1V-9 WHAT IS THE REMAINING
LIFE OF YOUR PRODUCTION EQUIPMENT?
m tm
TOTAL 1-*
- - NUMBER OF FULL-TIME
9-9 10-19 20-49 90-99
PEOPLE
100-
249
290-
9006
MORE
UNDER
SlOOrf
tot
9100M
-249M
A L
S290M
—499M
SAL
9900M
-999M
E S -
S1M1L
-2.4
92.9
MIL*
TOTAL
*61
64
>9 11* 111
46
19
94
99
92
96
49
19
NO ANSWER
242
41
99 96 91
21
6
31
36
99
37
17
6
number ANSWERING
219
100.0
2$
100.0
90 62 60
100.0 100.0 100.0
29
100.0
7
100.0
29
100.0
91
100.0
94
100.0
1
49
100.0
32
100.0
7
100.0
S YEARS OR LESS
129
96*2
12
92.2
21 19 96
TO.O 96.9 60.0
11
44.0
9
42.9
11
47.9
31
60.a
31
97.4
34
69.4
12
37.9
9
42.9
6 TO * YEARS
tl
21.9
9
21. T
4 10 14
13.9 16.1 23.9
9
36.0
2
29.6
9
21.7
7
13.7
19
27.9
7
14.3
12
37.9
2
29.6
10 TO 1* YEARS
49
20.9
9
21. T
9 16 10
16.7 29.9 16.T
4
16.0
2
29.6
7
90.4
12
29.9
7
13.0
9
16.3
7
21.9
2
29.6
20 YEARS OR MORE
>
1.4
1
4.9
1
1.6
1
4.0
1
2.0
1
1.9
1
3.1
AVERAGE
6.SI
6.69
9.67 6.2T 6.19
7.40
9.96
6.61
6.47
9.79
9.96
7.99
6.14
069
j
-------
national analysts
METAL FINISHING STUDY <957-11
suaVET PARTICIPANTS
QUESTION NO.IV-5 WHAT IS THE EXPECTED
BUILDING!
- - NUMBER
OF FULL-TIME
PEOPLE - -
100- 290-
soot
TOTAL
UNDER S100M 9250M
SAL
S500M
E S -
tiXIL
*2.5
TOTAL
1-4
5-9
10-19
20-49
50-99
249 499
MORE
S100M
-249M
-499M
-999M
-2.4
MIL*
TOTAL
441
__ *4
«>_
lie in
44
19
54
89
92
84
49
13
NO ANSWER
))*
54
41.
• 7
73
94
7
42
99
42
40
29
10
127
10
22
91
98
12
4
12
90
90
24
20
9
100.0
100.0
100.0
100.0
100*0
100.0
100*0
100.0 100.0
100*0
100*0 100*0
lo6*o
LESS'THAN >19*000
78
10
17
-20
l«
*
2
11
19
22
15
4
2
*1.4
100*0
77.J
*4.9
90*0
90*0
99*9
91*7
49*9
73*9
57*7
30*0
46.7
S19.000 TO S99>999.
2*.
2
1L
10
2
1
1
8
4
4
4
22.8
9.1
39.5
26.3
14*7
14.7
a.9
24*7
20*0
23*1
90*0
8100*000 TO 8499*999
19
9
9
9
9
9
2
5
a
1
19.0
19*6
29*7
29*0
50*0
10*0
~"S*7
17*2"
40*0
39*3
>900*000 OR MORE
1
1
•a
• •9
(AVERAGE ITHOUSAND?f
M
>•
1*
97
7a
105
5
24
19
44
72
49
OM
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY 1957-11
SMRVFV PART ir f PINTS
\
question no.iv-s what is the expected
INVESTMENT OVER THE NEXT FIVE YEARS FOR
PRODUCTION EQUIPMENT!
- - NUMBER
OF FULL-TIME
PEOPLE
100- 290-
---TOTAL SALES-
900* UNDER S100M (290H S900M *1MIL
*2.9
TOTAL
l-»
5-9 10-19
20-49
90-99
249 499
MORE S100M -249M -499M
-999M
-2(4
NIL*
TOTAL
4*1
6*
*9 11*
111
4*
13
94 *9 92
**
49
M
NO MMER
161
S*
6* 94
*2
3*
•
10
NUMBER ANSWER1M6
100
•
17 2*
29
10
9
9 22 2*
1*
IS
3
100.0
100.0
100.0 100.0
100.0
100.0
100.0
100.0 100.0 100.0
100.0
100*0
100.0
LESS THAN SlOtOOO
a*
•
1* 23
29
7
3
* 20 24
19
13
2
M.O
100*0
*2.4 99.*
**•2
70.0
60.0
**.9 90.9 *9(7
*3.3
a*(7
66.T
*10(000 TO S29t999
5
1
1
1
1
1 2
1
1
»(0
)•*
10.0
20.0
11.1 7.1
6.7
13.3
*30(000 TO *99(999
7
2 1
3
1
2 2
2
1
7.0
11.* 4.2
10.3
20.0
9.1 7*1
11.1
*•7
*100(000 TO **99*999
I
1
1
1(0
10.0
5(4
*900(000 OR MORE
1
1
1(0
10.0
AVERACE (THOUSANDS!
12
9 3
7
*7
19
2*6
14
9
•
0*7
-------
r
NATIONAL ANALYSTS
METAL FINISHING STUD* 1557-11
SURVEY PARTICIPANTS „
QUESTION NO.V-l WHICH OF THESE
WASTEWATER
TOTAL
- - - - NUMBER|OF FULL-TIME
1-4 5-9 10-19120-69 50-99.
PEOPLE ---- ---TOTAL
100- 250- 5006 UNDER »100M S250M
249 499 MORE S100M -249M -499M
SAL
SOON
999H
E S -
SIHIL
-2.4
82.5
MIL*
TOTAL
461
66
•5
lit
111
46
13
54
89
92
86
49
13
NO ANSWER
NUMBER ANSWERING
461
100.0
66
100.0
•5
100*0
lit
100.0
111
.00.0
46 13
100.0 100.0
54
100.0
89
100.0
92
100.0
86
00.0
49
100.0
13
100.0
A- PH ADJUSTMENT
146 8
12.3
17
20.0
34
50
45*0
23
50.0
7
53.8
3
5.6
23
25.8
27
29.3i
35
40.7
28
57.1
7
53*8
B- FLOW EQUALIZATION
52
1 If 3_
2
I.L
7
III
7
23
20.7
7
15. 2
2
15.4
2
3.7
6
6.7
10
10.9
IS
20.9
9
18*4
2
15*4
C- CHROMIUM REDUCTION
. 84'
It. 2
6
6.3
11
12.9
ia
15.3
>1
27.9
13
28.3
4
30.8
2
3.7
10
11.2
13
14.1
22
25.6
20
40*8
2
15*4
0- CYANIDE DESTRUCTION
T»
17.1
4
|6.3
10
11.a
16
13.6
29
26.1
12
26.1
3
23.1
4
7.4
11
12.4
12
13*0
20
23*3
18
36*7
2
15*4
E- PRECIPITATOR-CLARIFICATION
7T
16.T
T
1
1.6
9
10.6
17
14.4
28
25.2
15
32.6
4
30*8
1
1.9
6
6.7
18
19*6
17
19.8
20
40.8
1
7.7
F-LAGOON
90
6.5
2
3.1
3
3.5
3
2.5
9
8.1
*
19.6
2
15*4
2
3.7
2
2.2
3
3.3
8
9.3
12
24.5
2
15.4
G- SEPARATE CYANIDE STREAM
56
7.a
5
5.9
9
7.6
12
10.8
6
13.0
3
23.1
7
7.9
6
6.5
9
10.5
9
18*4
2
15*4
H- separate HEXAVALENT-CHROME
STREAM
60
• .7
1
1.6
6
T.l
9
7.6
15
13.5
6
13.0
2
19*4
6
6.7
6
6*5
11
12.6
8
16.3
1- COUNTERCURRENT RINSE
79
17.1
2
3.1
9
JO, 6,
17:
14.4
29
26.1
13
21.)
5
38.5
3
5.6
10
11.2
15
16.3
21
14.4
20
40.8
2
15.4
J- REVERSE OSMOSIS* EVAPO-
RATION* ION EXCHANGE! ETC.
29
4i)
1
1.6
1
. U2_
4
M.
I 13
JW?
8
17.4
2
15»4
2
2.2
2
2.2
9
10.5
12
24*5
1
7.7
NOME
2 SO
kO*7_
51
71.7.
61
?l.e
77
65*3 _
52
46.8
21
45.7
3
23.1
47
87.0
59
66.3
59
64*1
46
13*5
15
30*6
6
46.2
A ONLY
17
5.7
2
3.1
2
2.4
5
4.2
6
5.4
1
2.2
7
7.9
3
3.3
3
3.5
1
7.7
At B* AND C ONLY
1
.2
1
1*6
-------
(CONTINUED PAGE 21
MATlnwtl. ANALYSTS
METAL FINUHING STUDY
SURVEY PARTICIPANTS
1557-11
QUESTION N0.V-1 WHICH OF THESE WASTEWATER
TREATMENT FEATURES MAKE UP YOUR SYSTEM*
- - NUMBER OF FULL-TIME PEOPLE
---TOTAL
if
>
r
E S -
m m
TOTAL
1-4
5-9
10-19
20-*9 50-99
100- 250- 5004
249 499 MORE
UNDER S100M C25QM
S100M -249M -499M
S500M
-999M
S1M1L
-2.4
>2.5
MIL*
At Bt C> 0 AND E ONLY
5
1*1
5
*.5
5
5.5
1
2.0
At Bt C* 0* E» «• AND H ONLY
1
.2
1
1*2
1 ONLY
4
.9
1
l.fc
1
1.2
1
.1
1
•9
1 1
1.9 1*1
J ONLY
4
.9
2 2
1.5 A.I
2
2.5
1
2.0
ALL OTHER COMBINATIONS
145
»1.5
•
12.5
It
21.2
>5
29.7
45 22
40.5 47.•
10
14*9
5 22 29
9.5 24.7 51.5
52
37.2
52
65.S
*
46*2
06*
-------
national analysts
METAL FINISHING STUDY 1997-11
survey Participants
QUESTION NO.V-2A HOW MUCH DID
HATER SYSTFN COST TO PURCHASE
YOUR WASTE-
AND INSTALLT
TOTAt
1-4
NUMBER OF FULL-TIME PEOPLE
100- 290- 9006
5-9 10-19 20-49 #0-99. 249. 499 MORE
TO
UNOER S100M
»100H_->*9M
T A L
1250M
-499M
SAL
S500M
-999*
£ S -
S1M1L
-2.4
*2.9
mil*
TOTAL
64
•5
11*
111
46
13
94
*9
92
• 6
49
13
NO ANSWER
JO*
S3
64
•4
99
24
6
49
67
63
51
18
7
NUMBER ANSWERING
15>
100.0
11 21
100.0 100,0
34
LOOjO
92
i?P»o
22
1O0.0
7
100.0
9
100.0
22
100.0
29
100.0
35
100.0
31
100.0
6
100.0
LESS THAN *10*000
44
UtL
6
54. 5
11
52*4
19
44,1
9
2
9.1
3
60.0
14
63.6
10
34.5
4
22.9
2
6*5
*10*000 TO *24.999
38
24.•
4
36.4
4
19.0
11
32*4
13
_ 29.0
3
13.6
1
14.3
2
40.0
3
13.6
9
31*0
12
34.3
5
16*1
1
16*7
*29*000 TO *74*999
36
21. 5
1
9.1
5
23.1
7
20.. 6
10
19.2
6
27.3
9
7t.4
9
22.7
9
31.0
4
11.4
9
29*0
3
50.0
$75,000 TO *149*99*
19
12.4
1
4.8
12
23.1
6
27.3
1
3*4
6
17.1
9
29*8
I
16.7
*110*000 OR MORE
16
10.S
1
2.9
•
19.4
9
22.7-
1
14*9
5
14.3
7
22*6
1
16.7
AVERAGE 1 THOUSANDS!
SO
10
21
21
71
96
49
•
19
23
50
109
57
069
-------
NATIONAL ANALYSTS
METAL FINISHINS STUOY <557-11
SURVEY PARTICIPANTS -
QUESTION NO.V—2B IN WHAT YEAR DID YOU
HAKE. THE LAST HAJQR-ABBJT1QN TO THE—
SYSTEM!
- - NUMBER
OF FULL-TIME PEOPLE ---- -TOTAL SALES-
100- 290- 9006 UNDER S100M S250M S900M S1NIL
*2.5
TOTAL
1-4
5-9
10-19
20-49
30-99
249 4*9 MORE S100M
-249M
-499M
-999M
-2.4
NIL*-
TOTAL
4*1
64
69
116
. Ui
46
13 54
•9
92
86
49
13
NO ANSWER
2*7
»
U
•3
99
21
9 49
69
61
48
16
6
NUMBER ANSWERING
164
11
22
39
96
29
• 9
24
31
38
33
7
100.0
100.0
100.0
100.0
100.0
100.0
100.0 100.0
100.0
100*0
100.0
100.0
l6o,6
1MI OR EARLIER
•
2
3.
2
3
1
2
2
3
3.3
9.1
5.7
3.6
12.0
4.2
6.5
5.3
9.1
IMS
- 2
1
. .1-
1
1
1*2
9*1
2.9
20.0
3*2
1*70
7
2
1
1
1
2
2
1
1
1
2
4.1
f.r
i;r
T.T
4*0
29.0
• ¦3
3.2
2.6
J.O
21.6
1*71
A
1
i
2
2
1
1
2.4
"1.1
4.5
3.6
#.J
3.2
2.6
1»72
*
1
2
2
2
2
1
1
2
1
2
9.9
9.1
*.1
9.7
• .0
20.0
4.2
6*3
2.6
6.1
1*73
*
1
3
2
1
2
1
2
2
2
>•>
4.9
6.6
3.6
4.0
29.0
4.2
6.5
3.3
6.1
1*74
2*
3
1
2
13
2
1
4
5
a
3
1
19.*
27.3
13.6
3*7
23.2
6.0
12.9
16.7
16.1
21*1
9.1
14.3
1*79
' 1*
A
4
9
•
14
4
2 3
4
5
*
a
2
23*2
3*. 4
16.2
'23. 7
23.0
16.0
25.0 60.0
16.7
16.1
23.7
24.2
28.6
1*7*
*0
1
7
15
20
12
1
9
12
. 14
14
2
M.i
*•1
31.a
42.9
39.7
43.0
12.9
37.5
36.7
36.6
42.4
26.6
-------
( NATIONAL ANALYSTS
METAL FINISHING STUDY (557-1t
sunvtr participants *
>
QUESTION N0.V-20 HOW MUCH DOES
EACH YEAR TO OPERATE!
IT COST
- - - - NUMBER OF FULL-TIME PEOPLE
100-
TOTAL 1-4 5-9 10-19 20-49 50-99 2*9
250- 5006
499 MORE
TOT
UNDER S100M
S100M -249M
A L
S250M
-499M
SAL
S500M
-999M
E S -
S1MIL
-2.4
•a m
*2.5
MIL*-
TOTAL
*61 64 65 lit 111 46
13
54
>9
92
86
49
13
NO ANSWER
336 57 TO 91 69 27
5
50
72
67
59
25
6
NUMBER ANSWERINC
US T 15 27 42 19
100.0 100.0 100.0 100.0 100.0 1O0.0
e
100.0
4
100.0
17
100.0
25
100.0
27
100.0
24
100*0
7
100.0
LESS THAN *5.000
17 J • 1) 10 1
2«100*000 OR MORE
5 4
4.0 21*1
I
12.»
4
16*7
1
14.3
AVERAGE
21 6 5 7 23 51
41
a
6
6
21
45
41
0T1
-------
national analysts
METAL FINISHING sroor (557-11
-
QUESTION NO.V-IF OtD YOU CONTRACT FOR
AND INSTALLATION OF THE
YOU 00 IT ALL YOURSELFT
SY&TEN OR OID
- - NUMBER OP PULL-TIME PEOPL
P - «-
- - - T 0 I
A L
SAL
£ £ -
TOTAL
1-4
5-9 10-19 10-49
SO—99
100-
249
250-
%99
9006
MORE
UNDER
S100M
tlOOM S290M
-24»H -499N
S900M
-999M
S1MIL
-2.4
*2.9
NIL*
TOTAL
44
•9 lit ill
46
19
54
• 9
92
•6
49
19
HO AHSMCft
Si
42 «4 S3
21
4
49
64
61
48
16
6
NUMBER ANSWERING
lH
100.0
12
100. 0
29 94 96
100.0 100.0 100.0
29
100.0
9
100.0
9
100.0
29
100.0
31
100.0
38
100.0
33
100.0
1
100.0
CONTRACTED FOR SOME
1»
74.4
•
44.7
IS 26 49
69.2 76.9 74.1
20
•0.0
••.9
9
60.0
17
6S.0
26
B9.9
26
69.4
2«
14.S
9
71.4.
010 all myself
49
Uit
4
99.9.
» e 15
94. • 29.9 29.9
s
20*0
1
11.1
2
40.0
«
92*0
5
16.1
12
91.6
S
15.2
2
20.6
-------
NATIONAL ANALYSTS
METAL FINISHING STUD* tMT-U
suaver PARTICIPANTS ^
QUESTION NO.V-2S OIO YOU REDUCE YOUR
- -
NUMBER
OF FULL-TIME
PEOPLE
- -
TO
r a l
SAL
E 5 -
- -
100- 250-
5006
UNDER
S100M
S2 50M
1500M
81MIL
*2.5
TOTAL
1~4
5-9 10-19
20-49
90-99
249 499
MORE
S100M
-249M
-499M
-999M
-2.4
MIL*
TOTAL
64
•5 US
111
46
IS
S4
89
92
86
49
13
NO ANSWER
291
SI
60 IS
53
21
6
47
63
60
48
16
7
NUMBER ANSWERING
1T0
If
25 35
sa
25
7
7
26
32
38
33
6
100.0
100.0
100,0 100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100,0
YES
11»
•
15 27
40
17
4
5
It
£3
28
23
4
67*6
61.9
60.0 71*1
69.0
68.0
97.1
71.4
69*2
71.9
73.7
69.7
66,7
NO
39
]
7 7
12
4
3
1
S
S
7
6
2
22.9
23*1
J8.0 20.0
20.7
16.0
42.9
14*3
19*2
25.0
18.4
18.2
33*3
DON'T KNOW
16
2
3 1
6
4
1
3
1
3
4
9.4
15*4
12.0 2.9
10.3
16*0
14.3
11*5
3.1
7«9
12*1
Oil
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY (557-11
SURVEY PAR TJ CI PANTS »
QUESTION NO.VI-1 WHAT IS THE ESTIMATED
AMOUNT row TMg DESIGN. PURCHASE AND
INSTALLATION OF A NEW WASTEWATER SYSTEMt
TjQTJdL
TOTAL
*61
NUMBER OF FULL-TIME PEOPLE TOTAL SALES---
100- 280— SOPS UNDER S100M S250M »500H >1M1L »2.9
MO ANSWER
JUI_
1-4
_9*_
_42_
5-9 10-19 20-49 50—99 2*9
_» ua ui IL
499 MORE S100M -249M -499M -999M -2*4 MIL+
»» «9 92 66 49 19
J7_
_1Q_
_5A_
20
JL
_S1_
_£fl IS_
-22.
_191
2L
ZSl.
Ai-
47
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100*0
100.0
100*0
100*0
LESS TMAN SlQiOOO
*9
9
10
iL.
14
4
9
6
19
17
14
4
9
»9.9
IS.7
19.S
19.2
19.*
99.9
14*9
14*1
11*1
lltiOOt TO S99.999
)4
2
9
9
17
9
1
9
2
10
10
6
1
17.6 11.•
lo77
10.4
l9.i
nw
U.J
ll.l
3.4
23.1
21*9
22*2
12*3
•100*000 OR MORE
>4
1
¦
19
ii
2
9
5
9
19
9
U.7
5.9
16.T
22.*
42.9
' if. 4
1.9
11.9
19.1
46*1
97 *9
AVERAGE 1THOUSANDS)
61
1*
11
97
79
196
104
19
26
96
54
156
199
oT»
-------
national analysts
METAL. FINISHING STUOY 1997-11
smtvrv PARTICIPANTS v
OUESTION NO.V1-2 WHAT ARE ALL THE SOURCES
PURCHASE OF A WASTEWATER SYSTEMV
JUI1L_
NUMBER of FULL-TIME PEOPLE -TOTAL SALES
100- 290- 9006 UNPg* »1P0H >Z?0M >?Q0M »1*1L »Z.>
TOTAL 1-4 9-9 10-19 20-49 90-99 249 499
*61 64 |S_ _1JB JLUL 46 13
MORE S100M -249M -499M -999M -2*4 MIL*
94 69 92 66 »9 13
_MQ_AM4«A_
J»7_
19
26
IP
15
10
26
20
n
10
JiUHBER_Mi&UERLr«L
PROFITS FROM THE BUS1HE
PERSONAL FUNDS
WILL CLOSE BUSINESS
OTHER
J 44
100.0
49
100.0
66
jL0tiL£Bffll-CU$ieMEB5Z51ffi£LieB4-
19.2 19>6
JL
59 _ M
100.0 iod.o
_^J>4_. 90.
17.656.8
17 _ 17
26.a 19.i
•6
36
12
100.0 100.0 100.0
41 20 9
10.9 ~i5.6 79.0
19 4 2
22*1 11.1 XbiT
9.9 4.4 1.7 2.9
SMALL BUSINESS ADMINISTRATION
LOAN
COMMERCIAL BANK LOAN
_n«
94. 9~
_2ll
'64.•
9
6 26 26_
177a "54.1 29i9
7.0
91
14
_22
u.r
36 60_
61.0 6172
44.5 36.9 lSTT"
62 26 6
1171 12.2 66.r
1
1.7
I
i.i"
19
TT
29
T.T
10_
T.7—r.4~
9 9
$¦5 i.T"
4 4
4.7 11.1
1
~T7T
49
100.0
19
63
100.0
34
72 69 39 12
100.0 100.0 100.0 100.0
43
48
21
42.2 5470 5977 6975 5371 79.0
11 17 12 14 9 1
24.4 27.0 rs77 2075 12.6 6.4
13 16 1
2*2
13
4.e
23
1.4
26
6.7 2.6
31 16
28.9 36.5 5571 447S 417? I7F
it 40 91 49 26 11
-5T7T
l
63.S 76.i 71.0 66.7 41.7
T72"
2
T7r
4
"TJT"
9 2
T71—JT7T
MO SOURCES OPEN
"177 i
PROFITS S PERSONAL
FUNDS ONLY
I ROE II5 BJPfiAL jFU« 0Sj_
AND COMM. BANK LOAN ONLY
PROFITS ANO COMMERCIAL
2.9 4.4
JL
.A
2.3
3.F"
9
J.S
TSTT"
__L 4 6 11_
7.3 2.2 6.6 6.8 12.8
BANK LOAN ONLY
ALL OTHERS
17.7
229
64.6
6
Ti.i
26
62.2"
6 17 JL
6 _ 17
10.2 "19.3"
41 58
69.9 6J.9
9.6
8.9
9
19.¦ 22.2 41.7
92
26
60.3 72.2 33.3
1.6
7
1
15.6 11.1 *73 T7* 57T
2 3 1 3
4.4
I
"47T
6
T75 «T7T
6 6
"272 979 a7T 877 777"
2 9 19 13 6
4.4 14.3 207b TbTS 15.4 98.3
33 36 44 46 26 9
73.} 6575 STTT 5577 TT7? vTTT
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY (397-11
SURVEY PARTICIPANTS
QUESTION NO.VI-3 WHAT ARE THE AVAILABLE
SPACES FOB THE INSTALLATION OF A SYSTEM
IF IT MERE PURCHASED?
- - - - NUMBER OF FULL-TIME PEOPLE - - - - -.--TOTAL SALES
100- 2SO— SOOt UNDER S100M S250M 1500M HHIL S2.5
TOTAL 1-4 S-» 10-19 20-49 50-99 249 499 MORE S100M -249M -499M -999M -2.4 MIL*
JQIA1 Ml *4 »5_.J1« Ml 46 11 »4 »9 92 86 49 13
¦HQ ANSWEK It.
_JWM9ER_AHSiERJNfi 442 60 61 1J«? 19? *>* 12 >1 *6 M >4 4» 12
100.0 100.0 100.0 100.0 100.0 100.0 10U.0100.0 100.0 100.0 100.0 100.0 100.0
on PRESENTLY AVAILABLE FLOOR 102 JJ .15 23 30 14 3 13 17 19 22 15 6
SPACE 23.1 1B.3 IB.5 20.3 27.5 30^425.0 2575 1575HTS 2573JI71 50.6
_DH_$PAC£_PRESENILY_USEQ-EQB 12 _? 17 1? 27 7 2 15 14 14 20 6 2
PLATING/FINISHING OPERATIONS 11.6 15.0 21.0 16.1 24.• IT7216.7 I97k1575 T575 UTS ISTT 16.»
ON SPECIALLY CONSTRUCTED FA- 37 2 7 • 13 4 2 2 4 7 12 7 2
~CILlTYINTMe PLSiit 874 !"• i" ~67J 7 .I-ITi* I.~7 16.7 3T9 577 1.0 14.3—14*6 16.7
OUTSIDE THE PLANT ON MY 127_ 12 1? __32_ 33 IS 6 12 27 21 2> 19 6
PROPERTY " 2«.7 20.0 23.5 2B.6 32.1 39.1- 5o7o 2»T5 3171 fJT? ST71 J976 50.0
_ OUTSIOE THE PLANT ON UNO I 26 3 4 9 4 4 1 2 3 9 3 4 1
WOULD. HAVE TO BUY 5.9 5.0 4.9 «7o 377 S77 173 379 375 T672 176 b7387T
NO PLACE YO PUT IT li !f \4 %\ 14 4 2 B 15 22 10 4 1
l*.l 21*7 17.3 lB.t 12.B B.7 16.7 15.7 17.4 25.0 11.9 B«3 8.J
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY
SUBYEJL-gART ICIPAWTS
1957-11
QUESTION NO.V1-4 IF YOU LACKED SPACE TO
ACQ TQi OB TQ, lMSIAU^A_MA5tEWAT6B.SYSIENt..
WHAT IS THE LIKELIHOOO THAT YOU MIGHT
TAKE OUT A PRODUCTION LINE TO FREE UP
FLOOR SPACE*
TOTAL
NO ANSWER
NUMBER ANSWERING
1-VERY UNLIKELY
2-UNLIKELY
3-MATBE
~-LIKELY
5-VERY LIKELY
NUMBER OF FULL-TIME PEOPLE TOTAL SALES
100- 250- 5006 UNDER S100M 5250M SSOOM S1H1L *2.5
TOTAL 1-4 5-9 10-19 20-49 80-99 249 *99 MORE tlOOH -249M -499H -999M -2.4 M1L+
4*1
64
•5 118
111
46
IS
222
S4
41
54
51
23
239 30 44 64 60 23 7
100.0 100.0 100*0 100.0 100.0 100.0 100.0
127 14 29 34 29 11 2
S3.1_4«»!__%fj,9. 53,1 48.3 47.» 2«i6_
32 6
13.4 20*0
2 7 9 4 3
4.5 10.9 1540 17.4 42.9
30 9
12.6 16.7
2
*.5
6 11
9.4 la.i
3 2
13.0 28.6
24
10.0
2 7
6.7 19.9
9
14.1
5
8.3
1
4.3
26 3
10.9 10.0
4
9.1
8
12.5
6
10.0
4
17*4
54
89
92
86
49
13
21
46
33
38
24
33 43 59 48 25 8
100.0 100.0 100.0 100.0 100.0 100.0
19
57.6
25
38.1
28 23 10 5
47.5 47.9 40.0 62.5
3
9.1
4 9 6 6 2
9.3 15*3 12.5 24.0 25.0
4
12.1
4
9.3
8 7 4 1
13.6 14.6 16.0 12.5
4
12.1
7 6
16.3 10*2
4
8.3
2
8*0
3
9.1
3 8
7.0 13.6
8
16.7
3
12*0
MEAN
2.12 2.13 1.9* 2.22 2.17 2.26 2.00
2.06 2.05 2.27 2.33 2.2* 1«50
077
V
-------
NATIONAL ANALYSTS
METAL FINISHING STUOY
suavrv pipThtpamts
1557-11
QUESTION NO.VI-4 IF YOU LACKED SPACE TO
tBB TO. OR TO Ih&TAtL A WASTEWATER SYSTEM.
WHAT IS THE LIKEL1H000 THAT YOU MIGHT
PAY TO ALTER The facility, for example*
BY KNOCK 1MB OUT,MAI > S QB BUILPIMS_A—BALCQNYl.
_I0IAL_
- NUMBER OF FULL-TIME PEOPLE ---TOTAL SALES
100- 250- SOOfc UNDER S100M S250M S500M S1MIL S2.J
-9 10-19 20-49 50—99 249 499 MORE 5100M -249M -499M -999H -2.4 MIL*
total
461
*4
as
lit in
4«
13
54
•9
92
06
49
13
NO ANSWER 217 »4 59 55 50 21 4 22 4« 33 40 21 5
number answering
244
30
44 63
41
25
7
32
43
>9
46
28
8
100.0
100.0
100.0 100.0
lOO.O
100.0
100.0
100*0
100.0
100.0
100.0
100.0
100.0
l-VERY UNLIKELY
92
15
1* 28
16
•
2
16
16
26
14
4
2
37.7
90.0
41.3 44.4
26.2
32.0
21.6
50.0
37.2
44.1
30.4
21.4
25.0
2-UNLIKELY
14
3
1 3
B
2
3
a
1
1
4.4
10.0
2.2 4.6
13.1
4.3
7.0
13*6
2.2
3*6
3-MAY8E
57
3
12 14
19
5
2
>
•
10
1«
7
2
23.4
10.0
26.1 22.2
3l.il.
20.0
21*6
25.0
18.4
16*9
34*8
25«0
25.0
~-LIKELY
34
3
7 9
•
3
2
4
«
7
7
3
2
13.9
10*0
15*2 14«3
13.1
12*0
21*6
12*5
18.6
11*9
15*2
10.7
25*0
5-VERY LIKELY
45
4
7 9
10
9
1
2
«
8
«
11
2
18.4
20.0
15.2 14.3
16.4
34.0
14.3
6.3
18.4
13*6
17.4
39*3
25.0
MEAN
2*49
2.40
2.61 2.49
2.CO
3.20
3.00
2.19
2.74
2.37
2.87
3.43
3*25
07*
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY
SURVEY Pi»T1CIPAMT&
1557-11
QUESTION NO.VI-4 IF YOU LACKED SPACE TO
WHAT |S THE LIKELIHOOD THAT YOU MIGHT
FAY TO RELOCATE TO A DIGGER FACILITY
WITH NUDE Ft now XPWF1
- NUMBER OF FULL-TINE PEOPLE TOTAL SALES -
100- 250- 5006 UNOER tlOOM J2J0M S500M S1MIL *2.5
TOTAL
461
64
85
118
Ill
46
13
54
89
92
86
49
13
NO ANSWER
231
17
41
58
55
23
6
21
48
36
40
25
5
NUMBER ANSWERING
228 27
100.0 100.0
44 60 56
100.0 100.0 100.0
23
100.0
7
100.0
31
100.0
41
100.0
56
100*0
46
100.0
24
100.0
8
100.0
1-VERY UNLIKELY
142
Ui)
16 2S
_Mf9 61.6
38
63.3
38
67.9
14
60.9
4
57.1
20
64.5
25
61.0
35
62.5
31
67.4
14
M.J
6
75.0
2-UNLIKELY
22
9.6
3
11.1
2
4.5
4
6.7
8
14.3
1
4.3
2
28.6
3
9.7
I
2.4
6
10.7
4
8.7
5
20.8
3-MAYBE
SO
15.2
3
11.1
8
16.2
8
13.3
4
7.1
6
26.1
4
12.9
7
17.1
7
12.5
6
13.0
4
16.7
~-LIKELY
15
6.6
3
11.1
3
6.8
5
8.3
3
5.4
1
4.3
2
6.5
4
9.8
4
7*1
2
4*3
1
12*5
5-VERY LIKELY
19
• .3
4
14.6
3
6.8
5
3
5.4
1
4JL
1
14.3
2
6.5
4
9.8
4
7.1
3
6*5
1
4.2
1
12.5
MEAN
1.89 2.26 1.89 1*92 1.66 1.87 1.86
1.81 2.05 1.86 1.7* 1.71 1.88
-®2»
-------
r
NATIONAL ANALTSTS
METAL FINISHING STUOY
tiivn PintriiiMTt
1557-11
OUESTION NO.V1-5 IF YOU
IN A WASTEWATER SYSTEM*
HAD THE ROOM TO PUT
BUT COULDN'T RAISE
THE CAPITAL. WHAT IS THE LIKELIHOOD THAI YOU
MI6HT ADD TO WORKING CAPITAL BY SELLIHa OFF
SOMF OF THE AS&ETS OF THE BUSINESS!
