(Proceedings of the 1994 Steel Founders' Society of America Technical & Operating Conference, Chicago, IL, Nov. 9-12, 1994)

DIMENSIONAL VARIABILITY OF PRODUCTION STEEL CASTINGS

Frank E. Peters - Research Assistant John W. Ristey - Research Assistant Wayne G. Vaupel - Research Assistant

Edward C. DeMeter - Assistant Professor Robert C. Voigt - Associate Professor

Department of Industrial & Manufacturing Engineering The Pennsylvania State University University Park, Pennsylvania

ABSTRACT

Work is ongoing to characterize the dimensional variability of steel casting features. Data are being collected from castings produced at representative Steel Founders' Society o f America foundries. Initial results based on more than 12,500 production casting feature measurements are presented for carbon and how alloy steel castings produced in green sand, no-bake, and shell molds. A comprehensive database of casting, pattern, and feature variables has been developed so that the influence of the variables on dimensional variability can be determined. Measurement system analysis is conducted to insure that large measurement error is not reported as dimensional variability. Results indicate that the dimensional variability of production castin% features is less than indicated in current US (SFSA) and international (ISO) standards. Feature length, casting weight, parting line and molding process all strongly influence dimensional variability. Corresponding pattern measurements indicate that the actual shrinkage amount for casting features varies considerably. This variation in shrinkage will strongly influence the ability of the foundry to satisfy customer dimensional requirements.

DISTRIBUTION OF THIS DOCUMENT IS UMUMITEO

INTRODUCTION

To meet ever tightening customer demands for close-

tolerance, near-net-shape steel castings, the foundry must

exercise great control over pattern dimensi.ons, foundry process

variability, and measurement system variability. Ongoing work by

ROSS',' and the authors3 has strongly suggested that past ~tudies~*~*~

have overestimated casting dimensional variability. Past results

have been confounded by measurement errors. Widely used steel

casting tolerance specifications based on these

therefore do not accurately reflect the true dimensional -

capabilities of steel foundries. This has limited the market for

steel castings in precision applications. Less-than-adequate

pattern shrinkage allowances, and traditional trial and error

pattern correction methods also add unnecessary cost and lead

time to the initial casting approval process.

. . .

In this paper, first year results for an on-going three year

study of dimensional control of steel castings will be

summarized. The initial results presented here build on

measurement system analysis studies by Ross and early dimensional

studies by Peters and Voigt that have been reported

previou~ly.'~~~~~~~'~

based on dimensional surveys of production castings at member

foundries. To date, comprehensive data from 6 molding processes

from 4 foundries have been collected. This includes measurements

of 498 different casting features from 57 different castings.

The corresponding pattern feature measurements have also been

All of the results presented in this paper are

2

taken, when feasible. In most cases, features have been measured

on at least 20, and usually 30, different castings to determine a

specific feature's dimensional variability.

more than 12,500 individual measurements in the database. Data

from each casting and each feature have been compiled in a

comprehensive descriptors database to assist in the analysis and

interpretation of the data.

This corresponds to

Complete details of the database

structure, measurement system analysis techniques used, and

casting feature inspection procedures developed have been

previously rep~rted.~

All dimensional data collected to date have been compared to

existing casting dimensional tolerance specifications--the SFSA

I1Tl1 grades and IS0 specification^.^-^ It is important to note

that although these specifications predict similar tolerances for

casting features, the fundamental nature of the SFSA and IS0

dimensional tolerance specifications are different. The SFSA IfTii

grades predict feature dimensional variability based on feature

length and casting weight.

feature length to determine expected tolerance for a given

molding process.

The IS0 specification uses only

Data analyses presented in this paper are preliminary.

will be modified as additional dimensional data are added to the

database. The present database is expected to grow by a minimum

factor of 3 or 4 before the end of this focused effort. As the

size of the database increases, the statistical certainty with

which conclusions can be made will also increase.

They

However, it is

3

expected that many of the general trends in the data suggested

from these first year data will be reinforced with future data.

DESCRIPTION OF CURRENT DATABASE

The range of feature lengths and casting weights for green

sand, no-bake and shell casting dimensional features measured to

date at participating foundries is shown below.

MOLDING SMALLEST LARGEST PROCESS FEATURE LENGTH FEATURE LENGTH

inches (mm) inches (mm)

shell 0.25 ( 6.6) green sand 0.25 ( 6.5) no-bake 0.48 (12.3)

5.6 (141.6) , 11.6 (295.2) . 33.4 (848.4)

MOLDING SMALLEST LARGEST PROCESS CASTING WEIGHT CASTING WEIGHT

pounds (kg) pounds (kg)

shell 5 (2) 16 ( 7 ) green sand 2 (1) 228 