TOTAL
- - NUMBER
1-4 5-9 10-1V
OF FULL-TIME
20-49 50-99
PEOPLE
100- 250- 5006
249 499 MORE
UNDER
S100M
TOT
6100N
-249M
A L
S250M
-499M
SAL
•SOON
-999M
E S -
UM1L
-2.4
*2.5
MIL*
TOTAL
4*1
64 (9 tlB
111 46
13
54
•9
92
•6
49
11
NO ANSMEK
m
12 35 45
37 14
4
17
3<
24
26
17
4
NUMBER ANSWERING
204
100.0
>2 50 71
100*0 100.0 100.0
74 32
100.0 100.0
9
100.0
37
100.0
51
100.0
6«
100.0
SB
100.0
32
100.0
9
100.0
1-VEBY UNLIKELY
220
77.5
24 42 S3
75.0 B4.0 72.6
59 22
79.7 6B»fl
7
T7.B
30
•1.1
36
74.5
51
75.0
46
79.3
22
60.8
•
OS.9
2-UNLUELY
59
13.7
5 6 16
15.6 12.0 21.9
1 2
10.1 6.3
2
22.2
4
10.8
7
13.7
16
23.5
5
6.6
4
12.5
9-MAYW
IB
6.3
>15
9.4 2.0 4.1
6 5
•.1 15.6
2
5.4
3
5.9
5
B.6
6
IB.6
1
11.1
4-LIK.ELY
4
u«
1 1
2.0 1.4
1
3.1
1
2.7
2
3.9
1
1.7
5-VEBY LIKELY
s
1.1
1 2
1.4 6.3
1
2.0
1
1*5
1
1.7
MEAN
till
1.54 1.22 1.94
1.32 1.72
1.22
1.30
1.45
1.29
1.38
1.50
1*22
0B0
L.
J
-------
national analysts
METAL FINISHING STUDY
MJBVtr PARTICIPANTS-
<997-11
QUESTION NO.VJ-5 IF YOU HAO THE ROOM TO PUT
I.R41SE.
THE CAPITAL* WHAT IS THE LIKELIHOOD THAT YOU
MIGHT REDUCE THE OWNER'S COMPENSATION TO
HELP SECURF A HANK I OAN1
TOTAL
NUMBER OF FULL-TIME PEOPLE -- TOTAL SALES -
100- 290- 5004 UNDER SIOOM S290M S900M S1MIL S2.9
1-4 9-9 10-19 20—49 80-99 249 499 MORE tlOOH -249M -499M -999H -2.4 HIL+
JfllAk.
461
64
as ua
in
4*
IS
94
•9
92
a*
49
13
NO ANSWER
NUMBER ANSWERING
1—VERY UNLIKELY
2-UNLIKELY
3-MAYBE
4-UKELY
9-VERY LIKELY
MEAN
ITS
33
>3
AS
37
13
2*6 31 92 73 74 33 9
100.0 100«0 100iPlpO.Q lQOtOAOQ.0 100*0
134 II 21 32 33 17 9
46.9 >8.1 40,4 99.6
49
17.1
2
6*9
9 16
17.3 21.9
13
17.6
6 2
ia.2 22.2
97 9 11 14 16
19.9 16.1 29.0 19.2 21.6
6
la.2
l
ll.l
27
9.4
2
6.9
3
9.a
9 10
12.9 13.9
1
3.0
19 4
6.6 12.9
6
11.9
2
2.7
2
2.7
>
9.1
1
11.1
2.12 2.10 2.91 2.0a 2.12 2.00 1.89
ia
39
29
27
17
36 94 67 99 32 9
100.0 100.0 100.0 100.0 100.0 100.0
20 23 26 26 13 7
99.6 42.6 41.a 44.1 40.6 77.B
9 12
13.9 22.2
11 12 4 2
16.4 20.3 12*9 22.2
4
11.1
9 17 14 7
16.7 29*4 23.7 21.9
9
13.9
f a
9.3 11.9
4 4
6.8 12.9
2
9.6
9
9.3
3
4.9
3 4
9.1 12.9
2.00 2.20 2.21 2.0B 2.44 1.22
-------
f NATIONAL ANALYSTS
metal finishing study
SURVEY PANT1CIPANT&
1557-11
\
QUESTION HO.VI-3 if you
til A WASTEWATER SYSTEM*
HAD THE ROOM
BUT COULDN'T
TO PUT
RAISE
THE CAPITAL* WHAT IS THE LIKELIHOOD THAT YOU
MI6HT CLOSE DOMN THE BUSINESS! RETIRE OR
DO SOMETHING ELSE*
TOTAL
1-4
- - NUMBER Of FULL-TIME
5-9 10-19 20-49 30-99
PEOPLE -
100- 230- 3006
249 499 MORE
UNOER
S100M
TOT
S100M
-249M
A L
3230M
-499M
SAL
S500M
-999M
E S -
S1MIL
-2.4
m m
32.3
MIL*
TOTAL
461
44
l»
lit
111
46
13
34
•9
92
•6
49
13
NO ANSWER
1S1
24
2*
II
37
13
4
13
27
19
29
19
4
NUMBER ANSWERING
JOB
100.0
40
100.0
39
100.0
•0
100.0
74
100.0
31
100.0
9
100.0
41
100.0
62
100.0
73
100.0
37
100.0
30
100*0
9
100*0
I-VERY UNLIKELY
51
16.6
4
10.0
9
15.3
11
13. t
16
21.6
6
19.4
4
44.4
3
7.3
10
16.1
7
9.6
13
22.1
6
20.0
>
55.6
2-UNL1KELY
26
0.4
4
10.0
2
3.4
6
7.3
11
14.9
3
9.7
2
4.9
2
3.2
9
12*3
7
12*3
3
10.0
j-maybe
67 10
21.2 23.0
11
lli*.
23
33.0
20
27.0
12
SB.7
2
22.2
10
24.4
14
22.6
26
33*6
14
24.6
11
36.7
3
33.3
4-L1KELY
S3
17.9
*
13.0
11
16.6
IS
20.0
9
12.2
6
19.4
2
22.2
•
19.3
11
17.7
14
19.2
11
19.3
6
20.0
1
11.1
5-VERY LIKELY
•9
2B.9
16
40.0
24
44.1
19
23.1
IB
24.3
4
12*9
1
11*1
16
43.9
25
40.3
17
23*3
12
21* 1
4
13*3
MEAN
>•>4
l.i»
3.73
3.33
3.03
2*97
2.36
3.33
3.63
3.34
3.04
2.97
.2.00
0B2
V
-------
( national analysts
metal finishing study
SURVEY PARTICIPANTS
1557-11
1
QUESTION NO.VJ-5 if you
IN A WASTEWATER SYSTEMt
HAO THE ROOM
BUT COULDN'T
TO PUT
RAISE
the capital, what is the likelihooo that rou
MIGHT TRY to FIND A BUYER FOR THE BUSINESS*
no SFT IJB A MFftfiFBt
TOTAL
NUMBER
1-4 5—9 10-19
OF FULL-TIME
20-49 50-99
PEOPLE
100- 250-
249 499
5001
MORE
TOT
UNDER S100M
S100M -249M
A L
S250M
-499M
SAL
S500M
-999M
E S -
S1MIL
-2.4
82.5
MIL*
total
461
64 B5 118
111 46
13
54
89
92
86
49
13
no ANSWER
159
28 32 37
36 14
4
17
31
23
26
17
4
NUMBER ANSWERING
J 02
100.0
36 53 81
100.0 100.0 100.0
75 32
100.0 100.0
9
100.0
37
100.0
58
100.0
69
100.0
60
100.0
32
100.0
9
100.0
1-VERY UNLIKELY
50
16.6
5 10 11
13.9 18.9 13.6
14 4
18.7 12.5
2
22.2
4
10.8
11
19.0
10
14.5
13
21.7
4
12.5
3
33.3
2-VNLIKELY
26
9.3
3 4 1
8.3 7.5 9.9
7 4
9.3 12.5
2
22.2
3
8.1
3
5.2
5
7.2
6
10.0
5
15.6
1
11.1
3-MAYBE
B1
26.B
12 12 21
33.3 22.6 25.9
28 5
37.3 15.6
2
22.2
9
24.3
11
19.0
24
34.8
20
33.3
9
26.1
•"LIKELY
71
25.5
4 10 26
11.1 18.9 32.1
11 12
14.7 37.5
2
22.2
7
18.9
14
24.1
21
30.4
12
20.0
8
25.0
3
33.3
5-VERY LIKELY
72
23.B
12 17 15
33.3 32.1 18.5
15 7
20.0 21.9
1
11.1
14
37. S
19
32.8
9
13.0
9
15.0
6
18.8
2
22.2
MEAN
3.29
3.42 3.38 3.32
3.08 3.44
2.78
3.6S
3.47
3.20
2.97
3.22
3.00
0B3
-------
-------
THE PRINTED CIRCUIT BOARD INDUSTRY SURVEY
This appendix presents the methodology arid results
of our survey of manufacturers of Printed Circuit Boards.
Part 1 of this appendix describes how we defined the
sample and secured the data. All of the second part is
devoted to the findings. The last part of this appendix
presents the survey instrument used in the gathering of
data.
-------
THE METHODOLOGY OF THE SURVEY
The starting point of any survey is to define a uni-
verse and sample from it. In preparing the survey of
Printed Board manufacturers, the concern was that no defin-
itive listing of eligible firms appeared readily available.
Printed Board manufacturers do not appear as a ho-
mogeneous SIC listing with the Department of Commerce.
Firms belonging to the Institute of Printed Circuits tend
to be the larger producers, and are not exclusively in-
dependent producers.
A solution was provided when the EPA furnished a list-
ing of some 600 manufacturers of Printed Boards that had
submitted their products to Underwriters Laboratories (UL)
for approval. We asked Dun and Bradstreet to run a com-
puter match of this UL listing against their industrial
file. There were 508 "matches." DMI yielded a listing of
357 independent, domestic Printed Board producers. Given
the lack of any alternate, readily available list of firms,
we are prepared to treat the DMI list as an approximator of
the universe of independent Printed Board manufacturers.
-------
1. A SELECT SAMPLE OF PRINTED BOARD FIRMS WAS IDENTIFIED
FOR CONTACT
Through the earlier work on the metalfinishing industry,
we were heavily aware of the importance of good financial
data to complement the analytic data base of our closure
model. Equally keen was our awareness that gathering fi-
nancial data in survey work is difficult because of the
sensitivity and confidentiality of the information. We
needed the financial data but did not have time for a full
mail survey. A decision was made to order the latest fi-
nancial reports on approximately half the identified pop-
ulation. This yielded a randomly generated group of 190
firms all possessing financial records. Perusal of these
records showed slightly more than 100 provided values for
enough account categories to develop complete and consis-
tent balance sheets as well as sales and profit data.
All firms for which sufficient financial records
existed were defined as the segment of the universe to be
contacted. This pre-screening of the sample assumed two
risks. One, there is a certain probability of under-rep-
resenting smaller firms since they seem to be less likely
to volunteer their statements to D&B. A second is the
possibility that those firms offering data are overstating
their condition since no validation or certification of
the records is offered by D&B. While these biases could
be self"C&ncelingf the fact remains that the sample is
-------
neither fully stratified nor randomly drawn. All subsequent
results will have to be interpreted accordingly.
2. DIRECT PHONE INTERVIEWS WERE CONDUCTED
The attached telephone interview guide was developed
by Booz, Allen & Hamilton and the client. In addition, the
Technical Contractor was consulted for guidance on the pro-
duction and process items. Brevity guided the effort. Each
interview took fewer than 20 minutes to complete.
A team of special Booz, Allen & Hamilton consultants,
working for a week, made all the calls. Each call went
directly to the individual shown on the D&B listing as the
owner, president or chief officer.
Calls from the list of 190 continued until 100 inter-
views were completed. Reviewing all financial and tech-
nical data for accuracy yielded a sub-sample of 40 plants
that will be used for estimating compliance burdens for
the population.
-------
RESULTS OF THE PRINTED CIRCUIT
BOARD INDUSTRY SURVEY
This section of the report presents the results of our
telephone survey of independent Printed Circuit Board manu-
facturers (PB's). For purposes of comparability, as many
of the dimensions used to describe the metalfinishing job
shops will be used for the PB's as well. The dimensions
ate:
Size of the industry
Mix of processes
Role of metalfinishing
Pricing practices
Capital structure
Attitudes toward investment
Each is now developed in sequence.
1. ALL RESPONDENTS ARE COVERED BY THE GUIDELINES AS WILL
ALL 40Q FIRMS ESTIMATED IN THE POPULATION
All survey results for PB manufacturers will b& extrap-
olated to a population of 400 independent firms. Wherever
possible, our industry characterization will be compared
with other source estimates to illustrate convergence of
findings. Although there is the possibility that two inde-
pendent sets of estimates can both be wrong, agreement of
findings is one test for validity. In the absence of ob-
jective complete information, it is the best that can be
done.
-------
(1) On Average, the PB Industry Is a Larger Sales,
Smaller Water-Using Industry Than the Job Shops
Whereas 42% of the job shops were structured with
up to 10 full-time people, for PB's only 11% of the
sample has 1-9 employees. Fully 70% of PB firms are
in the (20-49) and (50-99) man intervals, while for
job shops, 33% of the population fell in the same
intervals.
The total employment of the PB industry is taken
by multiplying mean employment within categories by
the number of firms in that category and then summing
across categories. Table B-l below presents these
estimates.
Table B-l
Total Estimated Full Tijme Employment in the PB Industry
No. in
No. in
Mean
Total Est
Sample
Pop.
Employ.
Employ.
1-4
1
4
3.0
12
5-9
10
40
7.2
288
10-19
8
32
11.8
378
20-49
45
180
30.9
5,562
"50-99
25
100
64.3
6,430
100-249
6
24
135.0
3,240
250+
5
20
414.4
8,288
Total
100
400
24,198
The industry-wide mean employment is 60.5 (SD=90.6)
persons. The total employment is 24,200.
The next table displays the estimate of total metal-
finishing/printed board employment for the industry.
-------
We note that, on the average, if a typical PB firm has
61 full-time people, it also has 35 people working
directly in the production of PB's.
Table B-2
Total Estimated Production Employment in the PB Industry
No. in
No. in
Mean
Total Est
Sample
Pop.
Employ.
Employ.
1-4
4
16
3.5
56
5-9
15
60
6.6
396
10-19
20
80
15.1
1,208
20-49
43
172
29.9
5,143
50-99
14
56
64.8
3,629
100-249
3
12
179.7
2,159
250+
1
4
310.0
1,240
Total
100
400
13,831
Production employment is estimated to be on the order
of 13,800 with the mean employment per firm at 35 men
(SDs43.8).
It is on sales that we have the first source of
convergent information. From our sample results, the
estimated total sales for the PB industry are $610
million, with a per firm sales figure of $1.5 million.
Table B-3
Industry Total Sales
Total Industry
Sales
No. in
Mean
Sales
Up TO
Sample
Sales
(millions)
$ 250,000
18
$ 131,300
11.2
499,999
11
338,000
17.7
999,999
19
676,200
61.1
1,000,000
36
3,037,000
520.4
Total
84
$1,530,000
$610.4M.
-------
A report prepared for the Institute of Printed Circuits
estimates the total market (1975) at greater than $1
billion with independent producers projected at a 40%
share. This yields their industry estimate at $400
million compared with our calculation of $610 million.
The final two industry sizing measures that we
have been using are total plant water use and metal-
finishing process water use. In our survey, 72 re-
spondents gave data on plant water use. For the sample
as a whole, the mean total plant water use is 21,900
gallons per day. This is approximately one-half the
water use found in the metalfinishing job shop survey.
Metalfinishing process water is reported to be 86% of
the total plant figure or 18,800 gallons per day per
firm. Again this process water use ratio approximates
that found in the metalfinishing industry, although
in absolute terms, it is one-half the job shop value.
In terms of total usage, we can group the plant
water use by several sizing categories and extrapolate
across. These water use data appear below.
Table B-4
Industry Total Water Use
Gallons No. in Mean
Per Day Sample Use
Total
Use
(000's)
Under 1,000
1,000-4,999
5,000-19,999
20,000-49,999
Above 50,000
12
20
19
12
9
174
11.5
269.6
2,442
11,880
30,290
103,800
1,245.9
2,006.4
5,156.7
Total
72
21,900
8,690.1
-------
Our extrapolation suggests that the PB industry de-
mands 8.69 million gallons of water per day (one-
twentieth the job shops) of which 86% or 7.47 million
gallons per day is for metalfinishing process water.
Only 4% of the sample discharged directly to
navigable waters? 81% discharged to POTW's, 13% to
leaching ponds and 2% did not say.
(2) Basically, One Production Process Predominates
Several questions were asked during the telephone
survey about the production processes used by the firm.
In addition, the type of board and quantity produced
were also explored. We found that:
Two percent did just multilayer boards, 12%
did single-sided and 33% did double-sided.
Fully 53% do a combination of boards.
Eighty-six percent said the boards are through
hole plated, and the subtractive process is
employed eight times as prevalently as the
additive or semi-additive process (76% to
9%) .
Fifty percent of the sample produce 500 or
fewer boards a day. Another 25% do as many
as 1,000 per day. Only 10% of the sample
produces 3,000 or more finished boards in a
day.
The average size of a board is less than
one square foot.
259-718 O - 76 - 20
-------
(3) Virtually Every Firm Contacted Falls Into the
Electroplating Guidelines
We askdd each respondent to list the character-
istic metals and materials consumed in the course of
producing his finished boards. Below is a list of
trace materials and the proportion of the total sample
answering "yes," the metal/substance is present.
Copper 98%
Nickel 88%
Solder 86%
Tin 72%
Chrome 13%
Cyanide 18%
Gold 95%
Silver 11%
Fluorides 40%
Phosphorous 13%
Chelates 26%
2. MANY FIRMS SHOULD BE ABLE TO PASS ON THE INCREMENTAL
COSTS OF POLLUTION CONTROL
There are two considerations we investigated as part
of an analysis of the cost pass through characteristics of
the industry. One was a description of how dependeht the
firm was on its metalfinishing work. The other was a re-
quest for information on perceived pricing freedoms open
to the firm to recover the cost of putting in a pollution
control system.
-------
(1) Metalfinishing Is Integral to the Success of
Printed Board Manufacturers
Prior results from the job shop survey suggested
that some independent producers are market dependent
job shops, whereas others are independent producers who
manufacture for resale and own their inventories.
We asked two questions on this point:
Whether 100% of all company sales came from
the manufacture of PB's (if not, what was
the percent)
Whether the firm could divest itself of its
metalfinishing work and still be economi-
cally viable
The answers were as follows:
Two-thirds of the sample (69%) derives 100%
of its sales from PB's.
Only 12% of the sample derives 50% or less
of its total sales from PB's. Whereas 85%
of the sample enjoys at least three-quarters
of all its revenue from the sale of PB's.
There is little doubt that the vast majority of the
sample are direct manufacturers of boards. Confirming
this position is the fact that 80% of the sample said
"No, we cannot remain productive without metalfinishing."
12) The Sample Reports a 10% Price Increase
Possibility
Price increase was self-reported and targeted
specifically to raising prices to cover pollution
-------
control investment costs. We found that 39% of the
sample indicated a zero price increase, with another
21% indicating a l%-9% price rise. Fully 40% of the
sample said at least 10% with the sample mean at 11.2%
and an S.D. of 17.6%. On the average, this predicted
future price use is- on the same order of magnitude as
that reported by the job shop survey.
3. PB MANUFACTURERS APPEAR TO BE FINANCIALLY STRONGER THAN
JOB SHOPS
A key point in appreciating the capital structure of
the PB industry is to have a reference for comparison; in
this case the survey data from the job shops can serve.
Before arraying the sets of data, however, an important
qualifier must be introduced. The PB firms may be biased
in favor of the better capitalized ones because they are
the ones most likely to provide financial data to Dun and
Bradstreet. Although income statement items were not taken
from the D&B but requested orally, we want to introduce the
awareness of potential bias in the reader.
Table B-5, following this page, arrays income and
balance sheet items for the two samples.
In every line item the PB sample is not only larger,
but by analysis, it is stronger. The sales to fixed assets
ratio is higher for PB's (6.8 vs. 3.8) as is the profit to
-------
Table B-5
Selected Financial Items
Income Items
Sales
Profit BT
Profit AT
Job Shops
(n=344)
($000' s)
$676.0
30.1
15.6
PB Firms
(n=100)
($000's)
$1,520.0
64.6
25.1
Balance Sheet Items
Current Assets
Fixed Assets
Current Liabilities
Long Term Debt
Net Worth
$210
176
115
70
212
400.2
222.9
279.7
101.5
283.1
N = 40
-------
total assets (10% vs. 8%). In terns of leverage, I.e., debt
to equity, the groups are rather similar (36% vs. 33%) al-
though the total debt percent of the PB's is higher (57%
vs. 47%). It would seem that the cash flow situation of
PB's is superior to that of the job shops and they may
have more options toward absorbing new investments; either
through profits or debt.
4. PB ESTABLISHMENTS MAY BE BETTER PREPARED FOR MEETING
PRETREATMENT REQUIREMENTS THAN THE JOB SHOPS
In addition to the financial condition of PB establish-
ments relative to their future investments in pollution
control, two other factors pertinent to the issue assume
importance.
Amount of pollution control equipment currently
in place
Owner attitudes toward the investment
Data were gathered on each issue and will be developed
here.
(1) Various Water Conservation and Control Systems
Are Currently in Place
We asked two different types of questions on water
control systems. One had to do with conservation,
the other, with pollution control. On the first
issue, we found the following:
49% used water control series rinse, 74%
indicated spray rinse and 54% said they had
still rinse.
-------
Of advanced systems, 21% had ion exchange
systems in place, 12% had reverse osmosis,
7% practiced evaporative recovery.
Of the total sample, 54% indicated the pres-
ence of some end-of-pipe control. The com-
ponents listed by this 54% of the sample
are as follows:
Neutralization—42%
Clarification—28%
Chemical reduction—23%
Chemical precipitation—17%
Oxidation—6%
Flotation—7%
Sedimentation—0%
Filtration—29%
Approximately 62% of all equipment in place
is 3 years old or newer. The mean invest-
ment in pollution control equipment is
$44,476, with an S.D. of $74,490.
As was done with job shops, when pretreatment
systems are costed and applied to the PB industry,
credit will be given to the components already in
place.
(2) The Investment in Equipment Is Viewed as a
Necessary Business Loan
Of interest was the question of where an owner
would obtain the investment capital for a pollution
control system. Not surprisingly, 60% of the sample
anticipate a commercial bank loan. Only 4% would plan
to use owner's funds, whereas 10% see the funds coming
from profits or the cash flow generated by the business.
There were 14 respondents who said they did not believe
they could obtain any funds.
-------
5. A CLOSURE ANALYSIS OF PB FIRMS IS ALMOST IDENTICAL
TO THAT OF JOB SHOPS
The same financial closure model run for job shops
was applied to PB firms. There was one exception. No
data were obtained in the interviews on number of owners
or on owner's compensation because of its sensitive nature.
As a consequence, the issue of equity infusion as part of
the closure analysis will have to be based on a modeling
assumption rather than on survey data. In all other re-
spects, the analysis proceeded in the same manner. Because
many PB firms in the survey report equipment in place, and
appear to be well capitalized, compliance impacts on the
Printed Board industry are less than those estimated for
the metalfinishing job shop sector.
* * * *
This section has presented an industry characteriza-
tion of Printed Board manufacturers. In the next section,
the survey instrument used for gathering the data is
presented.
-------
-------
PRINTED CIRCUIT BOARD
TELEPHONE SURVEY
Date:
Interviewer:
Plant I. D. Number:
Company Name:
Address:
Phone Number:
Principal Name:
SIC's:
Status:
Completed
Incomplete
Terminated
Call back
-------
PRINTED BOARD PROTOCOL
Instructions
Call directly and ask for the individual identified on the cover
sheet.
If the identified individual is not available, establish whether he
or she will be available today or tomorrow.
If he will be available in a day, mark it a "call back" and go on
to your next call.
If the individual is out of the office for several days, then request
the name of another person in the firm able to comment on the
size and operations of the firm.
Enter the name of this individual on the cover sheet and
-------
SCALE OF OPERATIONS
1. What is the total employment at your plant?
# of plant employees
2. At any typical time, how many production
employees work directly in the manufacture
of printed boards?
of printed board employees
3. How many hours of the 24-hour day are spent on
printed boards?
# of hours _____
5. How many plating/finishing lines are set up
for your printed board production?
# of lines
6. Are 100% of your company sales from printed
boards?
( ) Yes (go to 9) ( ) No (go to 7)
7. What % of all your sales come from Printed Board
work? %
8. Could you list the other production activities at
your plant that generate revenues? How many
employees in each?
Activity
-------
TYPE OF OPERATION
1. What type of boards do you make?
Single sided
Double sided
Multilayer
1
2
3
2. Are the boards through hole plated?
Yes
No
Varies
1
2
3
3. Which production process do you use most frequently
4. For a typical order, what quantity of boards do
you produce in a day?
boards per day
5. What is the total immersed area of a board?
square inches or
square meters
6. How much water does your plant use in a day?
Gallons/day
or
Cubic feet/day
Additive
Subtractive
Semi-additive
Varies
1
2
3
-------
7.
How much of the plant's water is from the
printed board production lines?
% of plant total
or
Gallons per day
8. From the list of metals and chemicals found in
printed board operations, please identify the
ones found in your plant.
Copper Chrome Fluorides
Nickel Cyanide Phosphorous
Solder Gold Chilating
Tin Silver Agents
III. WATER TREATMENT
1. Where does your plant's discharge water go?
River or lake
Municipal sewer
Leaching Pond
2. Many plants practice water control. Do you use
any of the following?
Yes No
Countercurrent rinse
Series rinse
Running rinse
Spray rinse
Still rinse
3. Some plants have recovery systems in place.
Do you have:
Yes No
Ion exchange
Reverse osmosis .
Evaporation
4. Some plants are now treating their end-of-pipe
discharge water. Do you have any treatments
in place?
-------
5. Would you list the components of the system?
Neutralization
Clarification
Chemical Reduction
Chemical Precipitation
Oxidation
Flotation
Sedimentation
Filtration
6. How old is the system, and how much did it cost
installed?
Age in years
Installed cost
FINANCIAL ISSUES
"Now I would like to ask you a few questions about your
company's financial position. The EPA is quite concerned
with the ability of the Printed Board industry to manage
the investment in pollution control equipment. For us
to make that determination, we need to know the finan-
cial condition of affected firms.
"May I ask you about your firm's financial condition?
Is there any other person in your firm able to com-
ment on your finances?"
-------
1. There are five items from your income statement
that are important. From your latest fiscal year-end
statement, what were your company's:
Sales $
Depreciation
interest
Profit (Loss) Enter Loss
before Tax in parenthesis)
Profit (Loss) Enter Loss
after Tax in parenthesis)
2, There are also six items from your balance sheet
for the same period. We would like to know:
Current Assets $
Fixed Assets
Other Assets
Current Liabilities $
Long Term Debt
Company Net Worth
(Owners Equity)
B. OPTIONS
1. If you and all your competitors were to install
pollution control equipment, what is the maximum
you could raise prices before your business volume
might fall off significant ly ?
-------
t. Where would the capital come from to purchase
the pollution control equipment?
Bank loan
Owner's funds
Cash flow/profits
Other:
Can't get it
If the cost of pollution control equipment were a
serious problem, could your firm remain productive
doing no metal plating at all?
( ) Yes ( ) No
-------
-------
THE CAPTIVE METALFINISHING INDUSTRY SURVEY
This appendix presents the method, instrument, and
findings of the captive metalfinishing operations survey.
Detailed data on the financial condition of these opera-
tions were not gathered because a financial closure analysis
was not planned for this sector. Rather, the issue for cap-
tives is one of resource allocation and management decision-
making rules. A closure decision for captives depends on
process operations, alternatives to in-house work, and mar-
ginal increases in operating costs; more than on capital
availability and owner sacrifice.
The key points of this appendix ares
Study method
Data gathering instrument
Findings
1. ALL IDENTIFIED ESTABLISHMENTS LIKELY TO USE
MlTALFINISHING WERE MAILED A QUESTIONNAIRE
As in the study of the Printed Circuit Board industry,
the key starting point in the survey of captive operations
was to define the universe. Essential to any sample design
is knowing the totality of all cases defining the population
from which a sample can be drawn.
-------
There appears to be no definitive list of manufacturing
establishments known to house their own internal (captive)
metalfinishing operation. Industry experts said that
Products Finishing magazine was widely read in the metal-
finishing industry; that its subscription list probably in-
cludes a majority of businesses concerned with finishing, and
some prior survey data from the readership indicated the
finishing processes used by each subscriber. Inasmuch as
this readership list also served as the source data for
the National Commission on Water Quality's estimate of
60,000-80,000 captives, the list seemed appropriate as
the population of firms for our survey.
The editor of Products Finishing magazine provided full
cooperation with our effort under the following two condi-
tions:
Names and addresses of firms were not to be seen
by the Agency, or by BA&H. Mailing labels
would be provided only if we agreed not to see,
record, or identify respondents in any fashion.
This we agreed to.
Mailing was to occur at a single point, with no
means for second mailings, follow-ups or sub-
sequent contact. We agreed to this as well.
From the magazine's subscription list, approximately 8,800
firms (out of 22,000) were identified as currently involved
in finishing or plating operations defined under the Electro-
plating Point Source category. In early March, we sent a
-------
questionnaire to all 8,800 rather than to a selected sample.
By Friday, April 8, we closed down the effort with returns
from approximately .3,400 firms. Almost 40% of the population
returned a questionnaire. Of this total group of returns,
slightly fewer than half (47%) acknowledged doing a regu-
lated process. We have data on 1,610 captive operations.
The closure method and the planned analyses are pre-
sented in the next section.
2• A MODIFIED CLOSURE ANALYSIS WAS DEVELOPED FOR
CAPTIVE METALFINISHING ESTABLISHMENTS
To aid response rates and also because of the presumed
fiscal complexity of these firms, we did not solicit informa-
tion on income or balance sheet information. The closure
analysis cannot be a financially calculated routine. Such
financial data would have been of limited use because the
decision for captives is not whether the owner (or banker)
of a small firm considers the investment worthwhile, but
rather if a large firm, with presumed capital access would
find the investment worthwhile based on an analysis of alter-
natives: modifying the products or using jobbers.
Closures are estimated by inference. Of particular
importance to this qualitative closure analysis are the fol-
lowing issues:
Age and size of the finishing operation
-------
Criticality of the operation with respect to
production activities
Operating budget for finishing as a proportion
of total sales
Percent value added of finishing with respect
to the value of all finished goods sold
Amount of metalfinishing equipment in place
In sura, the closure test is whether a firm is "free"
to divest its captive operations. The analysis focuses on
the likelihood that a firm could economically as well as
operationally divest itself of its finishing given its
present commitment to the process. Firms likely to divest
rather than make the investment in requisite treatment sys-
tems are those which among other things:
Have the freedom to send out finishing work or
produce goods with an alternate finish
Produce relatively few metalfinished goods, and
for which the added value of finishing is minor
The full closure methodology for captives is presented in
Section 4 of this appendix.
3. SURVEY DATA YIELD A DETAILED PROFILE OF ESTABLISHMENTS
WITH CAPTIVE METALFINISHING OPERATIONS
There are four sequential steps to be taken in order to
characterize the captive sector of the metalfinishing indus-
try. They are the following:
-------
Arraying the respondents across the information
elements of the survey to appreciate frequency
patterns
Calculating mean scores for all continuous
variables in order to test for differences in
patterns
Applying alternative treatment scenarios to the
captives to appreciate marginal changes in costs
Incorporating sets of decision rules to identify
clusters of firms more or less burdened by the
investment.
Each of these steps has been followed and the results
for the 1,600+ respondents appear below.
(1) Captives Are Large Establishments in Which the
Captive Operation Appears Minor
In almost one-half (49.7%) of the cases, the plant
with the finishing operation sells at least $5 million.
The most heavily represented sales sector is $10M - $50M
with 35% of all respondents.
In terms of employment, facilities with captives
are far larger than job shops. One-sixth of all respon-
dents (16.7%) report having at least 1,000 total employ-
ees, with 57% having between 100 and 999 men. When the
employment data are tabulated by wetfinishing employ-
ees, the picture is far different. Less than 10% of the
sample (8.4%) has more than 50 people in finishing.
-------
More than half (53%) report between 5 and 49 men with
fully 38% of the sample reporting 1-4 men in wetfinish-
ing.
An additional means of appreciating the impact of
the in-plant value of metalfinishing is computing its
incremental cost as a percent of the total cost of the
finished good. On this variable# the pattern of re-
sponses suggests that metalfinishing is particularly
costly for one-quarter of th6 respondents; 24% report
that metalfinishing is at least 10% of the cost of the
final product. For 40% of the sample, the cost is 3%
and less. As will be shown in the closure methodology
section, it is within this low cost sector that the pos-
sibility for divesture exists most strongly. Interest-
ingly, when this variable is cross-tabulated against
employment, 22% of all respondents (376 cases) have 1-4
finishing employees and a 3% or under cost factor. As
employment increases along with finishing cost, divesti-
ture may be less likely. But for 376 cases eliminating
a low employment, low cost function seems an easier
management decision.
-------
(2) The Continuous Data Items Provide an
Appreciation of the Economic and
Environmental Significance of Captives
Sales and total employment at the plant move in
the expected linear fashion. While the sample overall
mean employment is 661 people, for firms selling
below $1,000,000 mean total employment is 177 people;
at plants selling in excess of §50,000,000, plant level
employment increases to 2,445,
Wetfinishing employment shows a similar linear
trend with sales but at a much reduced scale. For the
smallest sales interval, the mean wetmetalfinishing
employment is 5 people. At $50,000,000 in sales, wet-
metalf inishing rises to 54 people. Sample wide, wet-
metalfinishing employment accounts for 20 people per
firm.
On some other production indices, captive opera-
tions do not differ significantly from job shop opera-
tions .
On average, captives run 4.9 days a week,
with only firms at the largest sales inter-
val averaging more than 5 days a week.
There is no significant difference within
the sample on years in finishing. The
sample as a whole has done finishing for
23.6 years. Small sales plants have had
captives for 21.5 years and large sales
plants for 25.6 years.
-------
With respect to hours per day of captive
operations, jobbers and captives are quite
comparable. Smaller firms run 8.3 hours a
day and large ones run 16.5. Overall, the
sample reports 12.8 hours which is compara-
ble to the mean work time of job shop
operations.
On key issues pertinent to the pollution abatement
issue, there are striking differences between the
jobbers and captives samples.
On average, captive operations have made
a $740,000 capital investment in their metal-
finishing production equipment. By sales
intervals, this ranges from $170K for the
smallest group to at least $1 million for the
largest.
On average, captive operations operate on an
annual budget that closely parallels their
prior capitalization. Specifically, for
the entire sample the annual budget is
$736,000 with the small plants operating on
$127K with the largest exceeding $1 million.
On metalfinishing process water use, the size
of captive operations is most vivid. Each
day on average, the captives use 371,000
gallons of process water. Smaller firms
are at 34,900 with the largest at 555,000.
Captives reported their future capital in-
vestments for pollution controls over the
next 2 and 5 years. Overall, the sample
reported $140,000 in the next 2 years and
$340,000 in the next 5. Small firms report
short-term capital investments on the order
of $26K with the largest firms reporting
$400K.
Interestingly, the projected pollution control costs
for the sample under the full BPPT scenario represents
no conflict with the self reported investment plans
-------
with one exception. That exception rests with the
smallest plants.
For the total sample, the projected pollution
control capital is $194,000, not far removed
from the sample data of $140,000. The
largest plants will need approximately
$300,000 which falls within their estimation
of $340,000.
Small plants, those selling below $1,000,000,
are projected to need $55,000 for a system
and that is twice their reported planned
investment.
Clearly, the captives as a sector are quite large.
But the evidence suggests the smaller operations may
experience problems not dissimilar to those of some
job shops.
4. A CAPTIVES CLOSURE ANALYSIS USES AN INFERENTIAL
MODEL THAT IDENTIFIES FIRMS LEAST COMMITTED AND
CONSTRAINED TO KEEP THEIR FINISHING FUNCTION
Several new analytic variables were created from the
core questions of the captive's survey instrument. These
new variables are items that could not be asked outright
because they are not readily answered by respondents; or
they were created outside the instrument because they are
interactive; i.e., they build on the results of prior answers.
As examples, it is important to know the economic value of
the finishing operation with respect to the revenues gener-
ated by the final finished good. The question was
asked: what percent of the total value added of all goods
-------
produced at the plant is due to the value of the metalfin-
ishing? We were not optimistic that respondents could give
accurate estimates. Additional questions were built into
the instrument so that the same item could be computed from
those answers. Seven of these items are particularly key
to the closure analysis. They are the following:
Plant value added by metalfinishing: computed as
the product of the respondent's answers to
three items:
Annual sales at the plant
Percent of goods receiving metalfinishing
Cost of metalfinishing as percent of the
total cost
Corporate value added by metalfinishing: computed
as the product of answers to the following:
- Annual sales of corporation
Percent of goods receiving metalfinishing
- Cost of metalfinishing as a percent of the
total cost
Estimated pollution control annualized cost: com-
puted from flow rates, metals present, production
processes and value of equipment in place.
Estimated annual increase in the metalfinishing
budget: computed as the ratios
Estimated pollution control cost
Metalfinishing annual budget
Estimated increase in metalfinishing value added
due to the cost of the pollution control equip-
ment computed as the ratio:
Estimated pollution control cost
Plant value added by metalfinishing
-------
Estimated increase in sales price of goods receiv-
ing metalfinishing due to the cost of the pollution
control equipment: computed as the term:
Pollution control cost percent of all goods
Sales at plant x receiving metal-
finishing
Estimated risk factor, which is the incremental
increase in the metalfinishing equipment base rep-
resented by the investment in pollution controls:
computed as the ratio:
Pollution control capital cost
Replacement value of
metalfinishing equipment
In the following sections, the means for applying these
variables in a captives closure analysis will be presented.
(1) All Captives Can Be Described by Five Key
Variables
Given that no financial data are available for an
investment closure analysis, the method for estimating
closures tends to be qualitative.
From the analysis of the independent sector several
variables serve well as descriptive or sizing dimen-
sions. Two of these variables are common to both cap-
tives and jobbers; total plant sales and total metal-
finishing employment. Three of the sizing variables
are unique to this sector; they are value added by metal-
finishing, plant value added and the computed risk factor.
Combining and cross tabulating all firms within the
matrices created by these variables enables the closure
analysis to proceed.
-------
(2) Potential Closures Can Be Identified by Cell
Frequencies Within Matrices
Using these five sizing dimensions enables all
respondents to be scored and assigned to a specific
cell in a matrix. Not all possible combinations of the
variables are relevant and for purposes of this analysis,
5 matrices have been generated. They are:
Plant sales x value added
Plant sales x WMF employment
Value added x WMF employment
Plant value added x plant sales
Value added x risk factor
As suggested previously, there will be a certain
number of plants which on their position in a matrix
could be candidates to divest their in-house finishing
capacity. As an example, there will be a certain number
of firms that are characterized in the following terms?
they have:
. Few wetmetalfinishing employees
Finish few of their products
Low value added by finishing
High capital costs (risk factor)
Operational freedom to send out work
Were this the pattern for a firm, the prima facie
case could be made that it would chose to divest. These
are less economic predictions than estimates of cases
that satisfy a succession of cut-off criteria.
-------
Once this core group of candidates for divestiture
has been identified, the economic significance of such
divestitures can be computed. These calculations
involve projecting the total number of production em-
ployees affected, volume of finishing water curtailed,
shifts in total value added by finishing across pro-
duction sectors and incremental effects on pricing in
the job shop sector.
Estimates of captive operations that might choose
to divest are presented in the next major section.
5. FEW SURVEY RESPONDENTS APPEAR TO SATISFY
THE COST AND PRICE CRITERIA TO ALLOW CI\ESTITTJRE
OF THE CAPTIVE OPERATION
Two treatment scenarios were costed for the captive
operations. They are the same ones utilized in both the job-
bers and Printed Board sectors:
Full BPPT for all; cyanide oxidation, hexavalent
chromium reduction, clarification or filtration
for metals removal
Full BPPT for firms using at least 10,000 GPD
of process water with oxidation of amenable
cyanide and chromium reduction with no metals
removal for all firms below 10,000 GPD
For each cost scenario, the 5 matrices wore generated,
and cases arrayed. These matrices were used to identify clus-
ters of vulnerable operations.
C-13
-------
(1) Under Full BPPT 1% - 3% of All Cases Could
Choose To Divest
If investing in pollution controls adds signifi-
cantly to the total capitalization of the finishing
function, but the value added by finishing is quite
small, then a plant may judge the investment to be
unwarranted. Such a firm is then a candidate to divest.
In the sample, 84 out of 1,467 cases would at
least double their total capitalization in finishing
by the investment (risk factor — 1.00) but also report
a value added by finishing that is less than 1% the
value of all finished goods. This group is 5.7% of
all respondents. By broadening the categories to in-
clude all cases for which the risk factor is at least
.75 and for whom the value added is up to 3%, there
are 206 cases or 14% of the sample. These cases de-
fine the potential divestiture group.
Because the divestiture group is derived from
meeting a series of linked criteria, before closure
estimates can be finalized the behavior of these cases
on other key items must also be examined.
For the group of plants in which the value added
by finishing is less than 3% of the finished good, data
also exist on the requisite price increase of the
-------
finished goods needed to pass on the annualized invest-
ment burden. If a plant might divest because its risk
factor is hiqh and its value added low; it may choose
not to (divest) if the requisite price increase of
finished goods is low.
Fully 75% of all firms with a metalfinishing value
added of up to 3% also face price increases on their
finished goods of not more than 1%. Should 75% of the
206 cases with high risk and low value added feel free
to pass on a 1% price increase, then the maximum number
of estimated divestitures falls to 51 or 3% of the
sample. Under the more stringent case of a value added
of >1%, fully 72% need a price increase of >1%. This
yields a closure estimate of 24 firms or 1.6% of the
total.
Presuming very modest price increases on the order
of 1% or less has the effect of almost precluding cap-
tive closures.
(2) Under a Modified Abatement Scenario Closures
Are Essentially Unchanged
Introducing a modified abatement scenario aimed
at firms using hot more than 10,000 GPD of process water
has relatively little impact on captives. There were
1,125 respondents providing process water use data and
-------
386 (34%) fall below 10,000 GPD. There still remain
so many large water users receiving full BPPT systems
that average capital costs here are 95% of what they
are for the full-up case ($105K vs. $110K).
There are now 13% of all cases (200 of 1,461) that
fall in the cross-product of high risk (.75+) and low
value added (up to 3%). For this group, 77% can pass on
their pollution control costs by raising the price of
their metalfinished products not more than 1%. Should
this prove to be the case, then total estimated closures
are fewer than 50 or 3% of the sample. When the focus
is restricted to just those firms facing a risk factor
(<1.) and value added of under 1%, closures are limited
to 1% of the sample.
* * * *
This comoletes the presentation of findings. The
instrument and data follow.
-------
ft)
UNITED STATES ENVIRONMENTAL PROTECTION AGENCY
WASHINGTON. D.C. 20460
March 2, 1977
Dear Sir:
The U. S. Environmental Protection Agency is studying the effects
its regulations could have on the metal finishing industry. As
part of this effort we are sending the enclosed questionnaire to
some 10,000 firms who are thought to do metal finishing. Your
answers to the enclosed questions will help us to better understand
the economics of the industry.
You and other people in the industry have the best information on
the needs and capabilities of firms affected by EPA regulations. It
is vital for you and all firms surveyed to provide as much information
as possible so that potential economic problems can be more carefully
considered by the Agency.
You are not being asked to sign the questionnaire or in any way to
identify yourself or your firm. Your answers are anonymous and there
will be no way to connect the answers you give with you or your firm.
Only summary information such as "average sales of firms employing
ten to twenty people" will be used in reports.
Your cooperation in this survey is important to us, to the industry,
and most of all to you. With your help, we are confident that final
regulations will best balance the needs of all concerned.
Please answer all questions. If you are not certain about a question
perhaps one of your colleagues knows the answer. Please return the
completed questionnaire to National Analysts, the company conducting
the survey for us, by Friday, March 25. A postage paid return envelope
is provided. If you have any questions, feel free to place a collect
call to Mr. Nat Greenfield in Washington. He can be reached at
(202) 293-7933.
Thank you for your help.
Sincerely,
Roy MGamse, Director
Economic Analysis Division
-------
When filling in this questionnaire, please think of the word "plant" as
meaning the building or group of buildings in which your metal finishing
can be found.
1. Please circle a code number for each of the types of
electroplating activities done at this plant.
(CIRCLE AS
MANY AS
Copper
1
Nickel
2
Chromium
3
Cadmium
4
Zinc
5
Solder
6
Lead
7
Tin
8
Gold
9
Silver
10
Platinum metals group
1
Iron
2
Brass
3
Bronze
4
2. Please circle a code number>for each of the types of (CIRCLE A£
finishing activities done at this plant. MANY AS
APPLY)
Anodizing
1
Phosphating
2
Chromating
3
Chemical Milling/Etching
4
Printed Circuits
5
Electrochemical Milling
6
NOTEi IP YOUR PLANT DOES NONE OF THE ABOVE METAL FINISHING PROCESSES,
THEN PLACE A "CHECK" IN THE BOX, ANSWER NO FURTHER QUESTIONS, AND (—
PLEASE MAIL BACK THE QUESTIONNAIRE IN THE SELF-ADDRESSED ENVELOPE.
SCALE OF OPERATION
We wish to know in this section how extensive your in-house metal
finishing operation is.
Remember when we use the word "plant" in this questionnaire we mean the
building or group of buildings all at the same mailing address in whioh
your metal finishing oan be found.
3. What is the total employment at your plant?
-------
4. At any typical time, how many production employees work in plating or
finishing activities?
# OF METAL FINISHING EMPLOYEES:
5. Typically, how many hours of the 24-hour day are spent doing metal
finishing at the plant?
# OF HOURS OF METAL FINISHING:
6. Typically, how many days of each week are spent doing metal finishing?
# OF DAYS PER WEEK:
7. How many years has this plant done metal finishing?
# OF YEARS OF METAL FINISHING:
8. if today you were to replace all of the metal finishing production
equipment at your plant, how much would it cost? {Do not include costs
of pollution control equipment.) Please estimate to the best of your
ability.
REPLACEMENT VALUE: $
TYPE OF OPERATION
This section is concerned with your use of metal finishing, your customers
capacity and the like.
9. There are many reasons why a firm does in-house metal finishing.
Which of the reasons listed in the table below are factors in your
decision to do metal finishing in-house? Please circle a code number
for each reason which is a factor.
10. Now choose the two most important reasons for doing metal finishing
in-house. Please put a "1" in the column for the most important
reason and a "2" in the column for the second most important reason.
Reasons for
In-House
Two Most
Important
Reasons
No job shops in the area to send
work to
1
Job shops are not responsive to
our needs
2
Less expensive to do it in-house
3
Our work flow does not allow for
the interruption caused by sending
work out
4
Always have done our metal finish-
ing in-house
5
-------
11. Thinking about all of the metal finishing you do in-house, what
percent of that work is done with parte produced at yOUr plant?
What percent is done with parts sent in from other units of the
firm? What per.ei t is done with parts from outside customers?
% of Total
In-House Volume _
Parts produced here at
our plant
t
Parts sent to us from
other units of the firm
«
Parts from outside
customers
%
100%
Think of the last three yeara when answering Questions 12-15.
12. Please estimate the average annual sales of all goods produced at this.
plant. Your estiaat* should include the total value of the goods made
at this plant and the total value of the metal finishing done with
parts from out8j.ua uhis plant.
(CIRCLE
CODE)
13.
Under $1,000,000
$1,000,000 to $4,999,999
$5,000,000 to $9,999,999
$10,000,000 to $50,000,000
More than $50,000#000
What are the average annual sales of the whole corporation of which
you .« . p.xt7 (circm
Under $1,000,000
1
$1,000,000 to $4,999,999
2
$5,000,000' to $9,999,999
3
$10,000,000 to $50,000,000
4
More than $50,000,000
5
14. What percent of a.ll goods produced at this plant receive some metal
finishing?
% RECEIVE METAL FINISHING
-------
15.
16.
17.
18.
On the average, for the products made at your plant, how much of the
total cost to manufacture a product is due to the cost of metal
finishing?
(CIRCLE
Less than 1%
1
1% to 3%
2
4% to 6%
3
7% to 9%
4
10% or more
5
Don't know
V
Do you compile or receive on a regular basis a cost breakdown for the
metal finishing operation? (CIRCLE
Yes, for just this plant
1
Yes, but includes this plant
plus other locations
2
No, coots handled elsewhere
3
No, cost'1 not recorded
4
If records are kept for the metal finisning operation, please circle
the code numbers for all the items accounted for on a (CIRCLE AS
regular basis. j^Y AS
APPLY)
Total water
1
Piorf»ss water
2
Area plated
3
Jobs processed
4
Axrp hours
5
Chemical use
6
Factory overhead
7
Direut labor
8
Person hours
9
Revenues generated
10
CIRCLE CODE IP NONE OF THE ABOVE ITEMS IS ACCOUNTED FOR
In 1976, what was your total operating budget for doing metal
finishing at your plant?
METAL FINISHING BUDGET; $
V
-------
19. Please break down your 1976 metal finishing budget, showing the
dollar value* of the following itemsi
Dollar
value
Direct labor
$ I
Chemical
$ __
Water
S
Energy and utilities
r _
Other
$
POLLUTION ABATEMENT
The questions in this section all deal with your plant's waterkuse, metal
finishing, waste and pollution control measures.
20. Please fill in the table below showing your plant's water use for a
typical day dv ing 1976. Use gallons per day (GPD) if available.
If your information is in cubic feet or some other measurement,
please note it in the table.
Water Use GPD
Total plant
Metal finishing
process water
Other production
process water
21. Now please indicate where your metal finishing discharge water goes.
(CIRCLE THE CODE WHICH BEST DESCRIBES YOUR ANSWER)
Municipal sewer system
1
River, lake, pond, other
surface water
2
Both of the above
3
Holding tanks
4
22. Do you treat the effluent from your metal finishing operations at
this plant?
CONTINUE
Yes
1
GO TO NEXT SECTION
No
-------
23. How much have you spent to buy all of your water pollution control
equipment at the plant? (Use actual costs, not book or replacement
value.)
(CIRCLE
CODE)
Under $100,000
1
$100,000 to $249,999
2
$250,000 to $499,999
3
$500,000 to $1,000,000
4
More than $1,000,000
5
24. How much of this total capital investment represents the cost of
treating metal finishing wastes? (CIRCL
CODE)
100% - All of it
1
75% - Most of it
2
50% - About half
3
25% - Little
4
0% - None
5
ABATEMENT DECISIONS
This section is to be filled in by all respondents whether or not your
plant has a water pollution control system. The concern here is how your
plant did approach, or might approach, its investment decision.
25. Many issues, both of cost and production, may be part of a decision
to invest in pollution control. From the issues listed below;
please identify the three issues your plant judged most . M0ST
important. IMPORTANT
ISSUES
Size of required investment
1
Potential cost impacts of the investment
2
Feasibility of changing finishing processes
3
Feasibility of sending out metal finishing
4
Deciding on what system to install
5
Deciding how and when to install the system
6
Relocating metal finishing operations
7
Changing from or to a municipal sewer system
8
-------
26. If you have not participated in planning meetings for pollution
control and/or your plant does not have water pollution controls,
please review the list of reasons below and circle all items that
apply.
(CIRCLE
CODES)
Other people are responsible for it
1
It is not considered a problem
2
Pollution control planning is low priority
3
Other (WRITE IN:
0
)
27. Based on your best estimate, how much will your plant spend on pollu-
tion control equipment during the next 2 years? During the next 5
years?
2 YEARS $
5 YEARS $
THIS COMPLETES THE QUESTIONNAIRE. THANK YOU. PLEASE
MAIL IT BACX IN THE ENCLOSED ENVELOPE.
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY <815-21
QUESTION NO.I WHICH TYPES OF ELECTRO-
PLATING ACTIVITIES ARE DONE AT
THIS
PLANTT
- - —
PERCENTAGE
VALUE
ADDED -
- -
- T Q T
A L PL
A N T
SALE
S -
LESS
MOKE
THAN
1-3
4-6
7-9
10 OR
UNDER SI
MIL- *5
MIL- S10-50
THAN
TOTAL
1 PCT
PCT
fCT
PCT
MOKE
SI MIL 4.
9 MIL 9.
9 MIL MILLIOH J50 MIL
TOTAL
1614
254
400
270
155
394
175
367
233
565
237
NO ANSWER
480
loe
121
76
52
90
57
125
79
143
68
NUMBER ANSWERING
1134
146
279
194
103
304
118
242
154
422
169
100.0
100.0
100,0 100.0
100.0
100.0
100.0
100.0
iuo.o
100.0
100.0
COPPER
579
67
127
77
47
198
65
123
76
168
111
51.1
45.9
45.5
39.7
45.6
65.1
55.1
50.8
49.4
44.5
65.7
NICKEL
709
61
148
120
67
240
80
172
93
230
115
62.5
41.0
53.0
61.9
65.0
78.9
67.8
71.1
60.4
54.5
68.0
CHROMIUM
459
*9
89
79
44
143
40
78
69
163
97
40.5
33.6
31.9
40.7
42.7
47.0
33.9
32.2
44.8
38.6
57.4
CADMIUM
282
3*
77
48
32
50
24
47
32
107
65
24.9
23.9
27.6
24.7
31.1
16.4
20.3
19.4
20.8
25.4
33.5
ZINC
400
40
110
70
51
88
25
68
60
168
70
35.3
27.4
39.4
36.1
49.5
28.9
21.2
28.1
39.0
39.6
41.4
SOLDER
152
18
37
21
16
46
19
30
22
40
37
13.4
12.3
13.3
10.6
15.5
15.1
16.1
12.4
14.3
9.5
21.9
LEAD
54
5
10
10
4
18
4
10
5
1*
15
4.8
3.4
3.6
5.2
3.9
5.9
3.4
4.1
3.2
4.5
8.9
TIN
228
36
64
23
28
54
20
35
21
90
58
20.1
24.7
22.9
11.9
27.2
17.6
16.9
14.5
13.6
21.3
34.3
GOLD
27 2
28
55
38
23
94
40
67
33
66
54
24.0
19.2
19.7
19.6
22.3
30.9
33.9
27.7
21.4
15.6
32.0
SILVER
209
25
49
34
21
48
20
43
25
70
45
18.4
17.1
17.6
17.5
20.4
15.8
16.9
17.8
16.2
16.6
26.6
PLATINUM METALS GROUP
71
9
12
8
e
26
10
21
7
13
18
6.3
6.2
4.3
4.1
7.6
8.6
a.5
8.7
4.5
3.1
10.7
IRON
31
2
13
4
4
7
3 .
7
2
13
6
2.7
1.4
4.7
2.1
3.9
2.3
2.5
2.9
1.3
3.1
3.6
BRASS
143
5
25
14
21
62
12
44
20
51
12
12.6
3 .4
9.0
7.2
20.4
20.4
10.2
18.2
13.0
12.1
7.1
-------
(CONTINUED PAGE 21
NATIONAL ANALYSTS
METAL FINISHING STUDY 1815-21
QUESTION NO.l WHICH TYPES 0T ELECTRO-
PLATING ACTIVITIES ARE DONE AT THIS
PLANT?
LESS
THAN
TOTAL 1 PCT
BRONZE 43 2
J«» 1*4
HOT DIP GALVANIZE
OOI
PERCENTAGE VALUE ADDED
1-3
4-6
7-9
PCT
PCT
PCT
1
A
6
2*9
2.1
1.1
- - -TOTAL PLANT SALES-
NORE
10 OR UNDER SI MIL- S3 MIL- S10-S0 THAN
MORE SI MIL 4.9 MIL 9*9 MIL MILLION »50 MIL
20 4 8 S 1ft 7
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY 1815-21
QUESTION NO.2 WHICH TYPES OF
FINISHING
ACTIVITIES ARE DONE AT THIS
PLANT?
— — -
PERCENTAGE
VALUE
ADOED -
— —
-TOT
ALP
L A N T
SAL
E S -
LESS
MOKE
THAN
1-3
4-6
7-9
10 OR
UNDER SI
MIL-
S5 MIL-
$10-50
THAN
TOTAL
1 PCT
PCT
PCT
PCT
MORE
SI MIL 4.
9 MIL
9.9 MIL
MILLION
>50 MIL
TOTAL
1614
254
400
270
155
39 4
175
167
233
565
237
NO ANSWER
329
58
75
46
27
97
58
97
44
100
IB
NUMBER ANSWERING
1285
196
325
224
128
297
117
270
189
465
219
100.0
100. U
100.0 100.0
100.0
100.0
100.0
luo.o
luo.o
lOO.O
100.0
ANODIZING.
310
29
69
58
29
79
25
66
43
105
67
24.1
14.8
21.2
25.9
22.7
26.6
21.4
24.4
22.8
22.6
30.6
PHOSPMATING
718
11«
200
119
81
135
46
123
93
295
147
55.9
60.2
61.5
53.1
63.3
45.5
39.3
45.6
49.2
63.4
67.1
CHRCiMATING
634
¦»7
177
113
73
127
47
125
es
239
123
49.3
39.3
54.5
50.4
57.0
42.8
40.2
46.3
46.6
51.4
56.2
CHEMICAL HILLING/ETCHING
279
45
56
45
*4
76
25
50
38
82
78
21.7
23.0
17.2
20.1
18.8
25.6
21.4
18.5
20.1
17.6
35.6
PRINTED CIRCUITS
191
26
S7
28
12
48
29
39
19
45
54
14.9
13.3
17.5
12.5
9.4
16.2
24.8
14.4
10.1
9.7
24.7
ELECTROCHEMICAL MILLING
59
13
17
9
6
8
5
2
3
23
24
4.6
6.6
5.2
4.0
4.7
2.7
4.3
.7
1.6
4*9
11.0
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY I81S-2I
QUESTION NO.3 WHAT IS THE TOTAL
EMPLOYMENT AT YOUR PLANT*
m
LESS
Than
TOTAL X PCT
TOTAL 161* 254
NO ANSWER 49 9
NUMBER ANSWERING 1969 24$
100.0 100.0
1 TO 49 EMPLOYEES 222 28
14.1 11.4
SO TO 99 EMPLOYEES ITS 1*
11.3 6.9
iOO 10 199 EMPLOYEES 266 37
17.0 19.1
200 TO 499 EMPLOYEES 379 61
24.2 24.9
500 TO 999 EMPLOYEES 262 46
16.7 IS.8
1.000 TO 1.999 EMPLOYEES 133 23
S.5 9.4
2*000 OR MORE EMPLOYEES 129 14
S.2 13.9
AVERAGE 661.19 993.80
003
PERCENTAGE VALUE
ADDED
- - -
-TO
T A L P
L A N T
>
r
E S -
MURE
1-3
4-6
7-9
10 OR
UNDER
81 MIL-
SS M1L-
»lo-ro
HAN
PCT
PCT
PCT
MCRE
MIL
4.9 MIL
9.9 MIC
M.LLJOH
S50 MIL
400
270
155
394
175
367
233
569
231
13
10
2
9
6
6
6
19
9
387
260
193
389
169
361
227
946
232
100.0
100*0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
92
33
IT
70
121
76
9
7
3
13.4
12.7
11.1
18.0
71.6
21.1
4.0
1.3
1.3
39
27
26
63
19
128
19
5
4
9.0
10.4
17.0
16.2
11.2
39.9
8.4
.9
1*7
62
49
31
69
11
120
93
34
2
16.0
17.3
20*3
17.7
6.9
33.2
41.0
6.2
.9
90
74
~0
99
6
29
86
246
12
23.3
28.9
26.1
29.4
3.6
6.9
37.9
49.1
9.2
71
49
20
42
7
8
12
195
34
20.2
17.3
13.1
0.8
4.1
2.2
9.3
35.7
14.7
*1
20
10
22
2
3
2
55
66
0.6
7.7
6.9
9.7
1.2
.8
.9
10.1
28.4
29
16
9
24
3
1
6
4
111
7.9
6.2
9.9
6.2
1.8
.3
2.6
.7
47.8
663.40
984.92
930.41
497.93
177.19
126.96
322.96
944.03
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY 1815-21
QUESTION NO.4 AT ANY YYPICAL T
MANY PRODUCTION EMPLOYEES WORK
ING Oft FINISHING ACTIVITIES?
TOTAL
NO ANSWER
NUMBER ANSWERING
1 TO * EMPLOYEES
5 TO 9 EMPLOYEES
10 TO 19 EMPLOYEES
20 TO *9 EMPLOYEES
90 TO 99 EMPLOYEES
100 TO 2*9 EMPLOYEES
250 TO A99 EMPLOYEES
500 OR MORE EMPLOYEES
AUTOMATED SYSTEM
AVERAGE
004
• HOW
PIAT-
- - -
PERCENTAGE VALUE
LESS
THAN
1-3
4-6
TOTAL
1 PCT
PCT
PCT
161*
254
400
270
IS
2
3
1
1599
252
397
269
lOO.O
lOO.O
lOO.O
100.0
609
176
200
97
38.1
69.8
50.4
36.1
293
35
84
59
18.3
13.9
21.2
21.9
293
2A
*7
58
18*3
9.5
11.8
21*6
267
13
*8
34
16.7
5.2
12.1
12.6
75
3
13
14
A.7
1.2
3.3
5.2
AS
5
5
2.8
1.3
1.9
9
1
• 6
•4
6
1
• A
.4
2
1
.1
.41
20.18
5.50
11.17
17.13
AODED -TOTAL PLAHT SALES-
MOKE
7-9 10 OR UNDER *1 MIL- S5 MIL- S10-50 THAN
PCT MORE SI MIL 4.9 MIL 9«9 MIL MILLION #50 MIL
155
394
175
367
233
565
237
3
5
1
3
8
3
152
389
174
364
233
557
234
lOO.O
100.0
100.0
100.0
1U0.0
100.0
lOO.O
30
67
115
191
88
159
42
19.7
17.2
66.1
52*5
37.8
28.5
17.9
28
67
32
79
A8
103
26
18 .A
17.2
18.A
21.7
20.6
18.5
11.1
35
92
18
58
50
120
39
23.0
23.7
10.3
15*9
21*5
21.5
16*7
46
9*
7
31
32
125
65
30.3
25.2
4.0
8.5
13.7
22.4
27.8
6
29
2
A
10
31
28
3.9
7.5
1.1
1.1
4.3
5.6
12.0
b
24
1
4
16
23
3.9
6.2
¦ 3
1.7
2.9
9,8
8
1
2
5
2.1
• A
.4
2.1
1
3
1
5
.7
.8
.2
2.1
1
1
.3
.4
23.96
37.90
5.25
7*70
14.5«
21.18
-------
NATIONAL ANALYSTS
METAL FINISHING STUOY C813-2I
OUESTION NO.3.4 PERCENTAGE
IN METAL FINISHING
OF WORKERS
TOTAL
LESS
THAN.
1 PCT
total
1614
294
NO ANSWER
96
11
NUMBER ANSWERING
1996
100.0
243
loo.o
LESS THAN 29 PERCENT
1421
91.3
240
98.8
25 TO 49 PERCENT
63
4.0
1
¦ 4
SO TO 74 PERCENT
31
2.0
79 PERCENT OR MORE
41
2.6
2
.1
AVERAGE
•«17
.2.50
003
PERCENTAGE VALUE ADDED
1-3 7-9
PCT PCT PCT
400
270
199
19
10
5
385
260
190
1O0.0
100.0
100.0
36V
252
138
99.6
96.9
92.0
4
2
•
1.0
.0
9.3
*
2
1
1.6
.8
• 7
_ 7
l.a
1.9
2.0
5.J 6
6*46
9.90
-TOTAL PLANT SALES-
10 OR UNOER SI MIL- S9 MIL- «10-50 THAN
MORE SI MIL 4.9 MIL 9*9 NIL NlLLIOrt *50 MIL
394
179
367
233
965
237
10
7
10
6
29
7
384
168
357
227
940
230
100.0
100.0
100.0
100.0
luO.O
100.0
309
126
317
206
921
223
•0.9
79.0
•8.8
90.7
96.5
97.0
42
17
20
14
7
10.9
10.1
9.6
6*2
1.3
1*3
18
8
11
3
6
4.7
4.8
3.1
1*3
1.1
• 9
19
17
9
4
6
3.9
10.1
2.9
1.8
1.1
•9
16.82
2U36
11.33
9.26
9.75
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY 1615-2)
QUESTION NO.5 HOW MANY HOURS OF THE
24-HOUR DAY ARE SPENT DOING KETAL
FINISHING AT THE PLANT?
LESS
THAN
TOTAL 1 PCT
TOTAL 1*1* 25*
NO ANSWER 15 1
NUMBER ANSWERING 1599 253
100.0 100.0
LESS THAN 1 HOUR 5 4
*3 1*6
1 TO 8 HOURS 709 1*7
44*3 58.1
9 TO 16 HOURS 563 73
35.2 28.9
17 TO 24 HOURS 322 29
20.1 11.5
AVERAGE 12.82 10.51
006
PERCENTAGE VALUE ADDED -
1-3
4-6
7-9
PCT
PCT
PCT
400
270
155
3
5
2
397
265
153
100.0
100.0
100.0
1
.3
191
119
57
48.1
44.9
37.3
136
89
69
34.3
33.6
45.1
69
57
27
17.4
21.5
17.6
12*32
13.17
13.32
-TOTAL P
10 OR
MORE
UHOE.R
SI MIL
SI MIL-
4.9 MIL
394
175
367
1
3
3
393
100.0
172
100.0
364
100.0
2
1.2
1
.3
142
36*1
121
70.3
221
60.7
134
34.1
43
25*0
103
28.3
117
29.8
6
3.5
39
10.7
14.18
8.33
10*43
ANT
SAL
fc S -
MOKE
MIL—
S10-50
THAN
9 MIL
MILLION
S50 MIL
233
565
237
2
6
1
231
559
236
100.0
100.0
100*0
I
.4
111
191
46
49.1
34.2
19.5
81
216
107
35.1
38.6
45*3
39
150
83
16*9
26*0
35*2
12.42
14.4^
-------
NATIONAL ANALYSTS
METAL FINISHING STUOY 1615-2)
QUEST ION NO.6 HOW MANY
DAYS OF EACH WEEK
ARE SPENT DOING METAL
FINISHING?
• — •»
PERCENTAGE VALUE
ADDED
— — —
-TO
T
ALP
LAN
T SAL
E S -
LESS
MORE
THAN
1-3
*-6
10 OR
UNDER
SI
M1L-
85 HIL-
810-50
THAN
TOTAL
I PCT
PCT
PCT
PCT
MORE
>1 MIL
4.
9 MIL
9*9 MIL
MILLION
S50 MIL
TOTAL
1614
25*
400
270
155
394
175
367
233
565
237
NO ANSWER
10
5
1
1
1
2
4
1
2
2
NUMBER ANSWERING
1604
2*9
399
269
194
392
175
363
232
563
235
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
LESS THAN 1 DAY
»
3
1
1
2
2
1
.3
1.2
.3
• 6
1.1
.6
.2
1-5 DAYS
1492
230
371
251
138
336
168
334
219
512
105
90.5
92.4
93.0
93.3
89.6
85.7
96.0
92.0
94.4
90. V
78.7
6 DAYS
126
14
27
17
11
44
2
23
12
44
43
7.9
5.6
6.6
6*3
7.1
11*2
1.1
6.3
5.2
7.8
18.3
T DAYS
21
2
1
4
12
3
4
1
6
7
1.3
.8
.4
2.6
3.1
1.7
1.1
.4
1.1
3*0
AVERAGE
4,11
6.57
4.83
4.87
4.94
5.06
4.31
4.76
4.94
5.00
5.18
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY
(815-2)
OUESTION NO*? HOW MANY YEARS HAS THIS
PLANT DONE METAL FINISHING!
PERCENTAGE VALUE ADDED
LESS
THAN
1-3
4-6
7-9
TOTAL
1 PCT
PCT
PCT
PCT
total
1614
254
400
270
155
NO ANSWER
27
7
4
5
2
NUMBER ANSWERING
1587
247
396
265
153
100.0
100.0
100.0
100.0
100,0
LESS THAN 10 YEARS
265
41
80
46
18
16.7
16.6
20.2
17.4
11.8
10 TO 19
*46
72
109
72
40
28.1
29.1
27.5
27.2
26.1
20 TO 29
410
77
102
57
44
25.8
31.2
25.8
21.5
26.8
30 TO 39
202
24
41
42
23
12.7
9.7
10.4
15.8
15.0
*0 TO 49
14
26
17
11
6.1
5.7
6.6
6.4
7.2
90 YEARS OR MORE
167
19
38.
31
17
10.5
7.7
9.6
11*7
11.1
AVERAGE
23.90
21.97
22.63
24*30
25*35
10 OR
MORE
-TOTAL P
UNDER SI MIL-
SI MIL 4.9 MIL
L A N T
S5 MIL—
9*9 MIL
SAL
810-50
MILLION
E S -
MORE
THAN
*50 MIL
394
175
367
23i
565
237
6
2
7
4
6
4
388
100.0
173
100.0
360
100.0
229
100.0
559
100. t)
233
100.0
64
16.5
40
23.1
79
21*9
38
16*6
76
13.6
24
10.3
112
28.9
47
27.2
113
31.4
80
34.9
149
26.7
49
21.0
91
23.5
44
25.4
69
19*2
50
21*8
159
28.4
7a
33.5
52
13.4
18
10.4
35
9*7
26
11*4
73
13.1
44
13.9
22
5.7
8
4.6
24
6*7
7
3*1
42
7.5
15
6*4
47
12*1
16
9.2
40
11.1
28
12.2
60
10.7
23
9*9
25*45
21*67
24.26
23*10
24.81
25.91
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY (815-21
QUESTION NO*6 IF TOOAY YOU WERE TO
REPLACE ALL OF THE METAL FINISHING PROD-
UCTION EQUIPMENT AT YOUR PLANT* HOW
MUCH WOULD IT COST?
- - -
percentage value
ADDED
- - -
-TO
T
ALP
LAN
v»
>
r
E S -
LESS
MOKE
THAN
1-9
4-6
7-9
1C OR
UNDER
*1
MIL-
*5 HIL-
*10-50
THAN
TOTAL
1 PCT
PCT
PCT
PCT
MORE
*1 MIL
4.
9 MIL
9*9 MIL
MILLION
*50 MIL
TOTAL
1614
254
400
270
155
994
175
967
293
565
297
NO ANSWER
52
10
10
6
5
19
14
12
8
io
7
NUMBER ANSWERING
1562
244
990
264
150
961
161
955
225
555
290
100,0
100.0
100*0
100*0
lOO.O
100.0
100.0
100.0
100.0
100.0
100.0
less than sio*ooo
95
45
24
12
1
7
28
95
4
20
9
6*0
IS.4
6*2
4.5
.7
1.8
17.4
9.9
1*8
9.6
1*9
*10*000 TO <49*999
222
66
70
92
12
92
54
68
98
44
11
14.2
27.0
17*9
12.1
8.0
8.4
99.5
19.2
16.9
7.9
4.8
>50*000 TO *99* 999
165
40
47
92
10
27
24
56
24
49
12
10.6
16.4
12.1
12.1
6.7
7.1
14.9
15.8
10.7
8.8
5*2
*100*000 TO *499*999
591
66
157
107
69
199
46
156
96
221
56
97.8
27.9
40.9
40.5
42.0
96.5
28.6
49.9
42.7
99.8
24.3
*500*000 TO *999*999
lea
7
42
97
26
56
5
27
39
88
29
12.0
2.9
10.8
14.0
17.9
14.7
9.1
7.6
14.7
15.9
12*6
Sl*0O0*000 TO *4.999*999
246
15
44
99
29
99
9
12
27
116
84
IS.7
6.1
11.9
14.8
19.9
24.4
1.9
9.4
12.0
20.9
96.5
*5*000*000 OR MORE
57
9
6
5
9
27
1
1
3
17
95
9.6
1.2
1.5
1.9
6.0
7.1
.6
.9
1.9
9.1
15.2
AVERAGE 1THOUSANDS1
56
269
495
599
1195
1188
169
2 J *
505
811
2102
-------
national, analysts
METAL FINISHING STUOY (015-21
QUESTION HO.9 WHAT ARE THE REASONS WHICH
ARE FACTORS IN YOUR DECISION TO
DC METAL
FINISHING IN-HOUSE1
- - -
percentage
VALUE
AOOED -
- —
-TOT
ALP
L A N T
sal
t S -
LESS
MOKE
THAN
1-3
4-6
7-9
10 OR
UNDEH SI MIL-
$5 MIL-
810-50
THAN
TOTAL
I PCT
PCT
PCT
PCT
MORE
SI MIL 4
.9 MIL
9.9 MIL
MILLION
S50 MIL
TOTAL
1614
254
400
270
155
394
175
367
233
565
237
NO ANSWER
29
2
2
2
14
13
6
3
2
2
NUMBER ANSWERING
1585
252
398
268
155
380
162
361
230
563
235
100.0
loo.o
100.0 100.0
100.0
100.0
100.0
100.0
IttOmO
100.0
100.0
NO JOB SHOPS IN THE AREA TO
350
52
90
62
37
81
37
76
53
127
50
SEND WORK TO
22.1
20.6
22.6
23.1
23.9
21.3
22.8
21.1
23.0
22.6
21.3
JOB SHOPS ARE NO* RESPONSIVE
654
93
163
102
61
180
66
153
85
232
99
TO OUR NEEDS
41.3
36.9
41.0
38.1
39.4
47.4
40.7
4 2.4
37.0
41.2
42.1
LESS EXPENSIVE TO DO IT
1207
163
315
217
124
ilk
99
262
182
457
180
IN-HOUSE
76.2
72.6
79.1
81.0
80.0
72.1
61.1
72.6
79.1
61.2
76.6
WORK FLOW DOESN'T ALLOW INTER-
1332
212
332
220
137
317
118
29J
186
<*94
217
RUPTION OF WORK SENT OUT
84.0
84.1
83.4
82.1
88.4
83.4
72.8
81.2
80.9
87.7
92.3
ALWAYS HAVE DONE CUR METAL
663
87
140
115
78
196
66
152
105
236
115
FINISHING IN-HOUSE
43.1
34*5
35.2
42.9
50.3
51.6
40.7
42.1
45.7
41.9
48.9
OTHER REASONS
8
2
2
1
1
1
4
2
1
.5
.8
.7
.6
.3
. 6
1.1
.4
• 4
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY I8I5-2)
QUESTION NO*10 WHICH OF THESE IS THE
MOST IMPORTANT REASON FOR DOING METAL
FINISHING IN—HOUSEf
TOTAL
LESS
than
1 PCT
TOTAL
1614
25*
NO ANSWER
191
26
NUMBER ANSWERING
1423
100.0
220
100.0
NO JOB SHOPS IN THE AREA TO
SEND WORK TO
51
2.6
10
4.4
JOB SHOPS ARE NOT RESPONSIVE
TO OUR NEEDS
193
9.9
16
7.9
LESS EXPENSIVE TO DO IT
IN-HOUSE
*80
33.7
60
26.3
WORK FLOW DOESN'T ALLOW INTER-
RUPTION OF WORK SENT OUT
68*
*8.1
135
59.2
ALWAYS HAVE DONE OUR METAL
FINISHING IN-HOUSE
70
4.9
4
1.8
other REASONS
4
.9
1
.*
Oil
'ERCENTAGE VALUE
AOOED -
— -
1-3
4-6
7-9
10 OR
PCT
PCT
PCT
MORE
400
270
155
394
)l
30
13
59
362
240
142
335
100.0
100.0
100.0
100.0
19
6
5
9
5.2
2.5
3.5
2.7
II
21
10
32
10.5
8.8
7.0
9.6
124
96
48
122
34.3
40.0
33.9
36.4
170
112
68
140
47.0
46.7
*7.9
41.8
11
4
10
32
3.0
1.7
7.0
9.6
i
1
• 4
.7
•TOTAL PLANT SALES-
MQR&
UNDER SI MIL- S5 NIL- S10-50 THAN
SI MIL 4.9 MIL 9.9 MIL MILLION *50 MIL
175
367
233
565
237
45
46
23
>2
15
130
321
210
51J
222
100.0
100.0
lOO.O
100.0
100.0
14
1*
7
12
2
10.8
4.4
3.3
2.3
.9
13
35
17
40
22
10.0
10.9
8.1
7.8
9*9
31
101
80
198
«0
23.8
31.5
38.1
3*i6
27.0
58
153
90
249
127
44.6
47.7
*2.9
*9.3
57.2
14
16
16
1*
10
ic.a
5.0
7.6
2.7
4.5
2
1
1
•6
.2
-------
NATIONAL ANALYSTS
METAL FINISHING STUOY (815-21
QUESTION NO*10 WHICH OF THESE IS THE
SECOND MOST IMPORTANT REASON FOR DOING
METAL FINISHING IN-HOUSE?
TOTAL
TOTAL 1614
NO ANSWER 2^6
NUMBER ANSWERING 1368
100.0
NO JOB SHOPS IN THE AREA TO 84
SEND WORK TO 6*1
JOB SHOPS ARE NOT RESPONSIVE 235
TO OUR NEEDS 17.2
LESS EXPENSIVE TO DO IT 460
IN-HOUSE 33.6
WORK FLOW DOESN'T ALLOW INTER- 419
RUPTION OF WORK SENT OUT 30.6
ALWAYS HAVE DONE OUR METAL 168
FINISHING IN-HOUSE 12.3
OTHER REASONS 2
.1
- - - PERCENTAGE VALUE
LESS
THAN 1-3 4-6
1 PCT PCT PCT
254
400
270
35
52
35
219
348
235
100.0
100.0
100.0
15
26
18
6.8
7.5
7.7
48
59
31
21.9
17.0
13.2
83
122
76
37.9
35.1
32.3
43
108
72
19.6
31.0
30.6
30
33
37
13.7
9.S
15.7
1
.4
012
-TOTAL PLANT SALES-
MORE
10 CR UNDER SI MIL- $5 MIL- S10-30 THAN
MORE SI MIL 4.9 MIL 9*9 MIL MILLION S50 MIL
394
175
367
233
565
237
78
56
62
28
65
23
316
119
305
205
500
214
100.0
100.0
100.0
100.0
100.0
1O0.0
13
9
19
13
28
15
4.1
7.6
6.2
6.3
5.6
7.0
61
26
61
28
81
33
19.3
21.8
20.0
13.7
16.2
15.4
89
35
102
68
163
85
28*2
29*4
33.4
33*2
32.6
39.7
117
33
85
66
170
55
37.0
27.7
27.9
32*2
34.0
25.7
35
15
38
30
57
26
11.1
12.6
12.5
14.6
11.4
12.1
1
1
1
.3
• 8
.2
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY .(
4a9
~.»
4.9
9.1
75 PERCENT OR MORE
1MB
214
391
236
139
96.7
S7.0
B9.0
as.7
•7.7
AVERAGE
79.BB
70.26
7B.71
79.02
•2.27
-TOTAL PLANT SALtS-
MORE
10 OR UNDER SI MIL- *5 MIL— »10-50 THAN
MORE *1 MIL *.9 MIL 9.9 MIL MILLION *50 MU
394
175
367
233
555
237
•
3
9
7
5
6
366
172
358
226
560
231
100.0
100.0
100.0
100.0
100.0
100.0
30
32
14
7
21
9
r.a
14.6
3.9
3.1
).«
3.9
10
9
9
3
6
5
2.6
5.2
2.5
1.3
1.1
2.2
27
9
20
14
31
15
7.0
9*2
9«6
6.2
5.5
6.5
319
122
315
202
502
202
92.6
70.9
aa.o
89.4
89.6
• 7.4
71.97
51.95
79.60
•0.06
SO. 10
•0.13
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY (815-21
question no.u thinking about all of the
METAL FINISHING YOU DO IN-HOUSE* WHAT
PERCENT OF THAT WORK IS DONE WITH
PARTS SENT TO US FROM OTHER UNITS
the firm?
OF
TOTAL
LESS
THAN
1 PCT
PERCENTAGE
1-3
PCT
VALUE
4-6
PCT
ADDED -
7-9
PCT
1C OR
MORE
-TOTAL P
UNDER Si MIL-
»1 MIL 4.9 MIL
L A N T
S5 MIL-
9.9 MIL
sal
*10-50
MILLION
t S -
MOKE
THAN
450 MIL
TOTAL
161*
254
400
270
155
394
175
3b7
233
565
237
NO ANSWER
45
12
10
5
1
11
5
11
10
6
6
NUMBER ANSWERING
1569
100.0
242
100.0
390 265
100.0 100.0
154
100.0
383
100.0
170
100.0
356
100.0
223
100.0
559
100.0
231
100.0
LESS Than 25 PERCENT
1476
94*1
229
94.6
365
93.6
2S5
96.2
142
92.2
355
92.7
161
94.7
339
95.2
210
94.2
525
93.9
214
92.6
25 TO 49 PERCENT
46
2.9
5
2.1
9
2.3
6
2*3
10
6.5
13
3.4
3
l.a
7
2.0
11
4.9
19
3.4
5
2.2
50 TO 74 PERCENT
20
1.3
2
• a
10
2.6
1
.4
6
1.6
2
1.2
5
1.4
1
.4
7
1.3
5
2.2
75 PERCENT OR MORE
27
1.7
6
2.5
6
1.5
3
1.1
2
1.3
9
2.3
4
2.4
5
1.4
1
.4
8
1.4
7
3.0
AVERAGE
4.09
9.13
4.00
3.03
4.37
5.34
3.81
3.27
3.16
4.23
5.76
-------
national analysts
METAL FINISHING STUOY (815-21
QUESTION NO.11 THINKING ABOUT ALL OF THE
METAL FINISHING YOU 00 IN-HOUSE• -HAT
PERCENT OF THAT WORK IS DONE WITH
PARTS FROM OUTSIDE CUSTOMERS/VENOERSt
LESS
THAN
TOTAL 1 PCT
total
1614
254
NO ANSWER
46
12
NUMBER ANSWERING
1561
242
loo.o
100.0
LESS THAN 25 PERCENT
1425
219
90.9
90.5
25 TO 49 PERCENT
44
7
2.8
2*9
50 TO 74 PERCENT
51
10
3.3
4.1
75 PERCENT OR MORE
48
6
3.1
2.5
AVERAGE
6.14
5.45
015
'ERCENTAGE VALUE
AODED -
— —
1-3
4-6
7-9
10 OR
PCT
PCT
PCT
M3RE
400
270
155
394
10
5
1
11
390
265
154
313
100.0
100*0
100.0
100.0
Ml
240
145
337
94.4
90.6
94.2
aa.o
S
7
*
15
1.3
2.6
3.9
3.9
10
10
2
14
2.6
3.«
1.3
3.7
?
a
1
17
l.a
3.0
• 6
4.4
4.63
7.30
5.03
7.*8
-TOTAL PLANT S A L c S -
MORE
UNDER SI MIL- *5 MIL- S10-50 THAN
SI mil 4.9 MIL 9,9 MIL MILLION *50 MIL
175
367
2J3
565
237
5
11
10
6
7
170
356
223
559
230
100.0
UO.O
ioo.o
100.U
100.0
127
324
208
521
216
74.7
91.0
93.3
93.2
93.9
7
11
5
16
5
4.1
3*1
2.2
2.9
2*2
10
13
5
14
8
5.9
3.7
2.2
2.5
3.5
26
•
5
8
1
15.3
2.2
2.2
1.4
.4
12.96
>.89
5.43
5.02
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY (815-21
ouestion no.12 in the last three years.
WHAT WAS THE AVERAGE ANNUAL SALES OF ALL
GOODS PRODUCED AT THIS PLANTt
PERCENTAGE VALUE ADDED -TOTAL PLANT SALES-
TOTAL
LESS
THAN
1 PCT
1-3
PCT
4-6
PCT
7-9
PCT
10 OR
MORE
UNOER
SI MIL
SI MIL"
4.9 MIL
S5 MIL-
9.9 MIL
S10-50
MILLION
MORE
THAN
S50 MIL
TOTAL
1614
254
400
270
155
394
175
367
233
565
237
NO ANSWER
37
B
9
1
7
NUMBER ANSWERING
1577
100.0
246
100.0
391
100.0
270
lOO.O
154
100.0
387
100.0
175
100.0
367
100.0
233
100.0
565
100.0
237
100.0
UNDER SI*000*000
175
11.1
27
11.0
39
10.0
27
10.0
11
7.1
53
13.7
175
100.0
SI.000*000-*-999.999
367
23.3
36
14.6
96
24 .6
61
22*6
40
26.0
109
28.2
367
100,0
#5.000.000-9.999#999
233
i*.a
32
13.0
43
11.0
54
20.0
29
18.8
61
15.8
233
100.0
S10.000i000-30•000»000
565
35.a
101
41*1
152
38.9
98
36.3
53
34.4
121
31.3
565
100.0
more than sso»ooo»ooo
237
15.0
50
20.3
61
15.6
30
11.1
21
13.6
43
11.1
237
100.0
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY (815-21
QUEST ION NO.13 WHAT ARE THE AVERAGE
ANNUAL SALES Of THE WHOLE CORPORATION
OF WHICH YOU ARE A PART?
m m
LESS
THAN
TOTAL 1 PCT
TOTAL 161* 25*
NO ANSWER *1 *
NUMBER ANSWERIN6 1373 250
100.0 100.0
UNOER H. 000. 000 106 IS
6.7 6.0
Sl.000.000-4.999.999 227 23
1*.* 9.2
S5»0001000-9.999.999 126 19
8.0 7*6
»10.000.000-50»000»000 271 34
17.2 13.6
MORE THAN SSOtOOOtOOO 843 159
53.6 63.6
017
'ERCENTAGE VALUE
ADDED
- - -
-TO
T
ALP
LAN
T SAL
E S -
MORE
1-3
*-6
7-9
10 OR
UNDER
SI
NIL—
S5 MIL—
$10-50
THAN
PCT
PCT
PCT
MORE
SI MIL
*.
9 MIL
9.9 MIL
MILLtOri
*50 MIL
*00
270
155
39*
175
367
233
565
237
6
3
3
10
3
7
3
*
2
39*
267
152
38*
172
360
230
561
235
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
20
17
7
38
102
3
5.1
6.4
*.6
9.9
59.3
.8
51
35
22
82
26
193
*
1
1
12.9
13.1
1*.5
21.*
15.1
53.6
1.7
.2
.*
26
22
15
3*
9
37
7*
5
6.6
8.2
9.9
8.9
5.2
10.3
32.2
• 9
78
**
3*
63
1*
55
51
1**
*
19.8
16.5
22.*
16.*
8.1
15.3
22.2
25.7
1.7
219
1*9
7*
167
21
72
101
*11
230
55.6
55.8
*8.7
*3.5
12.2
20.0
*3.9
73.3
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY (819-21
QUESTION NO. 14 WHAT PERCENT OF ALL GOODS
PRODUCED AT THIS PLANT RECEIVES SOHE
METAL FINlSHlNGt
TOTAL
TOTAL 1*1*
NO ANSWER 42
NUMBER ANSWERING 1572
100.0
LESS THAN 25 PERCENT 292
18.6
25 to 49 percent lea
12.0
50 TO 74 PERCENT 219
13.9
75 PERCENT OR MORE *79
55.5
AVERAGE 54.17
PERCENTAGE VALUE
LESS
THAN 1-3 4-6
1 PCT PCT PCT
254
400
270
10
8
2
244
392
268
100,0
100.0
100.0
124
79
41
50.8
20.2
15.3
28
57
38
11.5
14.5
14.2
21
56
42
8.6
14.3
15.7
71
200
147
29.1
51.0
54.9
27.15
51.22
56.83
018
- -
-TOT
>
r
L A N T
SAL
E S -
MORE
10 OR
UNDER SI MIL-
S5 MIL-
$10-50
THAN
MORE
SI MIL 4
.9 MIL
<0
•
*
X
m—
r
MILLION
*50 MIL
394
175
367
233
565
237
4
6
8
2
10
7
390
169
359
231
555
230
100.0
100.0
100.0
100.0
100.0
100.0
14
50
53
41
90
53
3.6
29.6
14.8
17.7
16. i
23.0
37
13
51
25
65
30
9.5
7.7
14.2
10.8
11.7
13.0
59
20
56
29
64
27
15.1
11.8
15.6
12.6
15.1
11.7
280
06
1<»9
136
316
120
71.8
50.9
55 .4
58.9
56.9
52*2
69.37
43.53
57.73
56.59
56.5 i
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY (S15-2I
QUESTION NO.15 ON THE AVERAGE* FOR THE
PROOUCT S HADE AT YOUR PLANT HOW MUCH OF
TIC TOTAL COST TO MANUFACTURE A PROOUCT
IS DUE TO THE COST Of METAL FINISHING?
TOTAL
PERCENTAGE VALUE AODED
LESS
THAN
1 PCT
1-3
PCT
*-6
PCT
7-9
PCT
10 OR
MORE
-TOTAL PLANT SAl
UNDER SI MIL- SS MIL- *10-50
SI HIL *.* MIL 9*9 MIL MILLION
E S -
MOKfc
THAN
*50 MIL
TOTAL
1614
600
270
155
39*
175
367
233
565
237
NO ANSWER
23
6
3
2
*
3
number answering
1591
25*
*00
270
155
39*
169
36*
231
561
23*
100.0
100.0
100.0
100.0
100.0
100.0
100*0
100.0
100.0
100.0
100*0
less than i percent
25*
25*
27
36
32
101
50
16.0
100*0
16.0
9.9
13«9
16.0
21**
1 PERCENT TO 3 PERCENT
*00
*00
39
96
*3
152
61
25.1
100.0
23.1
26.6'
18.6
27.1
26*1
6 PERCENT TO 6 PERCENT
270
270
27
61
5*
98
30
17.0
100.0
16.0
16.8
23.*
17.5
12*8
7 PERCENT TO 9 PERCENT
155
155
11
*0
29
53
21
9.7
100*0
6.5
11*0
12*6
9.*
9*0
10 PERCENT OR MORE
19*
396
53
109
61
121
*3
26. •
100.0
31.*
29.9
26**
21.6
18 •*
DON'T KNOW
116
12
22
12
36
29
7.6
7.1
6.0
5.2
6.*
12.6
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY 1815-21
QUESTION NO.12.14.15 PLANT VALUE ADDED
LESS
THAN
TOTAL 1 PCT
TOTAL
1614
254
NO ANSWER
189
16
NUMJER ANSWERING
1425 230
100.0 100.0
LESS THAN *50#000
386
27.1
167
70.2
*50tU00 TO *99)999
154
10.8
20
e.4
*130.000 TO *499.999
363
25. 5
42
17.6
*500.000 TO *999*999
134
9.4
9
3«b
M.uOO.OOO TO S4.999.999
329
23.1
*5»000(000 OR MORE
59
4.1
AVERAGE I THOUSANDSI
34#
65
020
ERtENTAG
£. VALUE
ADDED -
- -
-TO
T A L P
L A N T
>
r
E i -
MORE
1-3
4-6
7-9
10 u:t
UNDER
SI MIL-
*5 MIL-
#10-50
THAN
PCT
PCT
PCT
MORE
SI MIL
4.9 MIL
9.9 MIL
MILLIUN
*50 MIL
400
270
155
394
175
36 7
233
565
237
16
2
3
11
20
31
16
49
36
304
266
152
383
155
336
217
516
201
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
144
46
16
11
110
133
50
58
25
37.5
17.9
10.5
2.9
71.0
i9.6
23.0
13.2
12.4
30
32
11
53
45
58
14
30
7
9.9
11.9
7.2
13.8
29.0
17.3
6.5
5.6
3*5
95
83
39
104
145
82
114
22
24.7
31.0
25.7
27.2
43.2
37*0
22«i
10.9
68
IS
20
19
34
74
26
17.7
6.7
13.2
5.0
15.7
14.3
12,.»
39
78
53
159
37
230
62
10.2
29.1
34.9
41.5
17.1
44.6
30.8
9
13
37
59
3*4
8«6
9.7
29.4
365
802
1478
2545
27
133
398
1356
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY (815-2>
QUESTION NO*l)i14*19 CORPORATE VALUE AOOEO
am m
LESS
THAN
TOTAL I PC?
TOTAL 1614 25*
NO ANSWER 190 13
NUMBER ANSWERING 1424 241
100*0 100.0
LESS THAN S50*000 255 130
17.9 53.9
850*000 TO 899*999 113 20
7.9 8*3
8100*000 TO #499*999 296 64
20*2 26*6
8500*000 TO *999*999 131 27
9.2 11*2
*1*000,000 TO St*999*999 402
28*2
65*030*000 OR MORE 235
16.5
AVERAGE J THOUSANDS) 2541 132
021
>ercentAge value
AOOEO -
m «•
1-3
4-6
7-9
10 OR
PCT
PCT
PCT
MORE
400
270
155
394
13
5
5
13
387
265
ISO
381
100.0
100.0
100.0
100.0
81
26
10
8
20*9
9.8
6.7
2.1
26
23
3
41
6.7
• •7
2.0
10.8
76
43
26
79
19.6
16,2
17.3
20.7
54
22
15
15
14.0
8.3
8.7
3*7
150
115
51
8*
38.8
43.4
>4,0
22.S
36
47
152
13.6
31.3
39.9
800
2046
3199
5919
-TOTAL PLANT SALES-
HOSE
UNDER SI MIL- S5 NIL- 810-50 THAN
SI MIL 4.9 MIL 9.9 MIL MILLION *50 MIL
175
367
233
565
237
21
37
19
51
38
154
330
214
514
199
100.0
100.0
100*0
100.0
100*0
79
76
30
42
25
51.3
23*0
14.0
8.2
12.6
40
45
8
12
6
26.0
13.6
3.7
2.3
3.0
15
120
43
86
22
9*7
36.4
20.1
16.7
11.1
4
22
26
50
26
2*6
6.7
12.1
9.7
13.1
13
48
73
294
62
8.4
14.5
34*1
39.7
31*2
3
19
34
120
58
1*9
5.8
15.9
23.3
29.1
455
1224
2649
3570
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY (81S-2I
QUESTION NO*16 DO YOU COMPILE OR RECEIVE
ON A KEGULAR BASIS A COST BREAKDOWN FOR
THE METAL FINISHING OPERATION?
- - -
PERCENTAGE VALUE
ADDED
- - -
-TO
T
ALP
LAN
T SAL
E S -
LESS
MORE
THAN
1-3
4-6
7-9
10 OR
UNDER
SI
MIL-
65 MIL—
S10-50
Than
TOTAL
1 PCT
PCT
PCT
PCT
MORE
SI HIL
4.
9 MIL
9.9 MIL
MILLION
650 MIL
TOTAL
1614
254
400
270
155
394
175
367
233
565
237
NO answer
IT
1
1
2
1
3
2
4
1
4
2
NUMBER ANSWERING
1597
253
399
266
154
391
173
363
232
561
235
100,0
100.0
190.0
100.0
100.0
100.0
100.0
100.0
1U0.0
100.0
100.0
YES. FOR JUST THIS PLANT
9ia
96
209
17U
105
276
86
2U6
146
333
126
57.2
38.7
52.4
63.4
68.2
70.6
49.7
56.7
62.9
59.4
53.6
YES» BUT INCLUDES THIS PLANT
69
7
14
8
10
21
5
13
5
24
14
PLUS OTHER LOCATIONS
3.9
2.8
3.5
3.0
6.5
5.4
2.9
3.6
2.2
4.3
6.0
N0» COSTS HANDLED ELSEWHERE
213
33
63
38
14
30
14
31
30
83
50
13.3
13.0
15.8
14.2
9.1
7.7
8.1
8.5
12.9
14.8
21.3
NO* COSTS NOT RECORDED
408
115
113
52
25
64
68
113
51
121
45
25.5
45.5
28*3
19.4
16.2
16.4
39.3
31*1
22.0
21*6
19.1
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY <815-21
QUESTION NO.17 IF RECpRDS ARE KEPT FOR
THE METAL FINISHING OPERATION* WHAT ITEMS
ARE ACCOUNTED FOR ON A REGULAR BASIST
mm w
LESS
Than
TOTAL 1 PCT
TOTAL 161* 254
NO ANSWER 121 91
NUMBER ANSWERING 1493 223
100.0 100.0
TOTAL WATER 63S 45
42.3 20.2
PROCESS WATER 401 94
26.9 13.2
AREA PLATED 274 19
18.4 I.3
JOBS PROCESSED 817 91
34.7 40.a
AMP HOURS 199 9
12.9 4.0
CHEMICAL USE 1096 122
70.7 34.7
FACTORY OVERHEAD 913 97
61.3 43.5
CIRECT LABOR llv7 146
•u.2 63.5
PERSJN HOURS *36 96
56.0 43.0
REVENUES GENERATED 2 83 15
19.0 6.7
HONE OF THE ABOVE ITEMS IS 202 5S
ACCOSTED FOR 13.5 26.0
023
PERCENTAGE VALUE
ADO ED
— - -
1-3
4-6
7-9
10 OR
PCT
PCT
PCT
MORE
400
270
135
31*
92
17
7
19
36a
233
148
373
100.0
100.0
100.0
100.0
131
113
81
217
33*6
44.7
34.7
57.9
•3
66
46
136
22.6
26.9
32.4
36.3
61
43
28
103
16.6
17.0
18.9
27.5
164
144
96
234
50.0
56.9
64.9
62.4
26
36
23
83
7.6
14.2
15.5
22.1
254
167
117
290
69.0
73.9
79.1
77.3
213
163
lU9
261
57.9
64.4
73.6
69.6
27a
222
132
320
75.5
67.7
69.2
85.3
195
147
95
236
53.0
58.1
64.2
63. i
43
36
35
134
11.7
14.2
23.6
35.7
63
22
11
30
17.1
6.7
7.4
a.o
-TOTAL PLANT SALES-
MURE
UNOER SI MIL- 35 MIL- S10-50 THAN
SI MIL 4.9 MIL 9.9 MIL MILLION 650 MIL
173
367
233
565
237
21
36
10
30
17
154
331
223
335
220
100.0
100.0
100*0
lOOaO
100.0
43
119
107
237
96
29.2
36.0
48*0
48.0
43*6
22
63
65
170
7S
14.3
19.0
29.1
31.6
34*1
19
61
44
100
43
12.3
18.4
19.7
16.7
»•»
64
166
132
301
1ST
41.6
50.2
39.2
56.3
62.3
IB
43
22
73
SO
11.7
13.6
9.9
13.6
13*6
61
204
161
412
177
32.6
61.6
72.2
77 *0
BOaS
72
192
131
340
144
46.8
58.0
67.7
63*6
65 a 5
103
247
183
451
192
66.9
74.6
•2.1
64.3
•7*3
76
169
117
321
137
49.4
51.1
52.5
60.0
62*3
43
85
41
71
40
27.9
25.7
18.4
13.3
18*2
*2
58
24
34
19
27.3
17.5
10*8
10.1
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY 1815-2)
QUESHON NO.18 IN 1976* WHAT WAS YOUR
TOTAL OPERATING BUDGET FOR DOING METAL
FINISHING AT YOUR PLANT?
LESS
THAN
TOTAL I PCT
TOTAL 1614 294
NO ANSWER 562 10*
NUMBER ANSWERING 1052 150
100.0 100.0
LESS THAN SlOOiOOO 391 101
37.2 67.3
*100.000 TO S499.999 383 40
36.4 26.7
$500,000 TO $999»999 125 5
11.9 3.3
*1.000.000 TO S4.999.999 121 3
11.5 2.0
*5.090.000 OR MORE 32 1
3.0 .7
AVERAGE 637 198
024
>ERCENTAGE VALUE
ADDED -
- -
-TO
T
ALP
L A N T
SAL
E S -
MOKE
1-3
4-6
7-9
10 OR
UNDER
SI
MIL-
S5 MIL—
•10-50
THAN
PCT
PCT
PCT
MORE
SI MIL
4.
9 MIL
9.9 MIL
MILL1UN
450 MIL
400
270
155
394
175
367
233
565
237
127
88
42
119
61
129
88
172
86
273
182
113
275
114
238
145
393
151
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
121
69
28
51
76
140
50
96
24
44.3
37.9
24.8
18.5
66.7
58.8
34.5
24.4
15.9
101
74
49
99
31
74
62
174
38
37.0
40.7
43.4
36.9
27.2
31*1
42.8
44.3
25.2
28
21
21
45
6
17
22
51
27
10.3
11.5
18.6
16.4
5.3
7.1
15.2
13*2
17.9
20
16
12
38
1
7
10
61
41
7.3
8.8
10.6
21.1
.9
2.9
6*9
15*5
27.2
3
2
3
22
1
10
21
1.1
1.1
2.7
8.0
.7
2*5
13.9
379
419
663
1265
111
194
381
686
-------
national analysts
METAL FINISHING 5TJOV <815-21
Que ST I OH NO. 19 ta'HAT IS YOUR 1976 BUDGET FOR
DIRECT LABORt
USS
THAN
TOTAL 1 PCT
TOTAL 1614 254
NO ANSWER 675 125
NUMBER ANSWERING 939 129
100.0 100.0
LESS THAN *20.000 140 4)
14.9 33.9
*20.000 TO 649'1999 1B9 39
20.1 30.2
SSOtOOO TO 899.999 172 21
IB.3 16.3
6100*000 TO 8499.999 337 21
35.9 16.3
$500,000 TO $999,999 52 4
5.5 3.1
*1t000*000 OR MORE 49 1
5.2 .a
AVERAGE (THOUSANDS) 269 90
025
PERCENTAGE value
A0OED
- - -
-TO
T
>
r
¦o
1 L A H
T SAL
fc S -
MOHt
1-3
4—6
7-9
10 OR
UNOER
SI
mil-
*5 NIL—
SI0-50
THAN
PCT
PCT
PCT
NQRE
$1 NIL
4.
9 NIL
9*9 MIL
MILLION
*50 NIL
400
270
155
394
175
367
233
565
237
156
118
49
139
81
176
112
186
93
244
152
106
255
94
191
121
379
144
100.0
100.0
lOO.O
loo.a
lOO.O
100.0
\00.0
100.0
100.0
56
29
4
9
31
46
14
42
6
23.0
13.2
3.8
J. i
33.0
24.1
11.6
11.1
4.2
63
33
16
31
25
62
31
55
12
25.8
21.7
15.1
12.2
26.6
H, 5
25.6
14.3
8.3
36
30
23
51
17
35
29
78
12
14.B
19.7
21.7
20.0
18.1
18*3
24.0
20.6
8.3
75
55
53
111
20
45
44
160
65
30.7
36.2
so.o
43.5
21.3
23.6
36.4
42.2
45.1
7
9
5
23
1
2
1
27
20
2.9
5.9
4.7
9.0
1.1
1.0
• 8
7.1
13.9
7
5
5
30
1
2
17
29
2.9
3.3
4.7
11.8
.5
1.7
4*5
20.1
161
224
309
487
65
82
151
248
-------
NATIONAL ANALYSTS
MCTAL FINISHING STUDY (819-21
QUESTION NO*19 WHAT IS YOUR 1976
chemical?
total
no answer
NUMBER ANSWERING
LESS THAN S20»000
S20.000 TO $49» 999
»50>U00 TO S99»999
$100,000 TO $499#999
S5Q0fOOO TO S999.999
11.000.000 OR MORE
AVERAGE (THOUSANDSI
026
BUDGET FOR
PERCENTAGE VALUE
LESS
THAN
1-3
4-6
TOTAL
1 PCT
PCT
PCT
1614
254
400
270
719
133
163
130
695
121
237
140
100. 0
100.0
100.0
100.0
281
7V
86
38
31.4
65*3
36.3
27.1
173
21
55
34
19.3
17.4
23.2
24.3
133
6
36
24
14.9
5.0
15.2
17.1
248
14
54
39
27.7
11.6
22.S
27.9
39
3
4
4.4
1.3
2.9
21
1
3
1
2.3
.B
1.3
.7
170
117
97
120
ADDED -
- -
-TO
T A L P
L A N T
SAL
t S -
MOKE
7-9
10 OR
UNDER
SI MIL-
*5 MIL—
$10-50
THAN
PCT
MORE
>1 MIL
4*9 MIL
9*9 MIL
MILLION
*50 MIL
155
39o
175
367
233
565
237
50
147
89
181
114
206
100
105
247
86
186
119
359
137
100.0
100.0
100.0
100.0
100.0
100.0
100.0
30
35
57
91
34
76
22
28.6
14.2
66.3
<>8.9
28*6
21.2
16.1
20
34
17
38
31
67
18
19.0
13.8
19.8
20.4
26.1
18.7
13.1
15
43
9
23
16
65
19
14.3
17.4
10.5
12.4
13.4
18.1
13.9
34
94
3
31
36
121
53
32.4
38.1
3.5
16.7
30. 3
33.7
38.7
4
27
3
1
23
12
3.8
10.9
1.6
.8
6.4
8.8
2
14
1
7
13
1.9
5.7
• 8
1.9
9.5
152
317
21
60
96
176
-------
national analysts
METAL FINISHING STUDY 1815-2)
QUESTION NO.19 WHAT IS YOUR 1976 BUDGET FOR
WATERY
TOTAL
LESS
THAN
1 PCT
PERCENTAGE VALUE
1-3 4-6
PCT PCT
ADDED
7-9
PCT
10 OR
MORE
-TO
UNDER
>1 MIL
T A 1. P
>1 M1L-
4.9 NIL
LAN
>5 MIL-
9.9 MIL
T SAL
>10-50
MILLION
e s -
MORE
THAN
>50 MIL
TOTAL
161*.
254
*00
270
159
394
175
367
233
565
237
NO ANSWER
922
iao
216
161
67
192
112
221
144
281
130
NUMBER ANSWERING
692
100.0
7*
100.0
164
100.0
109
100.0
88
1OO.0
202
lOO.O
63
lOO.O
146
100.0
89
100.0
284
lOO.O
107
10O.U
less Than >20*000
528
76.9
67
90. 5
148
•0.4
Sfl
•0.7
68
77.3
130
64.4
63
100.0
131
89.7
77
86.5
199
70.1
56
52*3
(20*000 TO >49*999
102
14.7
5
6.8
23
13.6
14
12.8
13
14.8
40
19.8
13
8.9
8
9.0
56
19.7
24
22.4
>90*000 TO >99*999
39
5.6
2
2.7
6
3.3
4
3.7
6
6*8
19
9.4
2
1.4
2
2.2
22
7.7
13
12.1
SlOOiOOO TO >499*999
17
2.5
2
1.1
J
2.8
11
5.4
1
1.1
7
2.5
9
8.4
>500*000 TO >999*999
4
• 6
2
1.1
1
1.1
1
•5
1
1.1
3
2.8
>1*000*000 OR MORE
2
• 3
1
.9
1
.5
2
1.9
AVERAGE 1THOUSANDS1
32
7
49
17
22
43
3
•
16
19
132
-------
NATIONAL ANALYSTS
METAL FINISHING STUOY (815-2)
QUEST ION NO.19 WHAT IS YOUR 1976 BUDGET FOR
ENERGY AMD UTILITIES?
- - -
PERCENTAGE VALUE
ADDED -
- -
-TO
T A L P
L A N T SAL
t S -
LESS
MORE
THAN
1-3
*-6
7-9
10 OR
UNDER
J1 MIL-
*5 MIL—
S10—50
THAN
TOTAL
1 PCT
PCT
PCT
PCT
MORE
SI MIL
*.9 MIL
9*9 MIL
MILLION
S50 MIL
total
161*
25*
*00
270
155
39*
175
367
233
565
237
NO ANSWER
862
171
209
151
59
170
97
205
132
270
125
NUMBER ANSWERING
752
83
191
119
96
224
78
162
101
295
112
100.0
1U0.0
loo.o
100.0
100.0
100.0
100.0
100.0
100.0
loo.o
100.0
LESS THAN S20.000
360
56
11*
56
35
82
63
109
*3
116
27
*7.9
67.5
59.7
*7.1
36.5
36.6
80.8
67.3
*2.6
39.3
2*.l
»20t000 TO S*9»99'9
153
16
30
29
28
39
13
27
33
So
21
20.9
19.3
19.7
2*.*
29.2
17.*
16.7
16.7
32*7
19.7
18.8
S50.00Q TQ *99(999
102
6
27
15
13
36
19
16
56
11
13.6
7.2
l*.l
12.6
13.5
16.i
11.7
15*8
19.0
9.8
S100.000 TO $*99.999
112
5
18
18
16
50
2
7
8
5*
*0
1A.9
6.0
9.*
15.1
16.7
22.3
2.6
4*3
7.9
18.3
35.7
*500.000 TO S999t999
1*
2
1
10
1
8
»
1.9
1.0
.8
*.5
1.0
2.7
*.5
41.000.000 OR MORE
11
4
7
3
8
1.5
*.2
3.1
1.0
7.1
AVERAGE 1 THOUSANDS)
90
2*
*1
5*
117
171
12
2*
*1
88
295
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY 1819-21
QUESTION NO*19 WHAT IS YOUR 1976 BUDGET FOR
OTHER ITEHS1
LESS
THAN,
TOTAL 1 PCT
TOTAL 1614 254
NO ANSWER 1070 197
NUMBER ANSWERING 544 57
100.0 100.0
LESS THAN $20*000 169 23
31.1 40.4
*20.000 TO 6+9*499 98 .16
18.0 26*1
650*000 TO 699*999 64 7
11*0 12*3
6100*000 TO 6499*999 141 9
25.9 15.6
6500*000 TO 6999*999 .40 1
7.4 1.8
61*000*000 OR MORE 32 1
3.9 1.0
AVERAGE (THOUSANDS! 272 77
029
PERCENTAGE VALUE ADDEO
l-J
4-6
7-9
PCT
PCT
per
400
270
i»»
256 176 95
144
94
60
100.0
100*0
100*0
55
30
11
98.2
31.9
28.3
27
16
9
18.8
17.0
15.0
21
13
6
14*6
13*8
10.0
30
27
19
20.6
28.7
31.7
6
6
4
4.2
6«4
6.7
i
. 2
5
3.5
2.1
8.3
174
161
312
10 Gft
MORE
-TO
UNOER
61 NIL
T
61
4.
ALP
MIL—
9 MIL
'LAN
65 MIL-
9.9 MIL
T SAL
610-50
MILLION
E S -
MOKE
THAN
650 MIL
39+
1J5
367
293
565
237
235
127
267
167
335
142
159
100.0
46
100*0
100
100.0
66
100.0
230
I oo.a
95
100.0
33
20.6
26
54*2
49
49*0
16
27.3
57
24.8
17
17.9
24
15.1
9
16.8
17
17*0
11
16*7
47
20*4
14
14.7
15
9.4
6
12*5
10
10*0
8
12*1
33
14.3
7
7*4
49
30.8
7
14.6
19
19.0
12
33.3
61
26.5
29
30.5
20
12.6
4
4.0
4
6*1
16
7*6
14
14.7
16
11.3
I
1.0
3
4*5
14
6*1
14
14.7
497
54
90
192
290
-------
MAT I Oft A L ANALYSTS
METAL FINISHING STUOY (615-2)
QUESTION NO*20 ON A TYPICAL DAY IN 1976
MOd MUCH WATER DID YOUR TOTAL PLANT USE?
- - _
PERCENTAGE VALUE
ADDED -
- -
-TO
T A L P
L A N T
SAL
t 5 —
LESS
MURE
THAN
1-3
4-6
7-9
10 OR
UNDER
SI M1L-
S5 MIL-
S10-50
THAN
TOTAL
1 PCT
PCT
PCT
PCT
MORE
SI MIL
4.9 MIL
9.9 MIL
MILLION
*
V
c
2
r
total
1614
254
400
270
155
394
175
367
233
565
237
NO ANSWER
441
67
107
82
41
90
76
148
71
101
26
NUMBER ANSWERING
1173
187
293
188
114
304
99
219
162
464
211
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
1OO.0
100.0
LESS THAN 2*000 GALLONS
82
17
19
13
7
21
31
27
10
10
2
7.0
9.1
6.5
6.9
6.1
6.9
31.3
12.3
6.2
2.2
.9
2>000 TO 9.999
124
21
33
25
7
33
25
65
9
20
3
10.6
11.2
11.3
13.3
6.1
10.9
25.3
29.7
5*6
4.3
1.4
10.000 tO 49(999
254
3B
58
39
25
74
23
81
53
82.
13
21.7
20.3
19.8
20.7
21.9
24.3
23.2
37.0
32.7
17.7
6.2
50.000 TO 99.999
152
27
42
27
23
24
6
22
27
79
16
13.0
14.4
14.3
14.4
20*2
7.9
6.1
o
•
©
16.7
17.0
7.6
IOC.000 TO 499.999
357
49
89
56
34
105
12
18
53
206
61
30.4
26.2
30.4
29.8
29.8
34.5
12.1
8.2
32.7
44.4
28.9
500.000 GALLONS OR MOftE
204
35
52
28
18
47
2
6
10
67
116
17.4
'8.7
17.7
14.9
15.8
15.5
2.0
2.7
6.2
14.4
55.0
AVERAGE (THOUSANDS)
BOB
787
691
288
1500
917
241
205
494
823
1950
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY (81S-2I
OUESTlON NO*20 ON A TYPICAL OAY IN 1976
MOW MUCH WATER 010 YOUR METAL FINISHING
PROCESS USE*
LESS
THAN
TOTAL 1 PCT
TOTAL 161* 254
NO ANSWER 4*9 95
NUMBER ANSWERING 1125 159
100.0 100.0
LESS THAN 2*000 GALLONS 1*6 55
16.7 34.6
2*000 TO 9*999 198 33
17*6 20.8
10*000 TO 49*999 305 37
27.1 23.3
50,060 TO 99.999 138 1»
12.3 11.3
100.000 TO *99*999 239 13
21.2 8.2
530*000 GALLONS OR MORE 57 3
5.1 1*9
AVERAGE (THOUSANDt 277 50
031
PERCENTAGE VALUE
AOOEP
- - -
-TO
T
ALP
LAN
T SAL
t S -
HOKE
1-3
*-6
7-9
10 OR
UNDER
SI
MIL—
65 MIL-
*10-50
THAN
PCT
PCT
PCT
MORE
SI MIL
4*
9 MIL
9*9 MIL
MILLION
SSO MIL
*00
270
155
394
175
367
233
565
237
121
82
37
97
81
150
75
116
48
279
188
118
297
94
217
158
449
189
100.0
10O.0
100.0
100.0
100.0
100.0
100*0
100.0
100.0
*9
32
14
30
41
59
23
50
11
17.6
17.0
11.9
10.1
43*6
27.2
14*6
11*1
»«S
5*
31
19
47
22
67
32
59
17
19.4
16.5
16*1
15*8
23*4
30.9
20*3
13.1
9.0
90
5*
30
67
24
55
49
137
36
32.3
28.7
25.4
22.6
25*5
25*3
31*0
30.5
19.0
27
20
19
44
3
23
26
62
20
9.7
10.6
16.1
14.8
3*2
10.6
16*5
13.8
10.6
4#
45
25
87
3
7
27
124
76
17.2
23*9
21*2
29.3
3*2
3.2
17.1
27*2
40*2
11
6
11
22
1
6
1
19
29
3.9
3.2
9*3
7.4
1*1
2*8
*6
4.2
15*3
162
78
423
621
30
118
339
358
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY (815-21
QUESTION NO.20 ON A TYPICAL DAY IN 1976
HOW MUCH WATER DID YOUR OTHtR PRODUCTION
PROCESS USE?
- PERCENTAGE VALUE
LESS
Than 1-3 <.-6
TOTAL 1 PCT PCT PCT
TOTAL
1614
254
400
270
NO ANSWER
572
100
143
98
NUMBER ANSWERING
1042
154
257
172
100.0
100.0
100.0
100.0
LESS THAN 2*000 GALLONS
36a
56
86
63
35.3
36.4
33.5
36.6
2*000 TO 9*999
127
16
34
23
12.2
10.4
13.2
13.4
10,000 TO 49*999
211
34
45
34
20*2
22.1
17.5
19.8
90*000 TO 99*999
96
14
29
17
9.2
9.1
11.3
9.9
100*000 TO 499*999
1B1
23
45
25
17.4
14.9
17.5
14.5
500*000 GALLONS OR MORE
59
11
18
10
5.7
7.1
7*0
5.8
AVERAGE CTHOUSANDS1
384
4*6
486
124
032
ADDED -
- -
-TO
T
ALP
L A N T
sal
E S -
MOKE
7-9
10 OR
UNDER
>1
MIL-
85 MIL-
*10-50
THAN
PCT
MORE
SI MIL
4.
9 MIL
9.9 MIL
MILLION
150 MIL
155
394
175
367
233
565
237
45
120
86
176
88
147
52
110
274
89
191
145
418
185
100.0
100.0
100.0
100.0
100.0
100.0
100.0
39
98
67
99
52
112
29
35.5
35.8
75.3
51.8
35.9
26.8
15.7
13
34
10
55
21
36
5
11.8
12.4
11*2
28.8
14.5
8*6
2*7
20
65
7
23
41
108
31
1ft.2
23.7
7.9
12*0
28.3
25.8
16.8
9
18
3
8
14
57
14
8.2
6.6
3.4
4*2
9.7
13.6
7*6
20
51
2
4
16
88
69
is.2
18.6
2.2
2.1
11.0
21.1
37.3
9
8
2
1
17
37
8.2
2.9
1.0
• 7
4.1
20*0
1214
147
9
99
67
363
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY 1815-21
QUESTION NO.21 WHERE DOES YOUR METAL
FINISHING DISCHARGE WATER GOt
TOTAL
TOTAL
1614
LESS
THAN
I PCT
254
NO ANSWER
12
12
NUMBER ANSWERING
1502
100.0
242
100.0
MUNICIPAL SEWER SYSTEM
955
60*4
156
64*5
RIVER* LAKE) POND» OTHER
SURFACE WATER
250
15. a
40
16.5
aOTH OF THE ABOVE
78
4.9
t
2.5
HOLDING TANKS
174
11.0
24
9.9
MUNICIPAL SEWER SYSTEM AND
HOLDING TANK
98
6.2
15
6.2
NATURAL SURFACE WATER AND
HOLDING TANK
23
1.5
CHEMICAL TREATMENT PLANT
1
.1
COMBINED MUNICIPAL. NATURAL.
AND HOLDING
3
.2
0)9
>ERCENTAGE value
ADDED
— — —
1-3
4-6
7r9
10 OR
PCT
PCT
PCT
MORE
400
270
155
394
5
3
~
4
395
267
151
390
100.0
100.0
100.0
100.0
230
169
90
225
56.2
63.3
59.6
57.7
62
34
21
64
15.7
12.7
13.9
16.4
21
10
11
24
5.3
3.7
7.3
6.2
42
36
18
47
10.6
13.5
11.9
12.1
30
12
8
24
7.6
4.5
5.3
6.2
7
6
3
6
1.8
2.2
2.0
1.5
1
.9
-TOTAL plant SALES-
MORE
UNDER SI MIL- *5 MIL- S10-50 THAN
SI MIL 4.9 MIL 9.9 MIL MILLION S50 MIL
175
367
233
565
237
1
8
7
9
3
174
359
226
556
234
100.0
100.0
100.0
100.0
100.0
115
223
136
339
123
66.1
62.1
60.4
61.0
52.6
22
40
37
93
54
12.6
11*1
16.4
lb.7
23.1
3
16
10
30
16
1.7
4*5
4.4
5*4
6*8
26
43
22
54
25
14.9
12.0
9.7
9.7
10.7
5
27
17
31
15
2.9
7.5
7.5
5.6
6.4
3
10
3
7
1.7
2.8
1.3
1.3
1
• 4
2
5
i
• 4
1
-------
NAT IUNAL ANALYSTS
METAL FINISHING STUDY 1815-2)
QUCST ION NO.22 00 YOU TREAT THE EFFLUENT
rROM YOUR METAL F HUSHING
OPERATIONS AT
T-1 mil
4.9 MIL
9.9 MIL
MILLION
»50 MIL
TOTAL
161*
254
400
270
155
394
175
367
233
565
237
NO ANSWER
33
10
7
5
2
4
6
11
4
5
3
NUMBER ANSWERING
1561
244
393
265
153
390
169
356
229
560
234
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
YES
941
116
216
149
101
261
70
189
130
355
172
59.5
47.5
55.0
56.2
66.0
66.9
41.4
53.1
56*a
63.4
73.5
NO
640
126
177
116
52
129
99
167
99
205
b£
40.5
52.5
45.0
43.8
34.0
33.1
58.6
46.9
43.2
36.6
26.5
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY (1)13-21
QUESTION NO.23 (IF EFFLUENT IS TREATED*
0*22> HOW MUCH HAVE YOU SPENT TO BUY ALL
OF YOUR WATER POLLUTION CONTROL EQUIPMENT
AT THIS PLANTT
LESS
THAN
TOTAL I PCT
TOTAL 941 116
NO ANSWER 7 2
NUMBER ANSWERING 934 111
100.0 100*0
UNDER *100.000 *63 66
49.6 57.9
Sl00*000-S249t99« 214 10
22.9 1S.I
*250*000-S499i999 122 9
13.1 7.9
S500«00-S1»090*000 71 8
7*6 7*0
morc than si*000.000 64 13
6.9 11.4
OSS
•EftCENTAGE VALUE
ADDED
- - -
-TO
T A L P
L A N T
SAL
e s -
MORE
1-3
4-6
7-9
10 OR
UNDER
SI NIL-
*5 MIL-
*10-50
THAN
PCT
PCT
PCT
MORE
SI MIL
4*9 MIL
9*9 MIL
MILLION
*50 MIL
216
149
101
261
70
189
130
355
172
1
3
1
1
2
2
216
146
101
258
69
188
128
355
170
100.0
100*0
100*0
100.0
100.0
100.0
100.0
100*0
100.0
109
79
47
114
39
135
73
151
34
50*5
53*4
46.5
44.2
85.5
71*8
57.0
42*5
20*0
57
32
21
67
5
43
30
95
33
26.4
21.6
20.a
26.0
7.2
22.9
23.4
26*8
19.4
23
24
16
as
4
9
18
63
25
10.6
16.2
19*0
14.7
5.8
^80
l*.l
17.7
1«.7
14
•
12
21
5
41
25
6*3
5.4
11*9
a.i
3.9
11*5
14.7
13
5
5
18
1
1
2
5
53
6*0
3*4
5.0
7.0
1.4
*5
1*6
1.4
-------
NATIONAL ANALYSTS
MFTAL FINISHING STUDY (815-2>
QUESTION NO.2* HOW MUCH OF THIS TOTAL
CAPITAL INVESTMENT REPRESENTS
THE COST
OF TREATING METAL FINISHING WASTES?
- - -
PERCENTAGE VALUE
AOOEO
- - -
-TO
T A L P
LAN?
SAL
t S -
LESS
HUME
THAN
1-3
4-6
7-9
10 OR
UNDER
SI mil-
MIL—
S10-50
THAN
TOTAL
1 PCT
PCT
PCT
PCT
MORE
»1 MIL
4.9 MIL
9.9 MIL
MILLION
SSO MIL
TOTAL
941
116
216
149
101
261
70
189
130
355
172
NO ANSWER
22
6
3
2
2
5
5
5
4
2
5
NUMBER ANSWERING
919
110
213
147
99
256
65
184
126
353
167
100.0
100.0
100.0
100.0
100.0
100.0
100.0
uo.o
100.0
100.0
100.0
ICO PERCENT-ALL OF IT
486
29
99
89
57
164
32
106
83
190
61
52.9
26.4
46.5
60.5
57.6
64.1
49.2
57.6
65.9
53.8
36.5
75 PERCENT-MOST pF IT
155
12
40
25
23
37
7
14
10
74
47
16.9
10.9
16.8
17.0
23.2
14.5
10.8
7.6
7.9
21.0
28.1
50 PERCENT-ABOUT HALF
75
8
24
9
7
15
7
15
8
20
22
0.2
7.3
11.3
6.1
7.1
S .9
10.8
8.2
6.3
5.7
13*2
25 PERCENT-LITTLE
178
50
46
20
11
38
16
43
22
62
32
19.4
45*5
21.6
13.6
11.1
14.8
24.6
23.4
17*5
17.6
19.2
0 PERCENT-NONE
25
11
4
4
1
2
3
6
3
1
5
2.7
10.0
1.9
2.7
1.0
.8
4.6
3.3
2.4
2.0
3.0
-------
NATIONAL ANALYSTS
METAL FINISHING STUOY ((115-2»
QUEST 10* MO.25 WHICH OF THESE ISSUES OF
COST AND PRODUCTION WOULD BE THE THREE
MOST IMPORTANT IN INFLUENCING
YOUR PLANT
•S
OCCISION TO INVEST IN A WATER
POLLUTION
CONTROL SYSTEM?
- — -
PERCENTAGE value
ADDED
— - -
-TO
T
A L P
LAN
T S A L
E S -
LESS
MORc
THAN
1-3
4-6
7-9
10 OR
UNDER
SI
MIL—
S5 MIL—
*10-50
THAN
TOTAL
1 PCT
PCT
PCT
PCT
MORE
SI MIL
4.
9 MIL
9.9 MIL
MILLION
*50 MIL
TOTAL
1614
254
4O0
270
155
394
175
367
233
565
237
NO ANSWER
so
20
21
12
1
15
15
25
13
15
5
NUMBER ANSWERING
1534
234
379
258
154
379
160
342
220
550
232
100.0
100.o
100.0
iou.o
1U0.0
IOU.O
100.0
luO.0
1U0.0
loo.o
100.0
SIZE OF REQUIRED INVESTMENT
1161
176
277
190
121
297
127
263
176
417
155
75.7
76.1
73.1
73.6
78.6
78.4
79.4
76.9
80*0
75.8
66.8
POTENTIAL COST IMPACT OF THE
921
126
227
166
B9
98
22J
132
329
121
investment
40.0
53.6
59*9
64*3
57.8
64.6
61*3
65*2
60*0
59.8
54.7
FEASIBILITY OF CHANGING
469
02
124
81
50
92
44
96
57
162
80
FINISHING PROCESSES
90.6
35.0
32.7
31.4
32.5
24.3
27.5
28.1
25.9
33.1
34.5
FEASIBILITY OF SENDING OUT
420
92
124
66
40
68
50
104
66
142
49
METAL FINISHING
27.4
39.3
32.7
25. 6
26.0
17.9
31*3
30.4
30.9
25.8
21.1
DECIDING ON WHAT SYSTEM TO
758
94
164
134
75
203
62
154
107
291
126
INSTALL
49.4
40.2
48.5
51.9
48.7
53.6
38*8
45.0
48*6
52.9
54.3
DECIDING HOW AND WHEN TO
436
57
98
74
39
124
42
78
55
148
103
INSTALL THE SYSTEM
28.4
24.4
25.9
28.7
25.3
32.7
26*3
22*8
25*0
26.V
44.4
RELOCATING METAL FINISHING
119
20
27
18
16
26
18
26
22
38
12
OPERATIONS
7.S
8.5
7.1
7.0
10.4
6.9
11.3
7.6
10.0
6.9
5.2
changing from or tc a munic-
229
42
65
32
22
S5
27
45
30
84
39
P4L SEWER SYSTEM
14.9
17.9
17.2
12.4
14.3
14.5
16.9
13.2
13*6
15.3
16*8
OTftCR ISSUES
11
1
2
1
6
1
3
3
1
3
.7
.4
.5
.4
1.6
• 6
.9
1*4
.2
1.3
-------
NATIONAL ANALYSTS
METAL FINISHING STUDY (815-21
QUESTION M0.26 IF YOU HAVE NOT PARTICIPATED
IN PLANNING MEETINGS FOR POLLUTION CONTROL
AND/OR YOUR PLANT DOES NOT HAVE WATER
POLLUTION CONTROLS* WHAT REASONS WOULD
ACCOUNT FOR THIS?
TOTAL
LESS
THAN
1 PC T
PERCENTAGE VALl
1-3 4-6
PCT PCT
TOTAL
1614
254
400
270
NO ANSWER
921
116
216
161
number ANSWERING
693
100. 0
138
1O0.0
184
100.0
109
10 0.0
OTHER PEOPLE ARE RESPONSIBLE
F03 IT
80
11. 5
15
10.9
22
12.0
12
11.0
IT IS NOT CONSIDERED A PROBLEM
416
60*0
-4
* *-
• ©
O \*
122
66.3
65
59.6
POLLUTION CONTROL PLANNING IS
LOW PRIORITY
71
10.2
13
9.4
17
9.2
12
11.0
PRESCMT PLANNING OF PROCEDURES
HAVE COMPLIED# HAVE FACILITIES
121
17.5
15
10.9
22
12.0
23
21.1
WAITING F03 PENDING GOVERN-
MENTAL REGULATIONS
32
4.6
2
1.4
10
5.4
3
2.8
OTHER REASONS
IV
2.7
2
1.4
9
1.6
1
.9
03a
ADDED -
- -
-TO
T
A L P
L A N T
SAL
E S -
MORE
7-9
10 OR
UNDER
SI
MIL—
S5 MIL-
*10-50
THAN
PCT
MORE
SI rfIL
4.
9 MIL
9.9 MIL
MILLION
i50 MIL
155
394
175
367
233
565
237
91
247
62
174
122
361
177
64
147
113
193
111
204
60
100.0
100. 0
100.0
loo.o
100.0
1O0.0
100.0
7
15
13
19
16
17
12
10.9
10.2
11.5
9.8
14.4
8*3
20*0
35
65
83
128
61
114
23
54.7
44.2
73.5
66*3
55.0
55*9
38.3
7
17
8
22
13
20
6
10.9
ll.6
7.1
11.4
11*7
9.8
10.O
16
36
9
17
27
50
15
25.0
24.5
8.0
a.a
24.3
24.5
25.0
3
13
1
10
3
11
7
4.7
8.8
.9
5.2
2.7
5.4
11.7
3
8
4
8
1
6
4.7
5.4
3.5
4.1
.9
2.9
-------
NATIONAL ANALYSIS
METAL FINISHING STUDY <815-21
QUESTION NO.2? HOW MUCH WILL YOUR PLANT
SPEND ON POLLUTION CONTROL EQUIPMENT
DURING The NCxT 2 YEARS?
LESS
Than
TOTAL 1 PCT
TOTAL 161* 25*
NO ANSWER 39* 52
NUMBER ANSWERIN6 1280 202
100*0 100*0
LESS THAN S10*000 997 84
91.0 41.&
•10*000 TO »49#999 977 55
29.5 27.2
850*000 TO S99»999 187 22
14.6 10.9
•100.000 TO *49>.999 250 91
19.5 15.3
•500.000 OR MORE 69 10
5.* 5.0
AVERAGE I THOUSANDS! 19B 187
039
•ERCENTAItE VALUE
ADDED
- - -
-TO
>
r
L A N T
SAL
E S -
MORE
1-3
4-6
7-9
10 OR
UNDEK
$1 MIL-
• 5 MIL—
•10-50
THAN
PCT
PCT
PCT
MORc
>1 MIL
4.9 MIL
9.9 MIL
MILLIuM
*50 MIL
400
270
155
994
175
367
233
565
237
91
41
90
85
59
104
42
39
24
309
229
125
909
116
263
191
47b
213
100.0
100.0
100.0
100.0
100.0
100*0
100*0
1U0.0
loO.O
116
69
92
70
70
130
61
110
25
97.S
27.5
25.6
22.7
60.9
49.4
31*9
23.1
11.7
05
77
96
99
32
82
61
160
95
27.5
93.6
28.8
92.0
27.6
il.2
31.9
33.6
16*4
97
40
22
50
7
28
26
69
95
12.0
17.5
17.6
16.2
6.0
10.6
13.6
18.7
16.4
56
98
29
74
5
21
39
9«
77
18.1
16.6
29.2
29.9
4.3
8.0
20.4
20.6
36*2
15
11
6
16
2
2
4
19
41
4.9
4.8
4.8
5.2
1.7
.8
2.1
4*0
19*2
116
125
169
108
37
30
107
105
-------
NATIONAL ANALYSTS
METAL FINISHING STUOY 1815-21
QUESTION N0.27 HOW MUCH MILL YOUR PLANT
SPEND ON POLLUTION CONTROL EQUIPMENT
OURINO THE NEXT 5 YEARS?
- - -
PERCENTAGE VALUE
AOOEO -
- -
-TO
T
A L P
LAN
T SAL
E S -
LESS
MOKE
THAN
1-3
4-6
7-9
10 OR
UNDER
SI
MIL-
S5 MIL—
810-50
THAN
TOTAL
1 PCT
PCT
PCT
PCT
MORE
SI MIL
4.
9 MIL
9.9 MIL
MILL]On
*50 MIL
TOTAL
1614
254
400
270
155
394
175
367
233
565
237
NO ANSWER
455
72
113
65
42
114
74
134
76
10C>
38
NUMBER ANSWER INC
1159
182
287
205
113
280
101
229
157
459
19V
100.0
100.0
100.0
100.0
100.0
100.0
100.0
loo.o
luO.O
100.0
100.0
LESS THAN 810(000
244
60
69
40
18
33
47
77
37
611
15
21.1
39(0
24.0
19.5
15(9
11.8
46(5
J3.6
23.6
14.8
7.5
tld.000 TO S49t999
220
40
60
51
16
42
27
63
27
09
13
19.0
22.0
20.9
24.9
14.2
15.0
26 ( 7
27.5
17.2
19.4
6.5
850(000 TO 899(999
183
23
43
30
23
51
13
36
32
79
22
is.a
12(6
15(0
14.6
20.4
18.2
12*9
15.7
20.4
17.2
11.1
9100(000 TO $%99«999
355
40
79
61
36
110
10
49
51
16<2
76
30.6
22(0
27.5
29.a
31(9
39.3
9(9
21.4
32(5
35. J
38.2
>500*000 OR MORE
157
19
36
23
20
44
M
4
10
61
73
13.5
10(4
12(5
11(2
17.7
15.7
4.0
1.7
6(4
13. 3
36. r
AVERAGE (THOUSANDS)
293
336
273
271
332
264
82
66
209
204
923
-------
-------
SAMPLE DESIGN AND SURVEY ISSUES
INTRODUCTION
Executing a successful mail survey of the job shop
sector of the metalfinishing sector required careful pre-
planning. No matter how well conceived, in practice every
survey must confront and satisfy several critical questions
in order to accept the results as valid. The questions are
these:
Is the basic sampling frame sound, e.g., free from
systematic sample selection bias?
Was a sound procedure employed to account for
non-respondents in order to assess the general
representativeness of the findings?
Do the response rates and data patterns permit
extrapolation of sample results to the population?
The purpose of this appendix is to present all the analytic
steps taken to satisfy these key questions.
1. A FIXED INTERVAL, RANDOM SELECTION DESIGN WAS
USED TO IDENTIFY THE SAMPLE: TWO-MAILINGS PLUS
FOLLOW-UP PHONE CALLS WERE MADE
The approach taken in this survey was a mail question-
naire followed by a follow-up telephone interview to a sample
of establishments not responding to the mail phase. A mail,
rather than a telephone or personal survey, was planned be-
cause of the nature of the data elements sought in the in-
quiry. We needed detailed and comprehensive information re-
garding production line configurations, water usage, employ-
ment statistics, and financial data. Such figures are not
-------
normally readily accessible in an interview situation and
often require review and consultation with others. The mail
approach affords respondents an opportunity to search out
and to consider thoughtfully their written replies. Pre-
vious studies among members of this industry have shown the
respondents can and do answer even the most detailed and
searching questions in a mail survey. The telephone follow-
up with non-respondents was included as an essential second
step to determine whether or not these establishments differed
along key parameters from those responding to the mail survey.
If the non-respondents could be shown to be no different from
respondents, then it would be reasonable to generalize the
survey data to all independent metalfinishing establishments.
If systematic differences were found between first and second
mail-backs, or between all mail respondents and telephone re-
spondents, then a means of weighting mail results to reflect
population parameters is needed.
(1) The Dun's Market Identifiers File Defined the
Metalfinishing Universe to be Sampled
Firms providing electroplating and metalfinishing
services are listed in SIC (Standard Industrial Classifi-
cations of the Department of Commerce) 3471 and 3479,
Therefore, the universe under investigation in the study
was defined as all firms listed in the two SIC's that
currently perform those manufacturing processes covered
by the regulations.
-------
The most recent and complete listing of such firms
available to us at the start of the study was the Dun's
Market Identifiers File (DMI) purchased by the U.S.
EPA from Dun and Bradstreet. Contained in the DMI were
5,551 names of organizations whose primary SIC is either
3471 or 3479.
This listing of 5r551 was ordered first by the size
of the company (using number of employees) and then alpha-
betically by state within size category.
A survey design was employed that systematically
sampled from the universe using a fixed interval and a
random starting point. By employing a 2.5 interval and
going through the list, a sample universe of 2,221 estab-
lishments was derived. An additional 70 firm names were
provided us by the Agency for inclusion in the sample.
They were included because they provided data previously
and effects over time could prove interesting.
(2) Great Care Went Into the Development of the Data
Gathering Instrument
Prior analyses, client discussions, and coordina-
tion with the metalfinishing industry reinforced our
understanding of how much information was needed for
systematic economic impact analysis. The data would
-------
have to be gathered via the mail. The instrument had
to be a convenient self-administered questionnaire.
To this end, we did the following:
Solicited descriptors of technical and pro-
duction variables from the technical con-
tractor. In this way, data would be gathered
from which pollution control costs could be
developed.
Provided drafts of the instrument to the
industry's association, the NAMF (National
Association of Metal Finishers). Their com-
ments contributed directly to the form, con-
tent, and length of the final instrument.
Reviewed the early drafts with our sampling
survey division, National Analysts. Their
contribution went far beyond the duties of
administering, coding, and scoring the re-
turns. On early drafts, they reviewed
critically the language, format, and lucid-
ity of all items.
Prior to the first mailing subsample, the
instrument was tested on a subsample of 12
firms located in New Jersey. This effort
was conducted to ensure that directions were
self-explanatory, items clear, and data ob-
tainable. Valuable information was gathered
by sitting with a respondent and "walking him
through" all items. Several changes in the
instrument's form and length were made as a
result of this pre-test.
By this point, the instrument had gone through six
drafts. It represented the most extensive, clear, de-
tailed, and balanced questionnaire we were able (at the
time) to create.
-------
(3) Two Separate Mailings Were Made
At the end of this development phase the final
instrument was 14 pages long (see Appendix A) and
covered the topics of:
Production activities
Market conditions
Technical operations
Financial conditions
Treatment requirements
Investment options
In October, all 2,221 establishments plus 40 of the
70 EPA firms were mailed a questionnaire with cover
letters from both the NAMF and the Agency. A postage
paid return envelope was enclosed. Replies were moni-
tored as received by National Analysts and when the re-
sponse levels diminished to fewer than two to three a
day, a second mailing went out to the non-respondents.
Again, a cover letter and a return envelope accompanied
each questionniare.
(4) Telephone Interviews Were Conducted With a
Sub-Set of Mail Non-Respondents
By the end of the mail phase, more than 1,400 firms
identified for the sample had not responded. To identify
as much as possible about these non-respondents, it was
decided to telephone and interview some of them directly.
-------
First, a shorter version of the mail instrument
was devised for use as a telephone protocol. Not only
was some language changed to make the questions more
conversational, but many production and financial items
were omitted for the sake of a limited (10-15 minute)
interview.
At the time, the subsample of non-respondents was
to be selected, 150 sample firms were known to be inactive
(e.g., mail returned as undeliverable, notes written on
questionnaires stating firm no longer in business, and
the like). In addition, not all active organizations
were subject to regulation and, therefore, not eligible
to complete a questionnaire. Of those returning a
questionnaire, only 68% were engaged in work involving
regulated processes. Moreover, this eligibility rate
varied by size of company*
Because of this differential eligibility, it was
decided that the subsample for follow-up should be
selected in such a way as to yield a specified number
of eligible firms within each size category.
-------
Operationally, the following seven steps were
executed:
Eight strata of company size were established
(7 groupings based on known employment and 1
in which the number of employees was unknown)
and the number of mailouts in the original
sample determined.
The number of firms in each stratum was ad-
justed proportionately by the 150 known to be
out of business. This reduced the total
sample universe of 2,221 to an eligible universe
of 2,071.
The percentage of eligible returns within each
stratum was calculated on the base of active
firms only.
The projected size of each stratum was derived
by multiplying the number of eligible firms
within each stratum by the eligibility rate
for the stratum. This stratum size estimate
was then divided by the sum of all strata
(1,345) to yield the relative size of a
stratum (as a %).
The total number of eligible firms to be con-
tacted in a sample of 600 was computed using the
computed relative size of each stratum. This
yielded a proportionate eligible sample of
follow-ups based on patterns of mail respondents.
The difference between the total eligible firms
(613) to be contacted and the number of eligible
returns from the mail phase (419) was deter-
mined for each stratum. This figure was then
multiplied by the eligibility rate for the
stratum to identify the total number of non-
respondents to be drawn for telephone follow-up.
A systematic sample with random start was taken
for each stratum to select the non-respondents.
-------
These steps are summarized in Tables D-l and D-2, on
the following pages. The number of telephone contacts
was targeted at 326; when the sample was drawn, 332
firms were included due to rounding in the selection process.
3. RESULTS OP THE TELEPHONE FOLLOW-UP SURVEY
PRECIPITATED EXTENSIVE REVIEW OF SURVEY"RESPONSES
Expecting that the smaller establishments were of primary
importance to the economic impact study, they were oversampled
in the telephone follow-up survey. Results of the follow-ups,
particularly eligibility levels were combined with eligibility
levels from the mail effort to yield total size strata levels
for the population.
Table D-3, following Exhibit D-3, presents a distribution
of results from both the phone and mail surveys.
Since all phone follow-ups were based on expected eligibility
rates, the proportions of usable returns between the surveys
should be the same. For the phone effort, 44% of the sample is
regulated and cooperated but for the main survey 24% are regu-
lated and cooperated. Combining telephone and mail responses
to yield a population estimate of regulated firms required
matching the samples to known population parameters.
Once eligibility rates were computed for both mail and
telephone respondents, the task became one of weighting respon-
dents and extrapolating out to the population. All data were
-------
TABLE D-l
Determining the Size of the
Eligible Population by Correcting
for Eligibility Rates
Size
Strata
Total
Mailouts
Out of
Business
Total
Returns
Usable
Returns
1 -
4
563
51
108
51
5 -
9
478
36
139
88
10 -
19
435
13
143
103
20 -
49
373
7
146
117
50 -
99
111
3
35
30
100 -
249
43
2
13
13
250+
HnlrnAU
Yl
7
211
0
38
1
32
1
16
UIUUlwW
2,221
150
617
419
Eligibility
Rate
.47
.63
.72
.80
.86
1.00
1.00
.50
Total
Eligibles*
241
280
304
293
93
41
7
86
* [Eligibility rate x Eligibles in business]
-------
TABLE D-2
Determining the Size of the
Telephone Sample by Strata
Eligibility Levels
Size
Strata
Total
Eligible
Relative
Size
Total
Eligible
Less
Prior Hail
Returns
Total
to be
Telephor
(Nail)
(Mail)
(Population)
1 -
4
241
.18
110
59
125
5 -
9
280
.21
128
40
63
10 -
19
304
,23
139
36
50
20 -
49
293
.22
134
17
21
50 -
99
93
.07
42
12
14
100 -
249
41
.03
18
5
5
250+
7
.01
3
2
2
Unknown
86
.06
39
23
46
1«345
1.01
613*
195
326
* 613 ¦ perfectly proportionate population for follow-up
** Computed for each strata from the eligibility rate
of that strata and the relative size of the strata
-------
TABLE D-3
Total Distribution of Types
of Respondents to the
Phone and Mail Surveys
Mail Phone
Survey Survey
Usable 444 143
Self-selected Out 243 112
Unlocated* 143 37
Refusal ~ 28
Not contacted 1,059
Unclassifiable 12
Totals 1,889 332 « 2,221
* Mergers, firms known to be out of business
and firms that could not be reached
-------
by sizing intervals. All eligible main respondents were
given a factor weight of (1). The eligible telephone respon-
dents were given a weight ranging from (3.1) to (11.5) depend-
ing on size strata. By summing over the weighted respondents
(444 mail, 144 telephone), the eligibility total of the orig-
inal sample frame (2,221) was found. This figure was then
multiplied by the original sample section interval (2.5) to
yield the population of eligible firms (2,941).
-------
-------
AUTOMATED FINANCIAL CLOSURE METHODOLOGY
A. DEVELOPMENTAL ISSUES
An automated financial closure routine was developed
for predicting firms least able to support an investment in
a pollution control system. The routine described below
was developed principally for the job shops and applied,
with minor revision to the printed board manufacturers.
The automated closure routine was not applied to the data
base of captive establishments.
Special features of this routine deserve special
mention here. Any combination of interest rates, payback
periods and abatement systems can be specified, costed and
closures predicted. The model uses a two-stage decision
rule; screening candidates for closure both by capital
availability through commercial sources, and then by equity
infusion by private (owner) sources. In addition, by alter-
ing the assumptions on pay back period, sales and coverage
ratio, a cash-flow approach to the investment can be
simulated.
During the development period of the closure model
the point was borne in mind that the outputs of the pro-
gram will receive intense scrutiny. Therefore, great care
went into defining the model's data elements; its decision
logic and criteria, and its capacity to withstand shifts
-------
in objective functions and still yield discriminating results.
In the following sections the capabilities, requirements and
products of the model are presented.
1. NINE SEQUENTIAL STEPS OCCUR IN THE MODEL
Exhibit E-I, on the following page, presents the eight
sequential steps of the program. The program begins with
costs, applies costs to all appropriate cases, assigns
models to various categories of fiscal strength, and yields
the number of cases that fail the financial tests. In
sequence, a brief description of each step appears below:
Analysis of Pollution Control Costs—The techni-
cal descriptors and the pollution control capital
and operating costs developed for the 82 model
plants by the EPA's technical contractor were
analyzed using correlation techniques. A re-
gression formula was developed that predicts pol-
lution control capital costs based on
finishing production water use.
Selection of Survey Respondents Having
Complete and Consistent Financial Data—
Because the financial model requires detailed
financial data, only those respondents that
answered all the financial questions and had
a balance sheet that balanced (within a 5%
range of error) were analyzed within the fi-
nancial closure methodology.
Assignment of Pollution Control Costs to
the 244 Selected Respondents—Pollution con-
trol costs were established as followss
Capital costs were set to the value pre-
dicted by the regression formula (dis-
cussed in step one) for those pieces
of equipment needed by the respondent
-------
EXHIBIT E-I
U.S. Environmental Protection Agency
FINANCIAL CLOSURE METHODOLOGY
1. Analysis of pollution control costs of the model plants
2. Selection of survey respondents having complete and consistent
financial data
3. Assignment of pollution control costs to the selected respondents
4. Initial selection of appropriate interest rates and allowable
price increases
5. Operation of automated financial model
6. Classifications of firms based on projected profitability and
capital access
7. Further investigation of marginal firms
-------
Operating costs were calculated as a
percentage of capital costs, using the
average ratio calculated for the 82
model plants, i.e., 12% of total capital
Initial Selection of Appropriate Interest
Rates and Allowable Price I ncreases—A nuxn-
ber of possible pricing and interest rate
scenarios were developed and analyzed in
order to yield three cases: best, worst
and mid-range. The cases are described in
the next section.
Operation of the Automated Financial Model—
The financial model was used to calculatethe
current financial performance and to estimate
the projected financial performance of each
firm for the three different cases. The auto-
mated financial model is described in detail in
the next section.
Classification of Firms Based on Projected
Profitability and Capital Access—Based on the
calculated financial measures, firms were
grouped into four categories for further
analysis:
Good capital access and good profitability
Good capital access but poor profitability
Poor capital access but good profitability
Poor capital access and poor profitability
Further investigation of Marginal Firing—Firms
that could not be classified clearly as candi-
dates for closures or nonclosures based on the
preceding analysis were analyzed further.
Several analytic techniques involving profit-
ability and owners compensation were used to
determine:
Which firms with good capital access but
poor profitability might elect to close
Which firms with poor capital access but
good profitability might remain open if a
reasonable amount of additional equity were
invested by the owners.
-------
Which firms considered candidates for clo-
sure might have been expected to close re-
gardless of the pollution control invest-
ment decision (Vulnerable Firms on a pre-
investment basis).
Prediction of Candidates for Closure Among the
Selected Firms—The results of the preceding
analyses werecombined to estimate which of
the 244 selected firms are likely candidates
for closure.
2. FINANCIAL CLOSURES ARE THOSE THAT FAIL ON
PROFITABILITY AND CAPITAL ACCESS CRITERIA
The automated financial model was designed to project
cash flows under different assumptions and then prepare pro
forma financial statements. The inputs, variables and out-
puts contained in the model are listed in Exhibit E-lI, fol-
lowing this page. The basic operation of the model for a
survey respondent includes these steps:
Calculation of current financial measures
using the respondent provided balance sheet
and income statement data, with an assumed
repayment schedule for reported long term
debt
Calculation of a modified, i.e., projected,
income statement using an:
Adjustment to sales due to a postulated
price increase to recover some portion
of expected pollution control costs
Increase in operating costs equal to
pollution control operating costs, de-
preciation of pollution control equip-
ment (over five year period) and in-
terest on a loan to purchase the pollu-
-------
EXHIBIT E-II
RESFOWPBHT PROVIDBD DftTA
Balance Sheet Data
Currant Assets
Fixed and other Assets
Current Liabilities
Long Term Debt
Met North
ADDITIONAL INPUT/VARIABf DATA
Inputs
Pollution Control Capital Cost
Pollution Control Operating Coats
8 tat aunt Data
Sales Depreciation
Owners Compensation
Profit (Loss) Before Taxes
Profit (Loss) After Tarns
U.S. Environmental Protection Agency
COMPUTERIZED FINANCIAL MODEL
Other Information
Ownership
Forecast Maximum Allowable
Price Increase
Ntsabar Of Owners Mho Work Pull Tlai
Variables
Interest on Outstanding Debt
Interest on Pollution Control Loan
Allowable Price Increase
Possible Equity Infusion
OUTPUTS
Coverage Ratio (cash flow divided by fixed obligations)
Profit after tax as percentage oft
. Sales
Total assets
• Met worth
Profit after tax plus owners compensation ast
. A percentage of. net worth
Dollara per owner who works full time
Financial ratios such ast
Debt percent
-------
Increase in profit after tax due to the
above changes and the investment tax
credit received for purchase of pollu-
tion control equipment
Formulation of a projected balance sheet re-
flecting the purchase and operation of pollu-
tion control equipment
Calculation of financial measures using the
updated balance sheet, income statement and
cash flow calculations
Determination of the amount of additional equity
capital that a profitable firm with capital
access problems would have to invest to qualify
for a loan for the remainder of the pollution
control capital cost
The resultant financial measures predicted by the model
are used to identify the firms with potential capital access
or profitability problems. The three most important predic-
tive measures are:
(Profit after tax)/(riet worth), which is the basic
return on equity measure used in analyzing business
investment decisions
(Profit after tax) plus (owner's compensation/number
of working owners), which is the total salary and
return that a working owner received from running
his firm
(Cash Flow)/(Fixed Obligation), the coverage ratio,
which is a standard baulking measure of the pro-
jected ability of the borrowers to repay a loan
These and three other output measures are illustrated in
Exhibit E-III, following this page. This form is generated
by the model for each respondent.
-------
Model Identification s
Projected t
Current
Fixed + Other
Assets
Totals
Difference (%)
Presenti
Liabilities
Current
LTD
Net North
Sale*
Depreciation
Profit Before Taxes
Profit lifter Hums
Cash Plow
Coverage Ratio
Operating Ratios:
Fixed Asset Turnover:
Cash Flow/Seles:
Cash Flow/Total Assets:
Profitability:
Profit After Taxes/Salesi
PAT/TOtal Assets:
PAT/Net Worth:
PATtOwners One/Met North
Cash Flow/Capitalisation t
Liquidity:
Current Ratio:
Leverage:
Debt Percent:
Debt to Equity:
Pollution Control Costs:
Least Cost Option:
Capital Cost:
OCM Costs
Energy Cost:
Equity Infusion:
Percent of PCC Borrowed:
Cost Pass-Through t
Return to WoiVlnq Ouaext
CYobitc Catw»in t
EXHIBIT E-III
U.S. Environmental Protection Agency
STANDARD DATA ELEMENTS FOR FINANCIAL ANALYSIS
OF MODEL PLANTS
Assets Liabilities
Current Current
Fixed ~ Other LTD
Met North
Totals
Difference («)
Sales
Depreciation
Profit Before Taxes
Profit After Taxes
Cash Flow
Coverage Ratio
Operating'Ratios >
Fixed Asset Turnover:
Cash Flow/Sales:
Cash Flow/Total Assets:
Profitability i
Profit After Taxes/Sales:
PAT/Total Assets:
PAT/Net North:
PATtOwners Coap/Net North
Cash Flow/Capitalization:
Liquidity:
Current Ratio:
Leverage:
Debt Percent:
Debt to Equity:
Profitability Changes
Profit After Taxes/Sales:
PAT/Total Assets:
PAT/Net North:
-------
B. VERIFICATIONS
From all of the preceding It should be clear that the
outputs of the financial closure model are a set of solu-
tions to specific independent (or input) variables. The
identified vulnerable firms are those which failed to meet
a set of empirical criteria and objective functions. In
order to accept the program's outcomes as valid estimates
of economic consequences for firms in the industry, objec-
tive reviews of the findings are required. There are two
compelling reasons for this verification step:
A financial investment closure model is one
specification of economic behavior. Any model
is limited by the set of variables it includes
for prediction and by the values it assigns to
those variables. Because changes to these vari-
ables might change the outcomes, it is critical
to establish the predictive power of the model,
e.g., its capacity to make predictions that
agree with other, non-model data.
Assessing the fiscal strength of a particular
firm by using self-reported financial data also
requires confirmation. Financial data can be
interpreted differently by different analysts,
and not all parties would necessarily agree on
precisely what constitutes an economically non-
viable firm.
To deal with these issues we conducted a series of
special follow-up analyses on the data. Collectively these
steps constitute a verification of the automated closure
model, and covered the following:
A core group of predicted closures was analyzed
by inspecting all the available information on
-------
the returns. This review incorporated items such
as planned capital investments for productive
assets, computation of financial ratios other
than the ones of the model, and an assessment of
whether the plant might be a baseline closure
independent of the incremental investment in pol-
lution controls.
Closures were predicted in plants that sell in
excess of a million dollars annually. This find-
ing seemed counter-intuitive because such firms
were presumed to enjoy scalar economies as well
as a stronger capital base. For these cases
complete financial reports were purchased from
Dun 6 Bradstreet (D6B) and detailed financial
(closure) analyses were run using those data.
Concerns existed that our base year (1975) was
atypical and that it represented a poor sales
year for basing industry financial closures.
In addition, there was the point that bank lend-
ing rules differed from those of the model.
Third, the concern was expressed that the raw
data of the survey may vary from that given
other sources (D&B) and conclusions drawn from
the model might be in error. Special follow-up
surveys coupled with the most recent D&B data
dealt with this group of potential problems.
Each potential problem coupled to its verification step
is presented below.
1. PROM THE FIRST GROUP OF CLOSURES 90% WERE FOUND TO BE
TRULY ifoN-VIABLE ECONOMIC ENttTO3
To test whether the closure model made accurate selec-
tions of financially vulnerable firms, a special cost-
closure scenario was run for all models. This specifica-
tion was one of the least expensive options possible, i.e.,
oxidation of amenable cyanide only. With a mean capital
requirement of under $20,000, 19 cases were predicted to
close. OSiese 19 were reviewed in detail to pinpoint'
-------
precisely what constituted their vulnerabilities. The
following was found:
Most of the 19 reported either a loss before or
after tax. On the basis of cash flows none of
the firms generated sufficient profits to sup-
port a loan.
Almost all cases (17) fell considerably below
the projected coverage ratio of 1.5. Two cases
were calculated at 1.40-1.49. These two cases
were judged "swing" cases in the sense that
minor reductions in their investment (tm $2,500)
would result in computed coverage ratios of at
least 1.5.
2. SPECIAL ANALYSIS OF LARGER FIRMS CONFIRMED THAT SOME
MIGHT NOT SUCCESSFULLY SUPPORT ADDED CAPITAL BURDENS
From the survey returns there were 13 firms with em-
ployment of at least 100 men and sales of at least $1 mil-
lion. Based on the completeness of those returns, seven
cases qualified as models. In a full BPT investment case
there were three closures for a closure rate of 23% for
the group.
Several questions arose:
Are the 13 respondents truly representative of
most large firms?
Are the seven models a good cross-sectional
representation of such firms?
Are the three identified closures unique or
representative?
E-8
-------
The only means of answering these questions was to
test the model's predictions against an alternate data base
and determine whether the observed closures are aberrant
cases or not. To this end the following was done:
From the Dun & Bradstreet file on the industry
70 large firms were identified and their finan-
cial records requested. This yielded 42 usable
reports.
Of the 42 reports, 19 clearly were not job shops.
Of the remaining 23 cases, 16 lacked all the nec-
essary information for comparable analysis.
This left seven cases for comparison with the
seven models.
These 7 D&B cases were compared with the 13 sur-
vey respondents as a whole, and then with the
7 models and 6 non-models. Specifically noted
were agreement on mean sales, sales per man,
debt levels, and a series of financial ratios.
No significant disagreements were noted. The
conclusion here is that the 13 survey respondents
are a good representation of the financial char-
acteristics of large job shops.
On these seven O&B cases, a modified closure
analysis was run using financial ratios reflect-
ing the firm's relative capacity ot take on debt:
- Long-Term Debt/Net Worth
Net Worth/Employee
Total Assets/Net Worth
In the group of seven D&B firms, there were two
and perhaps a third firm that had extraordinary
debt levels that precluded assuming more for
pollution controls.
This comparison of seven new D&B cases to seven study
models is more a support than a proof of the model's find-
ings. Were better financial data available for all 42
cases, there would be greater confidence in the projected
-------
closure rate of 23% for the group. At best, we have es-
tablished that our 13 respondents are not fundamentally
different from other cases in the group and that identify-
ing 2 of 7 firms as financially vulnerable can be repli-
cated with a second group.
3. A SERIES OF SPECIAL SURVEYS LENT SUPPORT TO BOTH THE
ASSUMPTIONS AND UTILITY OP TOE FINANCIAL CLOSURE
MODEL
Several additional concerns were raised during the
course of the study that required a response. These con-
cerns come down to three generic iBsues:
1975 may not be a typical year for the industry
and conclusions based on data for 1975 could
misrepresent the industry's capabilities.
Bankers may or may not use a 1.5 coverage ratio.
To the extent banks use unique criteria for as-
sessing loan recipients, the predictions of the
model may be in error.
Base data received via the survey may be dif-
ferent from that given other sources. Poten-
tially the raw data of the study could be
biased and of questionable use in an economic
impact study.
During the life of the study each issue was addressed
in a manner that both satisfies methodological rigor and
lays the potential criticism to rest.
(1) 1975 Was a "Typical" Year for the industry
Shortly after the raw data were in hand and pre-
liminary analyses run it was apparent that a means to
-------
assess the "goodness" of 1975 would be desirable.
Financial data over-time were omitted from the survey
in hopes of boosting response rates. There was no
built-in mechanism for interpreting each firm's rela-
tive performance in 1975 against prior years. A first
step in addressing this issue was to pull a sampling
of 100 job shop respondents for follow-up contact.
A short phone protocol was developed in which the key
question was:
Looking back to your plant's financial per-
formance in 1975, would you judge that year
to be: (1) above average, (2) about average,
or (3) below average?
Responses split evenly across the item. There
were as many people (33) who judged 1975 to be above
average as those (34) who judged it to be below. On
the basis of this follow-up survey, 1975 serves as
well as any year in which to project the economic
consequences of compliance on the industry.
The second step in judging the suitability of
using 1975 survey data was to match updated D&B fi-
nancial reports to the survey data. More than 300
financial reports were purchased for our core group
of 461 respondents. Of the firms not contacted by
phone, we assembled a cluster of 150 firms that pro-
vided both financial data to use in 1975 and to D&B
in either 1976 or early 1977.
-------
We noted that more than half the cases (80) gave
the same data to use as they did to D6B in 1975 or
early 1976. Fully one-quarter of the cases reported
1976 data that were within + 10% of the 1975 data.
Of the remaining 50 cases there were not more than
10 that reported a 1976 or 1977 line item from the
balance sheet that was more than 50% greater than in
1975.
Not only is the agreement between survey infor-
mation and D&B information quite strong, but the op-
erating changes are slow to be reflected within the
company balance sheet. This helps support two
conclusions:
Respondents provide consistent financial
information to us and to D&B. There was
no systematic distortion in the survey.
Closure rates computed for 1975, all things
being equal, should reflect industry via-
bility as well as any other year.
(2) Bankers Supported the Use of Coverage Ratio
Calculations
A major component of the automated closure rou-
tine is the incorporation of commercial lending rules.
Here there are two potential errors; either a cover-
age ratio calculation is irrelevant to the loan pro-
cess, and/or our threshold value of 1.5 is inappropri-
ate. We found neither to be the case.
-------
Prior attempts to contact banks familiar with
the financial needs of metalfinishers had proven of
limited value. Without knowing the specific banks -
in specific cities in which finishers conduct their
business, a survey of commercial bankers becomes a
stab in the dark.
From the same D&B financial reports utilized in.
comparing 1975 to recent financial conditions we noted
the name of the company's banker, and selected a dis-
tribution of 25 cases for contact. This is an ad-
mittedly small sample, but it is drawn with the knowl-
edge that each bank is actually serving a firm in the
industry.
No question that identified a particular respon-
dent to the survey was posed. The focus was specif-
ically the bank's lending rules for the industry, the
prevalence of requests for pollution control invest-
ments, and the applicability of a 1.5 criterion for a
coverage ratio calculation. Not surprisingly, each
commercial lending officer maintained that loan ap-
, plications are treated as unique cases and universal
lending rules are not applied. Each did acknowledge,
however, that a calculated coverage ratio is one im-
portant predictor of a firm's condition and the higher
the value the better. Our use of 1.5 to split
-------
probable loan rejections from loan approvals was
generally confirmed in our conversations with com-
mercial lending officers.
-------
-------
THE POLLUTION ABATEMENT
COST GENERATING PROGRAM
INTRODUCTION
This appendix describes the methodology employed by
the technical contractor (Hamilton Standard) for estimating
wastewater treatment costs for 82 electroplating job shops.
These model plants were selected by the economics contractor
and supplied to the technical contractor. Technical and
production data on these plants were used as input data to
the contractor's cost estimating program.
Hamilton Standard has revised and updated this pro-
gram during the past several years. At this time it may
be the most sophisticated tool of its type. It is capable
of generating equipment specifications and costs for direct
and indirect dischargers, reflecting cases with partial
equipment-in-place as well as alternative treatment
scenarios.
1. AN AUTOMATED POLLUTION CONTROL COST ESTIMATING
PROGRAM IS INDISPENSABLE FOR MANAGING COMPLEX TECHNICAL
INFORMATION
As the U.S. Environmental Protection Agency commis-
sions technical development documents in support of guide-
lines limitations and standards for industrial point source
dischargers, an immediate problem is the management of com-
plex technical data. Not only are large quantities of data
-------
generated for plant flows, concentrations and contaminants,
but also systematic cost estimates must be derived for all
abatement components designed to meet established or recom-
mended limitations.
Calculations are made for both the effluent dimensions
and for the pollution control systems. Designing, develop-
ing» and applying automated cost generating programs for
these data are critical to the expeditious discharge of the
regulation setting mission of the Aaency.
To this end, Hamilton standard has developed two com-
puter routines to facilitate such calculations. The rou-
tines have been used successfully in two separate EPA
studies over the past few years and have been updated to
reflect critical comments and new base line data.
2. THE COST PROGRAMS INCORPORATE SYSTEMATICALLY ALL
RELEVANT TECHNICAL DATA
The first step in computerized analysis of the col-
lected data for an EPA project is the formation of a plant
tape data file. Information on the data tape for each plant
typically consists of raw and effluent stream flows and pol-
lutant concentrations, production processes performed, pro-
duction rates for each production subcategory or factors
from which production rates can oe determined (such as hours
per day of operation, floor area in production, water dis-
charge from production subcategories, etc.), and waste
-------
treatment equipment employed. A separate tape file is
typically generated for each industry due to variations
in the type of data collected. Exhibit F-I, following
this page, shows a typical plant data file for a plant
performing painting or similar surface treatment.
The next step in computerization is the generation
of the analysis programs. The analysis programs calculate
the actual plant effluent as either grams per day or in
terms of a production-related parameter such as mg/square
meter of surface processed. The first analysis program
brought into play is the statistical analysis program.
This program calculates the actual discharge from each sub-
category through the use of flow data and concentrations
or by using an apportioning formula. A set of pass/fail
criteria is established in the program. These pass/fail
criteria may be the average of all data, current regulations
for the industry under study or some value established on
the basis of water use per unit of production times an ac-
ceptable concentration. The pass/fail gate allows the com-
puter to display the distribution of data points relative
to the gate. Those data points not passing the gates are
listed along with the company identification number (ID).
These "flagged" data points are examined to ensure that the
input data to the computer are correct, that the laboratory
analysis is correct and consistent and that the raw waste
and treated effluent are reasonable. If no apparent errors
-------
EXHIBIT F-l (1)
U.S. Environmental Protection Agency
TYPICAL PLANT DATA FILE
HAMILTON STAMDAMD DIVISION OP UNITED TECHNOLOGIES
OAT A COLLECTION SURVEY FOR THE SURFACE TREATMENT AND CHEMICAL COAT INC SEC HE NT
Of THE MACHINERY ANO MECHANICAL PROOUCTS POINT SOURCE CATEGORY
MANUFACTURING EFFLUENT LIMITATIONS GUIDELINES DEVELOPMENT PROGRAM
.• MANUFACTUMING ESTABLISHMENT DATA
10 NUMBER 6-&T4-12-0
NAME
AOORESS
TELEPHONE
PLANT PERSONNEL CONTACTED!
SHOP TYPE I CAPTIVE DISCHARGES MUNICIPAL
NO. SWF ACE TRTNT WORKERS 210
TOTAL NUMBER OF EMPLOYEES 4100
StANOARO INDUSTRIAL CLASSIFICATION 3429
PRINCIPLE PRODUCTS SURFACE TREATED BUILDING HARDWARE
PRINCIPLE RAM MATERIALS CONSUMED
SULFURIC ACID TSO.O U f DAY
TOT ORGANIC CARBON IOB.O LB / OAV
PHOSPHAriNG CHEMICAL 24.0 LB / DAY
ENAMELS 55.0 CAL / OAV
PRINCIPLE WASTE TREATMENT CHEMICALS CONSUMED
HONE LISTEO
2.0 MATER SUPPLY ANO USC
2.1 MATER SUPPLY SOURCE
Type
MUNICIPAL
HELL
QUANTITY 6PN
71000
43125
2.2 HATER USAGE
TYPE
DOES PLANT PRODUCTION LEVEL AFFECT MATER USACCT
QUANTI?? PERCENT RECYCLE
YES
TOTAL PROCESS 132500
SANITABV 4AB7
COOLING 2I7M
TOTAL NONPROCESS I343B
B
B
IT
8
3.0 M«STE CHARACTERISTICS
9.1 CURRENT REOUIREWNTSOR REGULATIONS*
-------
EXHIBIT F-I
(2)
S.2 COMPOSITION Of STREAMS
PARAMETERS PEASUREO AS TOTAL
CONSTITUENTS
SPRAY COATNC
SPRAY COATNC
RAM WASTE> 0
FINL EFFI>22
BHR COMPSITE
GRAB SAMPLE
JUN 25.197*
JUN 25.197*
ALUMINUM
2. 19
29.50
AMMONIA
0.850
••••••MM
BARIUM
••••••MM
**********
B. 0. 0.
**********
BORON
**********
**********
CADMIUM
0.001
0.00*
CHLORINATC0 HVOROCAR
**********
**********
CHROMIUM.HEXAVALEMT
0.028
1.890
CHROMIUM.TOTAL
0.897
1.890
C. n. 0.
1913*.
1543*.
CONDUCT AMCC UHHO/CM
••••••••••
**********
COPPER
0.237
2.470
CYANIDE ANN.TO CHLOR
**********
**********
CYANIDE.TOTAL
**********
01SSOLVEO OXYGEN
**********
FLOW IGPHI
3.
30.
FLUORIDES
3.80
2.90
COLO
**********
**********
IRON
2.310
1.000
LEAO
0.291
0.177
MAGNESIUM
••••••MM
**********
MERCURY
0.001
0.001
MOLYBDENUM
**********
**********
NICKEL
0.028
0.043
N!fRATES
••••••MM
OIL* GREASE
1*09.
3*0.
PALLADIUM
**********
PH. ACIOIC
**********
**********
PH. ALKALINE
**********
**********
PHENOLS
0.447
**********
PHOSPHORUS
2.20
5.50
PLATINUM
**********
•••••MM*
POTASSIUM
**********
**********
RHODIUM
**********
**********
SILICA
**********
**********
SILVER
**********
SETTLEABLE SOUOS
**********
**********
TOTAL SOL (OS.
**********
**********
TOT. OISSOLV0 SOLIOS
822.00
77*4.00
TOT. SUSPENOED SOS.
7729.00
3*0.00
TOT. VOLATILE SOLIOS
••••••••••
SULFATES
••••••••••
**********
SULFIDES
**********
**********
SURFACTANTS
**********
**********
TEMPERATURE OCC F
**********
**********
TIM
0.06
0.09
TITANIUN
MMMMM
••••••••••
I INC
1.3B0
0.7*2
IOT ORGANIC CARBON
*125.
42.
KJELOAML NITROGEN
3.*3
10 NUMBER *-*79-12-0
(•*«•••••»• INOtCATES NO CNTRYI
SPRAY C0ATN6
RAM MASTE> 0
CRAB SAMPLE
JUN 25.197*
30. SO
0.2T5
**********
0.003
•••••*••*•
2.000
2.000
16702.
2.930
**********
*»»»«*•*»*
**********
H.
3.20
**********
I.OtO
0.2*3
**********
0.001
»«««*»»»»
0.02B
218.
0.409
3. BO
**********
••••MMM
••••M*M*
••••••••••
••••••••••
8196.00
592.00
••••*•••»•
SPRAY COATNC
FINL EF*L>22
GRAB SAMPLt
JUN 25.IS 76
1.37
•«•*•»*•••
0.001
•••••*•*•»
0.005
0.089
9560.
**********
0.100
•••*•*••*»
30.
2.90
••••••••*•
1.250
0.050
•*••••••••
0.001
**********
0.017
1.
**********
0.50
«*(»»«»»*»
744.00
782.00
•••••••*••
SPRAY COATNC
RAW WASTE> 0
CRAB SAMPLE
JUN 25.1976
5.2B
**********
0.001
**********
0.005
0.737
74.
**********
18.800
**********
3.
2.90
23.200
2.500
0.001
**********
0.128
**********
*92.
**********
**********
**********
0.288
0.50
••••••••••
**********
**********
575.00
381S.OO
••••••••••
SPRAY COATNC
!NTFRNEOT> 0
BHR COMPStTE
JUN 25.1976
0.74
0.120
**********
**********
0.008
**********
0.005
0.175
581.
**********
0.150
**********
**********
**********
30.
0.22
3750.000
0.050
•••••••»»•
0.001
•••••*•»••
0.0*7
**********
30.
••••••••••
**********
0.127
3. BO
•••••M**«
••••••••••
9511.00
2*4.00
**********
**********
SPRAY COATNC
FINL EFFL>22
BHR COMPSITE
JUN 25.197*
0.19
0.210
**********
0. 001
**********
0.005
0.019
98.
••••••••••
0.47*
••••••*•••
• ••••MM*
••••••••••
30.
1.30
**********
1.200
0. 138
••••••MM
0. 001
•••••MM*
0.012
**********
9.
**********
0.1*1
15.30
**********
**********
**********
3*8.00
23.00
••••**•*••
SPRAY COATMS
FINL EFFL>22
BHR COMPSITE
JUN 25.197*
0.79
0.290
• »MM*«M
**********
0.009
**********
0.005
0.005
32.
••••••••«•
0.039
•••••••»M
**********
30.
0.90
••••••MM
0.6*7
0.010
••••••MM
O.OOt
**********
0.031
**********
I.
••••••••••
0.110
B.40
**********
166.00
19.00
0.08
••••••••••
0.952
4740.
0. S*
**********
0.06
••••••MM
0.200
3000.
••••••MM
0.0*
• ••••MM*
9.7*0
1050.
*.82
0.0*
••••••••••
0.4*2
4*.
•••«••••••
**********
0.0*
••••••MM
0.*92
37.
0.49
0„G*
••••••MM
0.714
23*
-------
9.) WASTE TREATMENT COST INFORMATION
EXHIBIT F-I (3)
TREATMENT SVSTCN
OATI
CAPITAL
OFERATINO RAN WASTE
HASTE
IDENTIFICATION
INSTALLED
COSTS
COSTS
STREAMS TREATED
9
m
g
•4
i
III
ll/YRI
in
CONVENTIONAL
BAKER BROS. CHRONE UNIT
19 TS
SOOOO
I24B
CHRONE RINSE
0
CONVENTIONAL
OIL SEFERATION
I9TS
22000
0
NON-SOLUBLE OILS
too
CONVENTIONAL
NEN FLATINC TREATNENT
191?
1290000
0
PLATING ACIOS AND RINSE
0
RECYCLE
WASTESAVER OISTILLATION
19TS
40000
0
CYANIDE PLATING HASTE
SO
RECYCLE
ECO-TEC
19T4
49000
«
CHRONE MAST"
a*
(MttfiT
REQUIRENCN1
(KN*HRt/Y*
METHOD t.O.NO. TECHNIQUE
24 CHEMICAL REDUCTION
15 PH ADJUST (FINAL)
*9 MIXER NODE I
2 CONTINUOUS
12 EVAPORATION
91 BRANCH NOOE 2
TS PROCESSINC FOR REUSE
*1 BRANCH NODE 2
tl MIXER NODE I
2 CONTINUOUS
24 CHEMICAL REDUCTION
II ION EXCHANGE
29 FH ADJUST I FINALI
*2 BRANCH NODE S
?9 FR0CESSIN6 FOR REUS!
92 BRANCH NODE i
99 MIXER NODE I
I BATCH
24 CHEMICAL REDUCTION
23 CHEMICAL OXIDATION
29 FH AOJUST IFINALI
9J BRANCH NODE 4
TO SANITARY SEWER
21 EMULSION BREAKING
40 BRANCH NOOE 1
.2 CONTRACT REMOVAL-OIL
90 BRANCH NODE |
9* MIXER NOOE 2
TS PROCESSING FOR REUSE
B.O SURFACE TREATMENT PROCESSES
OC SCRIPT ION W/MV UfHk CPLX USt MKKUl
-------
are found, further checks are made. Historical data, when
available, is compared to the "flagged" data. Often the
company is called and asked if this data point is consistent
with past samples of the same parameter. Whenever possible,
an explanation is developed for each "flagged" data point.
A second analytical program is used in many industry
studies. This second program calculates the actual plant
discharge in grams per day, the allowable discharge based
on the established or tentative regulations, and compares
the two numbers for each pollutant. This program also al-
lows the combination of multiple regulations to provide a
pass/fail test of a multiple use plant.
A log diagram is shown in Exhibit F-II, following this
page, which depicts the basic steps used in the programs.
The first set of analytical programs developed used
all available concentration values for all parameters.
Since then, many refinements have been incorporated. The
first unique feature of the programs is that they do not
use values for pollutants which do not exist in the plant.
A search is made of the plant description and raw material
file to determine if a particular pollutant material is used
in the plant. If no use of the pollutant is found, the
values are not normally used in calculating the minimum
and mean values for all plants. The exception to this rule
is used when the concentration value is abnormally high or
F-4
-------
OPERATION
tl ELECTROSATIC IHAY SOLVENT M« ENAMELS
«f IWYINC
DESCRIPTION HR/DAV IB/Ml CHX MSB MATERIAL
MINI LINE NO. t 14.0 425.0 0 IRON
OPERATION
S PHOSPHATING JATER RASE PH0SPHATIN6 CHEMICAL
II I STAGE RINSE FIXED ORIFICE
II I STAGE RINSE FIXED ORIFICE
41 ELECTROSATIC SPRAY SOLVENT RASE ENAMELS
«* OTHER POSTTREATREMT
OESCRIPTION HR/OAV LR/HR CPLX RASE MATERIAL
RICHIE LINE t*.0 44000.0 0 IRON
OPERATION
41 ACtO FICKLE/DCSCALE MATER RASE SULFURIC AC10
41 ACIO PICKLE/OESCALE MATER RASE SULFURIC ACIO
41 ACIO FICKLE/DESCALE MATER BASE SULFURIC ACIO
It I STAGE RINSE FIXEO ORIFICE
II I STAGE RINSE FIXEO ORIFICE
• S ORVING
EXHIBIT F-I
FTl/HR
GAL/MR
FT2
4 3. BO
3.40
140,
43. BO
0.0
450
FT2/HR
GAL/HR
FT2
159.50
0.0
740.
15**.50
30.00
740,
159.50
30.00
740,
159.50
0.0
740,
159.50
0.0
530,
FT2/HR
GAL/HR
FT2
33*5.00
4SO.OO
370.
3375.00
4S0.00
370.
3375.00
480.00
370.
3*7'.00
480.00
370.
3)75.00
0.0
370.
3375.00
0.0
-------
the production related value exceeds the gate. Another
unique feature of the programs is the ability to use mul-
tiple gates (usually an existing regulation and a set of
proposed changes). This feature allows comparison of the
allowable discharges from various plants to quickly ascer-
tain the impact of the changes. Comparisons have been run
with all parameters as well as just a selected list of the
critical ones.
The analytical programs currently in use can analyze
treatment effluent as reported (usually monthly) or as an
average for all reported values of a parameter. Raw waste
analysis can also be done on the same basis. Finally, in-
dividual selected types of streams can be analyzed for
particular features. A comparison feature has also been
included to provide the percent removal accomplished for
each pollutant parameter.
These analytical programs can handle up to 77 pollu-
tant parameters and 8 months of sample data. Table P—1,
following this page, shows 67 parameters currently pro-
grammed and there are 10 open boxes for other pollutants.
Also, since data is received from many sources, such as
self sampling, compliance data from regulatory agencies,
and sampling programs conducted by the EPA, the source of
the data is coded to show who supplied the information.
-------
EXHIBIT F-II
U.S. Environmental Protection Agency
SIMPLIFIED LOGIC DIAGRAM POLLUTANT
ANALYSIS PROGRAM
ANALYSIS
OPTIONS
PLANT OH!?
LIST
PLANT STREAM
DATA
OMIT PLANT
READ NEXT PLANT
PLANT CHECK CONTAINS
PROPER OPTION DATA
ACCEPTABLE ID
PLANT
PRODUCTION
DATA
DATA INCOMPLETE
READ NEXT PLANT
TAPE DATA
CHECK
5
ACCEPTED PLANTS
CALCULATE PRODUCTION
RATE IN PROPER UNITS
I APPORTION POLJ.UTANTI
MASS TO SUBCATEGORY!
CALCULATE EFFLUENT
MASS PER SUBCATEGORY
PER UNIT OF PRODUCTION
COMPARE TO STORED OR
CALCULATED REGULATORT
VALUES
ALL PLAtiT FILES READ
H
-------
TABLE F-l (1)
Pollutant Parameters
Parameter
PH
Turbidity
Temperature
Dissolved Oxygen
Residual Chlorine
Acidity
Alkalinity
Ammonia
Biochemical Oxygen Demand (BOD5)
Color
Sulfide
Cyanides
Kjeldahl Nitrogen
Phenols
Conductance
Total Solids
Total Suspendable Solids
Settleable Solids
Aluminum
Barium
Cadmium
Calcium
Chloride
Chromium
Copper
Fluoride
Iron, Total
Lead
Magnesium
Manganese
Molybdenum
Oil, Grease
Hardness
Chemical Oxygen Demand (COD)
Algicides
Total Phosphate
Polychlorobipheny1s
Pottassium
Silica
Sodium
Sulfate
Sulfite
Titanium
Zinc
Units
pH units
Jackson units
Degrees C
mg/liter
mg/liter
mg/liter CaC03
mg/liter CaC03
mg/liter
mg/liter
chloroplatinate units
mg/liter
mg/liter
mg/liter
mg/liter
micromhos/cm
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter CaC03
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
-------
TABLE F-l (2)
Parameter
Units
Arsenic
Boron
iron, Dissolved
Mercury
Nickel
Nitrate
Nitrite
Selenium
Silver
Strontium
Beryllium
Chlorinated Hydrocarbons
Total Volatile Solids
Surfactants
Plasticizers
Antimony
Bromide
Cobalt
Thallium
Tin
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
mg/liter
-------
Wh6n using these programs, several options are avail-
able. These include the selection of:
Discharge Destination—All surface dischargers,
all municipal dischargers, or all dischargers
may be selected and used. With sewer dischargers,
pretreatment standards are used. When all dis-
chargers are combined, the programs use the sur-
face discharge regulations.
Type of Analysis—Raw waste, treated waste or
special.
Analysis of Individual Stream or Plant Average—
On a stream basis, actual mass dischargers from
each appropriate stream are used as individual
data points. When analyzed by plant, the actual
mass dischargers for all of the appropriate
streams are averaged to provide a single data
point for the plant.
Type of Output—Either the statistical format
snowing minimum, maximum and mean values by sub-
category, or the plant performance format showing
individual plant allowable and actual discharge.
The calculation of actual discharge is quite straight-
forward. Effluent flow times the concentration provides
the actual mass discharged. Calculation of the allowable
discharge is more complex and depends on the industry and
the regulations involved. The simplest of the allowable
calculations is for Machinery and Mechanical Products.
Here a fixed factor (mg/m2 of floor area) for each sub-
category is multipled by the existing floor area devoted
to the operations in the subcategory. The procedure is
repeated for each subcategory and summed to show the total
allowable discharge for the plant.
-------
3. A SEPARATE PROGRAM (THE SYSTEM COST ANALYSIS PROGRAM)
Generals c6stt ESfiMATBS 1
A second major problem facing the U.S. EPA is consistent
estimates of cost of treatment. Each new effluent limita-
tion requires an estimate of the cost of the Best Practica-
ble Technology (BPT) and Best Available Technology (BAT)
wastewater treatment systems necessary to meet the standards.
A mathematical model or set pf correlations was de-
veloped for each individual wastewater treatment technology
commonly found in industry. A list of the programmed pro-
cess is contained in Table F-2, on the following page. In
general, these correlations relate equipment size to influent
flow rate and pollutant concentrations and, in turn, relate
cost to equipment size.
(1) All Data Comes From Authoritative Sources
The basic cost data came from a number of primary
sources. Some of the data were obtained during on-site
surveys. Other data were obtained through discussions
with waste treatment equipment manufacturers. Another
block of data was derived from previous EPA projects
which utilized data from engineering firms experienced
in the installation of waste treatment systems. These
data for wastewater flow rates, corresponding equip-
ment size and cost, were related by means of a separate
computer program. This program was developed to cor-
relate the data by regression analysis, utilizing
-------
TABLE F-2
Programmed Processes
Spray/Fog Rinse
Countercurrent Rinse
Vacuum Filtration
Gravity Thickening
Sludge Drying Beds
Raw Wastewater Pumping
Holding Tanks (lined or unlined)
Centrifugation
Equalization (concrete or earth)
Contractor Removal (wet or dry)
Reverse Osmosis
Landfill
Chemical Reduction of Chromium
Chemical Oxidation of Cyanide
Neutralization
Clarification (settling tank or tube settler)
API Oil Skimming
Emulsion Breaking
Membrane Filtration
Filtration (with or without alum, precoat)
Ion Exchange-ln-Plant Regeneration
Ion Exchange-Service Regeneration
Flash Evaporation
Climbing Film Evaporation-
Atmospheric Evaporation
Sanitary Sewer Discharge Fee
Cyclic Ion Exchange
Ultrafiltration
Submerged Tube Evaporation
Flotation/Separation
Wiped Film Evaporation
Preliminary Treatment
Preliminary Sedimentation
Aerator - Final Settler
Tricking Filter - Final Settler
Chlorination
Flotation Thickening
Multiple Hearth Incineration
Aerobic Digestion
Post Aeration
Sludge Pumping
Activated Carbon Adsorption
Copper Cementation
-------
first order arithmetic equations, first order logarith-
mic equations, and multiple order equations as
appropriate.
Subsequent to the initial programming, reviews
have been conducted by the EPA and at least two Eco-
nomic Analysis Contractors. These revievjs questioned
some assumptions and provided some valuable sugges-
tions for further updating. The capability for the
computer to select the least cost approach has been
incorporated. Large flows use a full treatment sys-
tem, but, as the flow decreases, batch treatment and
finally contractor wet haul of all wastes becomes the
most economical. Also for large flows, a concrete
tank (clarifier, etc.) is cheapest but as flow de-
creases, steel tanks become the more economical. This
type of variation plus constant review of the cost
equations provides an accurate method of estimating
impact of treatment on an industry as well as provid-
ing the EPA with a consistent result from industry
to industry.
The System Cost Analysis program was generated
to perform both the system cost estimate and perfor-
mance calculations. The needed cost estimates in-
clude the system required investment and total annual
cost break-down. Wastewater treatment system perfor-
mance must also be modeled to determine if the treatment
-------
system being costed satisfies the proposed effluent
limitations. To provide the broadest modeling tool
possible, the following techniques were incorporated
into the program logics
Generalized, "black-box," wastewater treat-
ment process definition to allow flexibility
in the variety of wastewater treatment sys-
tems that can be described
"Decision" fields for each individual treat-
ment process so that process design para-
meters such as hydraulic loadings, reten-
tion times, or operating mode decisions can
be varied
Multiple raw waste stream allocations so
that stream segregation treatment tech-
niques can be described
Generalized wastewater stream pollutant
parameter definition to model various wastes
and to perform intermediate system perfor-
mance calculations
Generalized costing factors so that material
or localized cost estimates can be made for
any desired dollar base period
(2) Five Data Elements Have to be Specified
To execute the System Cost Analysis program, a
definition must be provided for the following five
items:
The treatment processses to be used and
their interconnection
The "decision" parameters for each process
used
The raw waste steam flow and pollutants
for each influent stream
-------
The costing factors for the treatment system
The tolerance bands for any recycle loops
in the system
Up to 24 individual wastewater treatment processes
can be modeled into a single system. A simplified
logic diagram is shown in Exhibit F-III, on the fol-
lowing page, depicting the basic steps taken by the
program. Table F-2 on page 10, presented a list of
the currently programmed treatment processes. The
connecting stream locations and the "decision" para-
meters for each of the wastewater treatment processes
being incorporated into the system model must also
be specified.
The raw waste streams entering the treatment sys-
tem must be specified either manually or from the raw
waste analysis program previously described. Anywhere
from 1 to 10 influent streams can be defined. A
typical treatment system with six raw waste streams is
shown in Exhibit F-IV, following Exhibit F-lll. Flow
and up to 67 pollutant parameter values are specified
for each raw waste stream. Table F-l in the Effluent
Analysis Program section presented a list of those
pollutant parameters which can be entered as raw waste
and for which performance calculations are made.
Data are also required for each wastewater treat-
ment system to define costing factors at a desired
-------
EXHIBIT F-HI
U.S. Environmental Protection Agency
SIMPLIFIED LOGIC DIAGRAM—SYSTEM COST
ANALYSIS PROGRAM
INPUT
A) RAW WASTE DESCRIPTION
B) SYSTEM DESCRIPTION
C) "DECISION" PARAMETERS
D) COST FACTORS
PROCESS CALCULATIONS
A) PERFORMANCE - POLLUTANT
PARAMETER EFFECTS
R) EQUIPMENT SIZE
C) PROCESS COST
(NOT WITHIN
TOLERANCE LIMITS)
(RECYCLE SYSTEMS)
(NON-RECYCLE
SYSTEMS)
CONVERGENCE
A) POLLUTANT PARAMETER
TOLERANCE CHECK
(WITHIN TOLERANCE LIMITS)
COST CALCULATIONS
A) SUM INDIVIDUAL PROCESS
COSTS
B) ADD SUBSIDIARY COSTS
C) ADJUST TO DESIRED DOLLAR
BASE
OUTPUT
A)
STREAM DESCRIPTIONS -
COMPLETE SYSTEM
B)
INDIVIDUAL PROCESS SIZE
AND COSTS
C)
OVERALL SYSTEM INVESTMENT
-------
EXHIBIT F-IV
U.S. Environmental Protection Agency
TYPICAL SYSTEM WITH SIX PAIR HASTE SYSTEMS
Mater Returned For Keuae
OPTIONAL RECTC1A
Spllla t Special
CHRCtllUH WASTEWATER
CHROMIUM
REDUCTION
Flocculation
Pinal
Neutral lzal
^Diichtrfi
Alkaline Waste Hater
CYANIDE
[Clarification
CYANIDE
OXIDATION
'loci
Wastewater
containing
Oil skli
wastewater
'containing
eaulai fled Oil
Burn
^ Reclain
-------
reference time. Such items as Construction Cost Index,
Wholesale Price Index, depreciation period, rate of
interest, cost of land, cost of labor, and cost of
electrical energy all must be specified. The option
exists to use any dollar base desired. The reference
time used for programming the various process costs
was January 1971.
The computer program main routine accepts the
control specifications and accesses all other routines.
Each wastewater treatment process is described by a
separate sub-routine which computes the performance and
cost of the individual process step (clarification,
oil skimming, etc.). The main routine iterates the
raw waste load data to a system component until the
last iteration is within the tolerance of the next to
last iteration. For example, the clarifier has a
sludge output to sludge dewatering. The water removed
from the sludge is put back to the clarifier, changing
the input concentration. This cycling is repeated
until the tolerances are met. When the system itera-
tion is complete, the main routine accesses a cost
summation routine.
The cost summation routine sums all the-process
costs and calculates the least cost treatment option.
They may be omitted if only process costs are desired.
-------
This routine also adjusts all costs to the speci-
fied year dollar base. Capital costs are adjusted by
the Sewage Treatment Plant Construction Cost Index.
Operation and maintenance costs are related to the
proper dollar base by use of the Wholesale Price Index
for "Industrial Commodities" and by use of the hourly
labor rate for non-supervisory workers in water, stream
and sanitary systems.
When the cost summation routine is complete, the
output routine is accessed. Output consists of a
process connection listing, a complete presentation
of the input and calculated stream pollutant parameter
values at the various stream locations, a summariza-
tion of all costs and performance by process, and an
overall system cost and effluent concentration table.
The output cost table shown in Exhibit F-V, on
the following page, includes: investment cost, de-
preciation, cost of capital, operating and maintenance
cost (less energy and power) and energy and power costs
as a function of effluent flow. The effluent concen-
tration table presents the selected parameters with
their respective wastewater treatment system influent
and effluent concentration expressed in units of
milligrams per liter.
-------
EXHIBIT F-V
U.S. Environmental Protection Agency
TYPICAL OUTPUT COST TABLE FOR WATER
EFFLUENT TREATMENT COSTS-BPT
COST
Flow Rate (Liters/Hr)
Investment
Annual Costs:
Capital Costs
Depreciation
Operation & Maintenance
Costs (Excluding Energy
6 Power Costs)
Energy & Power Costa
Total Annual Cost
7,885 15,771 39,427 157,708
$344,936 $398,924 $527,008 $1,063,173
16,912 19,559 25,839 52,127
34,494 39,892 52,701 106,317
34,207 38,451 49,965 103,675
10,064 20,139 50,383 201,531
$ 95,676 $118,041 $178,887 $ 463,650
PERFORMANCE
Effluent Pollutant
Parameters
PH
Total Suspended Solids
Cadmium
Chromium, Total
Copper
Fluoride
Iron
Lead
Nickel
Oil 6 Grease
Chemical Oxygen Demand
Phosphates
Zinc
Typical
Waste Load
Typical Effluent
Discharge Level
9.2
8.5
1220
mg/i
15.0
mg/1
2.4
mg/1
0.12
mg/1
18.9
»g/i
0.4
mg/1
4.5
mg/1
0.2
mg/1
8.5
mg/1
2.0
mg/1
9.0
mg/1
0.5
mg/1
2.0
mg/1
0.1
mg/1
3.4
mg/1
0.2
mg/1
668
mg/1
5.8
mg/1
3087
mg/1
92.6
mg/1
10.0
mg/1
2.6
mg/1
7.1
mg/1
0.5
mg/1
-------
4. TWO TYPES OF COST ASSUMPTIONS ARE INTEGRAL TO THE"
PROGRAM'S OUTPUTS
This section presents the two types of cost assumptions
underlying the cost estimating routines described in the
prior section. There are process cost assumptions which
specify and size the abatement components, and there are
system cost assumptions which also affect the magnitude of
costs.
(1) Process Costs
The following process cost elements are built into
the modeling capability of the programs
Cyanide Oxidation
The cyanide oxidation tank is sized as an
above-ground cylindrical tank with a reten-
tion time of four hours based on the process
flow. Since cyanide oxidation is considered
to be of the batch type for the cost estima-
tion program, two identical tanks are used
and priced by the program.
Cyanide removal is accomplished by the addi-
tion of sodium hypochlorite as needed to main-
tain the proper pH level. A 60 day supply
of sodium hypochlorite is stored in an in-
ground covered concrete tank, 1 foot (.305
meters) thick. A 90 day supply of sodium
hydroxide is also stored in an in-ground
covered concrete tank, 1 foot (.305 meters)
thick.
When using a continuous system for batch
cyanide treatment, the system includes:
2 immersion pH probes and transmitters
2 immersion ORP probes and transmitters
-------
2 pH and ORP monitors
2 2-pen recorders
2 slow process controllers
2 proportional sodium hypochlorite pumps
2 proportional sodium hydroxide pumps
2 mixers
3 transfer pumps
1 maintenance kit
2 liquid level controllers and alarms,
and miscellaneous electrical equipment
and piping
A complete manual control system is costed
for the batch treatment alternative. This
system includes:
2 pH probes and monitors
1 mixer
1 liquid level controller and horn
1 proportional sodium hypochlorite pump
1 on-off sodium hydroxide pump and PVC
piping from the chemical storage tanks
Manpower estimates for operation and main-
tenance reflect the varying schemes for con-
tinuous and batch operation.
Mixer power requirements for both continuous
and batch treatment are based on 2 horsepower
for every 3,000 gallons of tank volume.
The mixer is assumed to be operational 25
percent of the time that the treatment sys-
tem is operating.
Chromium Reduction
For both continuous and batch treatment, sul-
furic acid is added for pH control. A 90
day supply is stored in the 25 percent aqueous
-------
form in an above-ground, covered, concrete
tank 1 foot (.305 meters) thick. A constant
power requirement of 2 horsepower is assumed
to mix the chemicals.
For batch chromium reduction, the dual chro-
mium reduction tanks are sized as above-
ground cylindrical concrete tanks, 1 foot
(.305 meters) thick, with a 4 hour retention
time, and an excess capacity factor of 1.2.
Sodium bisulfite is added to reduce the hex-
avalent chromium.
For continuous chromium reduction, the single
chromium reduction tank is sized as an above-
ground cylindrical concrete tank with a 1
foot (.305 meters) wall thickness, a 45
minute retention time, and an excess capacity
factor of 1.2. Sulfur dioxide is added to
convert the influent hexavalent chromium to
the trivalent form.
The control system for continuous chromium
reduction consists of:
1 immersion pH probe and transmitter
1 immersion ORP probe and transmitter
1 pH and ORP monitor
2 slow process controllers
1 sulfonator and associated pressure
regulator
1 sulfuric acid pump
1 transfer pump for sulfur dioxide
ejector
2 maintenance kits fox electrodes, and
miscellaneous electrical equipment and
piping
A completely manual system is provided for
batch operation. Subsidiary equipment
includes:
1 sodium bisulfite mixing and feed tank
1 metal stand and agitator collector
1 sodium bisulfite mixer with disconnects
-------
1 sulfuric acid mixer with disconnects
1 sulfuric acid pump
2 immersion pH probes
1 pH monitor and miscellaneous piping
Manpower estimates for operation and main-
tenance reflect the varying schemes for
continuous and batch operations.
Clarification
Clarification is employed for solids removal
where land is available outside the plant for
a treatment system. Clarification may be
either continuous or batch treatment. Lime
and sodium sulfide are added for metal and
solids removal and pH adjustment.
For continuous clarification with an influent
flow rate greater than or equal to 2600
gallons per hour (9,857 liters per hour)r
costs include a concrete flocculator and its
excavation, and two centrifugal sludge pumps.
The flocculator size is based on a 45 minute
retention time, a length to width ratio of
5, a depth of 8 feet (244 meters), a thick-
ness of 1 foot (.305 meters), and an excess
capacity factor of 1.2. A mixer is included
in the flocculator. The settling tank is
sized by a design hydraulic loading of 33.3
gallons per hour per square foot (1356.7
liters per hour per square meter), a 4 hour
retention time, and an excess capacity fac-
tor of 1.2.
For continuous clarification with an influent
flow rate less than 2,600 gallons per hour
(9,857 liter per hour), the flocculator and
settling tank are each replaced with an above-
ground conical, unlined carbon steel tank
with a 4 hour retention time. The dual
centrifugal sludge pumps are retained.
The sludge pumps are assumed operational 1
hour for each 12 hours of production opera-
tion and have 20% excess pumping capacity.
Costs include motors, starters, alternators,
and necessary piping.
For batch clarification, the dual centrifugal
sludge pumps and the chemical demands are
identical to continuous clarification. The
-------
flocculator and settling tank, however, are
replaced with dual above-ground cylindrical
carbon steel tanks, each tank with an 8 hour
retention time, an excess capacity factor of
1.2, and a mixer that operates 1 hour for each
8 hours that the tank is being used. All
power requirements are based on data from
major manufacturers.
Diatomaceous Earth Filtration
Diatomaceous earth filtration is used in
place of clarification for those plant models
which have no land available outside the
plant for a treatment system. Unit cost is
based on one filter station comprised of one
filter, one mix tank, two pumps, and asso-
ciated valving. The unit is shut down one
hour each day of operation for cleaning and
filter pre-coating. Diatomaceous earth ad-
dition rates, power requirements, and man-
power requirements are based on manufacturer's
data.
pH Adjustment
pH adjustment is used for treatment at plants
that discharge to a municipal treatment sys-
tem. When used, the pH adjustment tank is
an in-ground concrete tank with a 5 minute
retention time. The tank has a width ratio
of 5, a depth of 8 feet (2.44 meters), a
thickness of 1 foot (.305 meters), and an ex-
cess capacity factor of 1.2. A mixer and
tank excavation are included in the costs.
Lime is added to obtain the desired effluent
pH. Mixer power is based on a representa-
tive installation with 1 turnover per minute.
Sludge Drying Beds
Sludge drying beds are sized by a drainage
rate of 0.0078 gallons per hour per square
foot (0.318 liters per hour per square meter)
with a bed excavated to a depth of 4 feet
(1.2 meters) and an excess capacity factor
of 1.5. Costs include berms, underdrain
piping, and all required gravel and sand.
The unit is not sized for any influent flow
rate less than 50 gallons per day (189 liters
per day) as the bed area becomes too small
to warrant construction.
-------
Contractor Hauling
A flat rate of $42 per pick-up with a 15
cubic yard (11.5 cubic meters) capacity truck
is charged for a January 1976 dollar base.
This charge assumes that an appropriate
landfill is available at no charge and no
further treatment of the wastes is required.
Hauling costs are applied to the solids exit-
ing from the solids removal devices in con-
tinuous and batch treatment systems and are
applied to the total wastewater discharge
flow when analyzing "haul" as a least cost
system option.
(2) System Cost Assumptions
Section (1) presented the individual process
cost elements. Subsidiary costs, however, must be
included for any wastewater treatment system to be
complete. This section presents all system sub-
sidiary cost assumptions incorporated in the routines.
Each cost assumption can be modified in use to satisfy
any alternative set of conditions or assumptions.
Dollar Base
A dollar base of January 1976 is used for all
costs, investment costs are adjusted to this
dollar base by use of the Sewage Treatment
Plant Construction Cost Index from Reference
4. The national average of the Construction
Cost Index for January 1976 is 256.7.
Supply costs, such as chemicals, are related
to the dollar base by the "Industrial Com-
modities" Wholesale Price Index presented
in Reference 5. For January 1976, this index
is 177.3.
To relate operating and maintenance labor
costs, the hourly wage rate for non-supervisory
-------
workers in water, stream, and sanitary sys-
tems is used from Reference 6. This wage
rate is $5.19 per hour in January 1976.
This wage rate is then applied to estimates
of operational and maintenance man-hours
required by each process to obtain process
direct labor charges. To account for in-
direct labor charges, 15% of the direct
labor costs is added to the direct labor
charge to yield estimated total labor costs.
Such items as Social Security, employer con-
tributions to pension or retirement funds,
and employer-paid premiums to various forms
of insurance programs are considered indi-
rect labor costs.
Energy and Power
Energy and power requirements are calculated
directly within each process. Estimated
costs are then determined by applying a rate
of approximately 2.7 cents per kilowatt hour.
The electrical charge for January 1976 was
corroborated through consultation with the
Energy Consulting Service Department of the
Connecticut Light and Power Company. This
electrical charge was determined by assuming
that any electrical needs of a waste treat-
ment facility would be satisfied by an ex-
isting electrical distribution system? i.e.,
no new meter would be required.
Capital Recovery
Capital recovery costs are divided into de-
preciation and cost of capital. Deprecia-
tion is programmed for a straight line 5
year depreciation period consistent with the
faster write-off (financial life) allowed
by the IRS for these facilities, even though
the equipment life is in the range of 20 to
25 years. Cost of capital is calculated by
use of the capital recovery factor at a 10%
annual interest rate applied for a period
of 5 years.
The capital recovery factor (CPR) is normally
used in industry to help allocate the initial
-------
investment and the interest to the total
operating cost of the facility. The (CFR)
is equal to the interest rate plus the in-
terest rate divided by A-l. A is equal to
the quantity 1 plus the interest rate raised
to the nHI power, where n is the number of
years the interest is applied. The annual
capital recovery (ANR) is obtained by multi-
plying the initial investment by the CFR.
The annual depreciation (D) of the capital
investment is calculated by dividing the
initial investment by the depreciation
period N, which is assumed to be five years.
The annual cost of capital is then equal to
the annual capital recovery (ANR) minus the
depreciation (D).
Line Segregation
These costs account for plant modifications
to segregate waste if the wastes are present
in the wastewater discharge. The maximum
number of streams to be segregated is 1 less
than the total number of waste streams en-
tering the treatment system. This assumes
that one general wastewater discharge point
already exists at the plant. For example,
if a plant has cyanide bearing wastes, chro-
mium bearing wastes, and general wastewater,
2 lines would be the maximum number of
streams to be segregated. If the plant
model, however, indicates that either cyanide
oxidation or chromium reduction is already
in place, line segregation costs for this
process (es) already in place are ignored.
The investment costs of line segregation in-
clude placing a trench in the existing plant
floor and installing the lines in this trench.
The same ditch is used for all pipe and a
gravity feed to the treatment system is as-
sumed. The piping is assumed to run from
the center of the floor to a corner. Plant
floor area is related to discharge flow by
the results of an analysis of 300 plants
visited for which flow and floor area are
available. This data indicated that .05
gallons per hour of wastewater is discharged
per square foot of floor area (2.04 liters
per hour per square meter).
F-23
-------
Administrative and Laboratory Facilities
This item is the cost of constructing space
for administration, laboratory, and service
functions for the wastewater treatment sys-
tem. All the plant models executed for
electroplating economic impact analysis al-
ready had an existing building and space
for administration, laboratory, and service
functions. Therefore, there is no invest-
ment cost for this item.
Garage and Shop Facilities
For the industrial waste treatment facili-
ties being costed, the garage and shop in-
vestment cost is assumed to be part of the
normal plant costs and was not allocated to
the wastewater treatment system.
Laboratory Operations
An analytical fee of $80 (January 1976 dol-
lars) is charged for each wastewater sample,
regardless of whether the laboratory work
was done on or off site. This analytical
fee is typical of the charges experienced
by Hamilton Standard during the past several
years of sampling programs.
The frequency of wastewater sampling is a
function of wastewater discharge flow and
is presented in Table F-3, on the follow-
ing page. This frequency was suggested by
the Water Compliance Division of the USEPA.
Yardwork
The yardwork investment cost item includes
the costs of general site clearing, inter-
component piping, valves, overhead and un-
derground electrical wiring, cable, light-
ing, control structures, manholes, tunnels,
conduits, and general site items outside
the structural confines of particular indi-
vidual plant components. Thj.s cost is
typically 9-18 percent of the installed com-
ponent investment costs. For these cost
estimates, an average of 14 percent is
utilized. Yardwork operation and mainte-
nance costs are considered a part of normal
plant maintenance and are not included in
these cost estimates.
-------
Table F-3
Wastewater Sampling Frequency
Wastewater Discharge Flow
(gallons per day)
0 - 10,000
10,000 - 50,000
50,000 - 100,000
100,000 - 250,000
250,000 +
Sampling Frequency
once per month
twice per month
once per week
twice per week
thrice per week
-------
Land
The wastewater treatment system land require-
ments are calculated allowing a 10-foot (3-
meter) perimeter around each treatment sys-
tem component and a 5-foot (1.5-meter)
perimeter around each chemical storage tank.
Land is then bought in 5r000 square foot
(464.5 square meter) segments to satisfy the
land requirements. If a plant already has
land available for its wastewater treatment
system, this land cost iB set to $0.
The locale of the plant also affects land costs.
The following local relationships, as shown in
Table F-4 below, are assumed to determine land
costs.
Engineering
Engineering costs include both basic and
special services. Basic services include
preliminary design reports, detailed design,
and certain office and field engineering
services during construction of projects.
Special services include improvement studies,
resident engineering, soils investigations,
land surveys, operation and maintenance
manuals, and other miscellaneous services.
Engineering cost is a function of process
installed and yardwork costs as presented
in Reference 7. This charge has also been
substantiated by data supplied by the Con-
necticut Engineers in Private Practice.
Legal, Fiscal, and Administrative
These cost8 relate to planning and construc-
tion of wastewater treatment facilities and
include such items as preparation of legal
Table F-4
Locale - Land Cost Relationships
Locale $/acre (January 1976 dollars)
Urban
Suburban
Rural
75,000
10,000
2,000
-------
documents, preparation of construction con-
tracts, acquisition of land, etc. These
costs are a function of processes installed
yardwork, engineering, and land costs.
Interest During Construction
The dollar value calculated for this item
consists of the interest cost accrued on
funds from the time payment is made to the
contractor to the end of the construction
period. The total of all other project
costs: (processes installed, yardwork,
land, engineering, legal, fiscal and admin-
istrative) and the applied interest affect
this cost.
An interest rate of 10% is used to determine
the interest cost for these estimates.
5. THERE ARE SEVERAL SPECIAL CONDITIONS, IF NOT
LIMTTATIONS, TO THE ROUTINE'S APPLICABILITY"
The results of the cost program generally agree with
known costs to within + 20 percent* Comparisons of the
program estimates to actual plant data (for comparable
wastewater treatment equipment) have been conducted for
the Agency within the last year. Consistently, the sets
of costs show high levels of agreement.
In addition, the sensitivity of the cost estimates
to several variables is demonstrated in the program output.
The variables reviewed include plant size (as modeled by
wastewater discharge), treatment-in-place, and applied ef-
fluent discharge standards (as modeled by the various
estimation modes).
-------
There are, however, certain lixnitatione associated with
extrapolating the model plant cost estimates to the universe
of job shop electroplaters. These limitations are discussed
in detail below.
The cost program calculates a nationwide, general
cost of wastewater treatment system installation
and operation applicable for average situations.
Costs of unusual construction requirements, such
as foundation piling, rock excavation, or dewatar-
ing, have not been included in the general cost
estimates. Any one plant could experience instal-
lation costs far different from those estimated
by the program.
Plant alteration costs have only been estimated
in part. Line segregation costs have been esti-
mated per the procedure discussed in Section 2,
above, and are dependent on the floor area, floor
plan, and distance to the wastewater treatment
facilities.
Special plant alteration costs, such as the build-
ing of a mezzanine, the removal of a wall, or the
strengthening of a floor were not estimated due
to the special, unique nature of this type of
alteration for each plant. Again, high cost
variability on this item would be expected.
The haul costs calculated by the program include
transport costs only. It was assumed that a
suitable landfill was available at no cost and
that no further treatment of the wastes was re-
quired. The transport cost was corroborated by
a local Connecticut hauler. To the extent that
there is an added cost for treatment, then the
program will understate the full costs of that
treatment mode.
* * * *
This appendix has presented the logic, methodology
and limitations of the computerized cost estimating routine
developed by Hamilton Standard. Use of this program has
-------
enabled the present economic impact study to incorporate
highly reliable estimates of pollution abatement system
costs.
-------
-------
Plant f
Electroplating Operation
5f
MT Ni. Cr. Gold
ICS Cadmium
3n
52
US
334
152
353
347
355 Cu. Mi. Solder, Tin.
Gold. Silver, Cobalt
302 Cu. Ni. Cadmium. Zn.
Tin
Source: Boot. Allen fi inc.
EXHIBIT G-I
D. S. Environmental Protection Agency
PLANTS WITH CLARIFIER ONLY
Treatment Equipment
Fini ahing Operation
Anodizing
Chemical milling and
chemical
Bright dip. stripping
Chromting
Anodizing, coloring.
phoephatlng. chromat-
lng, non-aqueous plating,
bright dip. rh—leal
etching. stripping
Chemical milling, chemi-
cal etching, stripping
Chemical etching
Phoephating. stepping
etching
Anodizing, coloring
Previously Installed
pH adjustment, Cr, separate
hex Cr stream
CN. counter current rinse
pH'adjustment, flow equaliza-
tion. Cr. separate hex Cr
stream, countercurrent rinse
pH adjustment, lagoon
pH adjustment, flow equaliza-
tion, Cr. lagoon
pH adjustment, clarifier,
pH adjustment, clarifier,
countercurrent rinse
Blectroleee on metals and
plastics, bright dip, chemi-
cal etching, stripping
Anodizing, coloring, phosphat-
ing. chromating. electroless on
metals, bright dip, chemical
etching, stripping
pH adjustment. CN, aepaiats CI
stream, advanced treatment
-------
VALIDATION OF THE POLLUTION
ABATEMENT COST ESTIMATES
This appendix presents the methodologies employed by
Booz, Allen for interpolating technical contractor's cost
estimates for the initial 74 model plants. As stated in
the- methodology chapter, several analytic steps were re-
quired to derive generalized predictor equations from these
74 model plants for use on all models of the impact anal-
ysis. Specifically, the following was done:
Operations were grouped by common processes to
find basic treatment equipment requirements
Flow allocation rules were derived on a per
treatment component basis
Cost equations were developed on a water flow
sizing measure
Costs derived by the equations were tested
against the routine and outside sources
The next four sections provide the data and analyses
of each activity.
1. TREATMENT EQUIPMENT REQUIREMENT
The four exhibits which follow, G I-IV, contain the
raw data from which treatment equipment requirements rules
-------
Plant f
364
Electroplating Operation
142
423 Cu/Ni,/Cr
308 Ni/Cr
271
34
111 Ni/Cr
66
123 Ni. Cr, Zn
162
94
Stripping
EXHIBIT G-II
U. S. Environmental Protection Agency
fLANTS WITH CHROME REDUCTION
AND CLARIFTER
Finishing Operation
Treatment Equipment
Previously Installed
Anodizing, coloring,
phosphating, chromat-
ing. bright dip. chemi-
cal etching, stripping
pH adjustment
Anodizing, coloring,
bright dip. chemical
etching, stripping
Lagoon
Anodizing, coloring, pH adjustment, Cr, clarifier
chromating, bright dip,
chemical etching, strip-
ping
Chromating, chemical
etching
Anodizing, coloring,
chemical etching. strip-
ping
Chromating
pH adjustment. Cr. clarifier,
countercurrent rinse
Anodizing, coloring,
phosphating, chromating,
chemical etching
Anodizing, coloring,
chromating, bright dip,
chemical etching, strip-
ping
pH adjustment, flow equalization
Cr, lagoon, separate hex Cr stre.
pH adjustment, flow equalization,
-------
Plant #
231
14
47
15
303
414
331
281
391
128
159
316
187
Electroplating Operation
Cu. Ni. Cr
Cr
Cr. Zn
Cu. Ni, Cr
Cu. Ni. Cr
Cu, Ni. Cadmium. 7n, Tin
Finishing Operation
Stripping
Stripping
Phosphating, chroma t-
ing
Phosphating, chromat-
ing, chemical milling.
bright dip, chemical
etching, stripping
Anodizing, coloring.
bright dip, chemical
etching
Phosphating, chromat-
ing
Anodizing
EXHIBIT G-II (2)
Treatment Equipment
Previously Installed
pH adjustment, flow equalization,
CN
countercurrent rinse, advanced
treatment
Anodizing, coloring,
chroma ting
Flectroless on plastics
Anodizing, coloring,
phosphating, chroznating
pH adjustment. lagoon
pH adjustment, flow equalization
lagoon, separate CN stream, cam
current rinse
Anodizing, coloring,
bright dip
pF. Cr, lagoon. separate hex Cr
-------
Plant #
Electroplating Operation
215
348 Ni, Cr, Cadmium. Zn
212 Cu. Ni. Cr
149
Source: Booz, Allen 8 Hamilton foe.
Finishing Operation
Anodizing, bright dip
Anodizing, chromat-
ing, stripping
EXHIBIT G-II (3)
Treatment Equipment
Previously Installed
pH adjustment. CN, clarifier,
countercurrent rinse
-------
Plant f Electroplating Operation
79 Co. Ni. Gold, Silver
30 Platinum
59 Cu, Ni, Tin, Gold. Silver
Brass
332 Cu. Ni, Tin. Gold. Silver
Platinum
44 Cu. Ni. Cr. Gold. Silver,
Brass
45 Cu, Ni, Cadmium. Zn
39 Cadmium, Zn
Source: Booz, Allen 8 Hamilton. Inc.
Finishing Operation
Stripping
EXHIBIT G-III
U. S. Environmental Protection Agency
PLANTS WITH CYANIDE DESTRUCTION
AND CLARIFIERS
Treatment Equipment
Previously Installed
Electroless on metals, Clarifier, counter current rinse,
bright dip, stripping advanced treatment
Electroless on metals
Electroless on plastics Cr, separate hex Cr stream.
countercurrent rinse, advanced
treatment
Anodizing, coloring
phosphating, bright
dip
-------
Plant ~
289
80
151
25
46
257
312
305
1«4
373
345
188
Electroplating Operation
Cu. Ni. Cr. Tin. Silver,
Brass and Bronze
Cu. Ni. Cadmium, Zn,
Tin, Brass and Bronze
Cu. Ni, Cr, Cadmium,
Bronze
Cu. Ni. Cr, Gold
Cu, Zn
Cu. Ni. Cr. Gold. Silver,
Brass
Cu, Ni. Cr, Zn, Gold, Brass
Cu. Ni. Cr, Cadmium, Zn,
Tin
Cu. Ni. Cr. Cadmium. Zn.
Tin, Gold. Silver, Brass,
Bronze
Ni, Cr, Cadmium, Lead,
Tin. Silver
Cu. Ni, Cr, Cadmium, Zn,
Tin. Gold, Silver. Platinum
Ni. Cr, Zn
EXHIBIT G-IV (1)
U.S. Environmental Protection Agenc)
PLANTS WITH FULL BPT SYSTEMS
Treatment Equipment
Finishing Operation Previously Installed
Bright dip. stripping
Phosphating, chromatins,
bright dip, stripping
pH adjustment, flow equalizatioi
Cr, CN. clarifier, counter curre:
advanced treatment
Chromating, electroless
on metals, stripping
Chromating. bright dip,
stripping
Stripping
Chromating, bright dip
Anodizing, coloring,
phosphating, chromating,
bright dip, chemical etch-
ing, stripping
Electroless on metals C^lfier, coun ter current rinse
Coloring, phosphating,
chromating, electroless
on metals, bright dip,
chemical etching, strip-
ping
Chromating. stripping
-------
Plant > Electroplating Operation
386 Cu, Ni, Cr, Cadmium, Zn.
Solder, Tin
110 Ni. Cr. Zn
26 Cu, Ni, Cr
235 Cu. Ni. Cadmium. Solder,
Tin, Gold, Silver. Platinum
129 Cadmium, Zn
358 Cu, Ni, Cr, Brass
344 All electroplating
76 Zn
55 Cu, Ni, Cr, Cadmium, Zn,
Gold, Silver, Platinum, brass
143 Cadmium. Zn, Lead, Brass
346
Cadmium, Zn
EXHIBIT G-IV (2)
Finishing Operation
Anodizing, coloring,
chromating, phosphat-
ing. electroless on
metals, chemical etch-
ing. stripping
Chromating
Treatment Equipment
Previously installed
Anodizing, coloring,
chromating, electroless
on metals, bright dip.
stripping
Chromating
Stripping
Chromating. electroless
on plastics and metals,
bright dip. milling, strip-
ping
Anodizing, coloring, phos-
phating. chromating, bright
dip, chemical etching, strip-
ping
Anodizing, coloring, chromat-
ing. electroless on metals, bright
dip. stripping
Phosphating. chromating,
bright dip
pH adjustment
pH adjustment, flow equaliza-
tion, clarifler
pH adjustment, clarifler
pH adjustment, flow equaliza-
tion, Cr. CN. clarifler,
CN stream, separata
Anodizing, coloring, chromat-
ing , bright dip, chemical etch-
ing. stripping
-------
Plant § Electroplating Operation
340 Ni, Cr, 2n, Brass
82 Cr. Za
136 Cu, Ni, Cr. Zo, Cadmium
Source: Booz, Allen 8 Hamilton Inc.
EXHIBIT G-IV (3)
Finishing Operation
Chroma ting. stripping
Phoephating. chromat-
ing
Treatment Equipment
Previously Installed
pH adjustment, Cr, CN. lagoon,
separate stream, countarcurrent
rinse
Phosphating. ctaromating. Have everything
electrolesa on metals,
-------
were derived. Inspection of these exhibits provided the
basis for developing the following decision rules:
Plants involved only in sulfuric acid anodizing,
and/or nonelectroplating metalfinishing opera-
tions (except chromating and bright dipping)
were likely to require pH adjustment only to
meet BPT requirements.
Plants involved only in copper, tin, cadmium,
zinc, precious metal plating or bright dipping
or a combination thereof were likely to require
cyanide destruction and pH adjustment equipment.
Plants involved only in chromium plating, chro-
mic acid anodizing, chromating or a combination
thereof were likely to require hexavalent chro-
mium reduction and pH adjustment equipment.
Other plants doing combinations of these opera-
tions were likely to require all three major
systems: cyanide destruction, hexavalent chro-
mium reduction, and pH adjustment.
Line segregation was assumed to be required when
two or more pieces of equipment were required.
In cases where only two pieces of equipment were
required or because of previously installed
equipment, one-half of the total estimated line
segregation costs was likely.
The exhibits also show the treatment equipment which
the survey respondents indicated had been installed at
their shops. Again inspection of the exhibits shows that
the decision rules for predicting equipment appear to be
reasonably consistent with practice in the field.
2. FLOW ALLOCATION RULES
Exhibits G V-VIII on the following pages show the flow
of process water through the pollution abatement units.
-------
Percenc of
Plant Metal Finishing
No. Water to Cyanide Unit
79 69.5
59 62.1
332 62.9
44 20.1
45 78.0
91 15.6
18 67.4
39 73.8
Average percentage to Cyanide Destruction Unit
Standard Deviation
Source: Booz, Allen & Hamilton Inc.
EXHIBIT G-V
U.S. Environmental Protection Agency
PERCENTAGE OF FLOW TO CYANIDE
DESTRUCTION UNIT FOR PLANTS INSTALLING
CYANIDE DESTRUCTION AND pH ADJUSTMENT EQUIPMENT '
Operations
Copper, Nickel, Gold, Silver
Copper, Nickel, Tin, Gold, Silver Brass,
electroless on metals, bright dip
Copper, Nickel, Tin, Gold, Silver, Platinum,
electroless on metals
Copper, Nickel, Chromium, Gold, Silver
Brass, electroless on plastics, (Chrome
Reduction Unit already installed)
Copper, Nickel, Cadmium, Zinc
Brass, Bronze, flemish oxidizing
bright dipping, chromating
Copper, Nickel, Cadmium, Zinc, chromating,
bright dipping, chemical etching
Cadmium, Zinc, anodizing, phosphating,
bright dip (Chrome reduction unit
previously installed)
56.2%
-------
364
142
308
271
34
111
66
162
94
14
47
15
EXHIBIT G-VI (1)
U.S. Environmental Protection Agency
PERCENTAGE OF FLOW TO CHROME REDUCTION
UNIT FOR PLANTS INSTALLING HEXAVALENT CHROMIUM
REDUCTION AND PH ADJUSTMENT EQUIPMENT
Percentage of
Metalfinishing Water
To Hexavalent Chromium
Reduction Unit (%) Operations
33.4 Anodize, color, phosphating, chromating, bright dip
chemical etch
43.8 Anodize, color, bright dip, chemical etch
9.9 Nickel, Chromium
24.1 Anodize, color, chromating, bright dip, chemical etch
19.9 Chromating, chemical etch
9.9 Nickel, Chromium
37.2 Anodize, color, chemical etch, strip
20.2 Anodize, color, phosphating, chromating chemical etch
37.2 Anodize, color, chromating, bright dip, chemical etch,
strip
6.3 Chromium, strip
26.0 Phosphating, chromating
2.9 Phosphate, chromating, chemical mill, bright dip,
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EXHIBIT G-VI (2)
303 23.7 Anodize, color, bright dip, chemical etch
414 8.9 Phosphating, chromating.
331 58.9 Anodize
281 4.5 Chromium, Zinc (CN destruct in place)
391 6.3 Copper, Nickel, Chromium (Advanced treatment replace)
128 46.7 Anodize, Color, Chromating
159 6.7 Copper, Nickel, Chromium, electroless on plastics
316 6.6 Copper, Nickel, Cadmium Zinc, Tin, anodize, color
phosphating, chromating (CN destruct in place)
187 56.7 Anodize, color, bright dip
348 1.7 Nickel, Chromium, Cadmium, Zinc (CN destruct in place)
149 37.3 Anodize
Average Percentage of Flow to Hexavalent Chromium Reduction Unit = 23.0%
Standard Deviation = 17.8%
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EXHIBIT G-VII (1)
U.S. Environmental Protection Agency
PERCENTAGES OP FLOW TO CYANIDE DESTRUCTION
AND CHROME REDUCTION UNITS FOR FULL BPPT SYSTEMS
— COMPLEX PLANTS
Percentage of Metal Finishing Water to
Plant Cyanide Destruction Chrome Reduction
No. (%) (%) Operation
289 19.0 2.9 Copper, Tin, Nickel, Chromium, Silver,
Brass, Bronze, bright dip, strip
80 61.0 - Copper, Nickel Cadmium, Zinc, Tin,
Brass, Bronze, phosphating, chromating,
bright dip, strip (Chrome reduction
previously installed)
151 64.7 3.9 Copper, Nickel, Chromium, Cadmium, Bronze,
Chromating, electroless on metals, strip
392 66.3 0.7 Copper, Nickel, Chromium, Zinc, Gold,
Brass
305 61.0, 2.9 Copper, Nickel, Chromium, Cadmium, Zinc,
Tin, Chromating, bright dip
373 79.9 0.2 Nickel, Chromium, Cadmium, Lead, Tin,
Silver, electroless on metals
345 56.2 3.5 Copper, Nickel, Chromium, Cadmium, Zinc,
Tin, Gold, Silver, Platinum, coloring,
phosphating, chromating, electroless
on metals, bright dip, chemical etching,
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386
64.2
7.7
235 71.1 6.4
344 64.7 0.2
55 76.0 5.4
346 57.1 11.4
Average Percentage of Flow to Cyanide Destruction Dnit =
Standard Deviation - 15.2%
Average Percentage of Flow to Hexavalent Chromium Reduction
Standard Deviation = 3.4%
Source: Booz, Allen & Hamilton Inc.
EXHIBIT G-VII (2)
Copper, Nickel, Chromium, Cadmium,
Tin, Silver, Zinc, anodizing, coloring,
chromating, phosphating, electroless
on metals, chemical etching, strip
Copper, Nickel, Cadmium Solder, Tin,
Gold, Silver, Platinum, anodizing,
coloring, chromating, electroless on
metals, bright dip, strip
All electroplating and metal finishing
operation
Copper, Nickel, Chromium, Cadmium, Zinc,
Gold, Silver, Platinum, Brass, anodizing
coloring, chromating, electroless on
metals, bright dip, strip
Cadmium, Zinc, anodizing, coloring,
bright dip, chromating, chemical etching,
strip
61.8%
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EXHIBIT G-VIII
U.S. Environmental Protection Agency
PERCENTAGE OF FLOW TO CYANIDE DESTRUCTION
AND CHROME REDUCTION UNITS FOR FULL BPPT
SYSTEMS—SIMPLE PLANT CONFIGURATION
Percentage of Metal Finishing Water to
Plant Cyanide Destruction Chrome Reduction
No. (%) (%) Operation
287 9.8 4.6 Copper, Nickel, Chrome, Gold, Silver,
188 3.4 12.6 Nickel, Chrome, Zinc, chromating, strip
110 9.9 17.9 Nickel, Chrome, Zinc, chromating
26 5,9 9.6 Copper, Nickel, Chrome
340 9.2 3.2 Nickel, Chrome, Zinc, Brass, chromating
82 10.2 10.9 Chrome, Zinc, phosphating, chromating
Average Percentage of Flow to Cyanide Destruction Unit =8.1%
Standard Deviation = 2.8%
Average Percentage of Flow to Hexavalent Chromium Reduction Unit = 9.8%
Standard Deviation <= 5.4%
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Inspection of the flow volumes provided the basis for the
following allocation rules:
Plants requiring installation of cyanide de-
struction and pH equipment tend to have about
56% of their metalfinishing water flowing to
the cyanide destruction unit.
Plants requiring installation of hexavalent
chromium reduction and pH adjustment equipment
tend to have about 23% of their metalfinishing
water flowing to the chrome reduction unit.
Plants requiring installation of full BPPT sys-
tems fall into two categories:
Plants which perform more them six opera-
tions tend to have about 62% of their
metalfinishing water flow in the cyanide
destruction unit and about 4% of their
metalfinishing water flowing to the hexa-
valent chromium reduction unit.
Plants with six or fewer operations tend
to have about 8% of their metalfinishing
water flow to the cyanide destruction unit
and about 10% flowing to the hexavalent
chromium reduction unit.
In all cases all the metalfinishing water flows
through the pH adjustment unit.
3. COST EQUATIONS
Computer cost estimates were regressed against flow
volume in gallons per hour. This process was repeated for
each individual component. In this manner each component
had its own cost predictor equation. The regression lines
and the formulae appear in Chapter II. Only the basic cost
equations are repeated here in Exhibit G IX, on the next
page.
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EXHIBIT G-IX
U.S. Enviroimental Protection Agency
EQUATIONS RELATING ESTIMATES OF INVESTMENT FOR
HATER TREATMENT WITH GALLONS PER HOUR OF MATER TREATED
Subsysten
Hexavalent Chromium Reduction ;2»
Cyanide Destruction
pH Adjustment
Line Segregation
Clarifier
Diatomaceous Earth Filter
Equation*
Investment ($) = 8,400 GPH 0.17
Investment ($) « 19,000 + 15.2 GPH
Investment ($) * 14,700 -(-1.0 GPH
Investment ($) 210 GPH 0.5
Investment ($) * $16,000 GPH 0.15
Investment ($) =* $4,065 GPH 0.33
Correlation Statistic
0.8
0.9
0.9
*Notes on Equations
1. Investment value in 1977 dollars.
2. GPH is the metalfinishing water to specific unit.
3. GPH is the total metalfinishing water of the plant.
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4. TESTING OF DERIVED COST ESTIMATES
Given that the regression equations are best fit re-
lationships to the costs reported by the technical con-
tractor, they tend to agree closely with those estimates.
The utility of the cost equations rests not with how well
they predict back to the data base, but rather with how
well they predict to external sources.
Exhibit G X on the next page shows a comparison of
supplier generated quotations and regression equation
costs on a per component basis. This limited survey of
equipment suppliers yields the following:
At worst, the budgetary quotation from small
capacity hexavalent chromium reduction units
exceeds the model estimated cost by 33%.
For hexavalent chromium reduction units, the
average percentage difference between model
estimates and budget quotes was 13%.
For cyanide oxidation units, the average per-
centage difference between model estimates and
quotes was about 7%.
For clarifiers, the average percentage dif-
ference between model estimates and budget
quotes was about 13%.
Given that the Technical Contractor's original com-
ponent costs come from suppliers, and the regression
equations agree closely with the computer generated costs,
there is every reason to believe that the study can accu-
rately predict a firm's pollution abatement costs.
* * *
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EXHIBIT G-X
U.S. Environmental Protection Agency
COMPARISON OF SELECTED ESTIMATED
COST FOR POLLUTION CONTROL EQUIPMENT
AND BUDGETARY QUOTES BY SUPPLIERS
Equipment
Capacity
Model Estimated Cost
Budgetary Quotes by Supplier
Item
(GPH)
(Thousand)
(Thousand)
Chromium Reduction
300
20
30
1,400
28
30
2,000
32
35
3,000
35
32
5,000
40
38
Cyanide Oxidation
300
24
29
500
17
30
1,000
33
33
1,500
36
35-41
3,000
94
94
Clarifier
1,000
46
60
10,000
66-105
82
(1) Tho suppliers provided quotes in chrood.ua reduction equipment. Three suppliers provided quotes on
cyanide oxidation equipment. One supplier provided quotes on clarifiers.
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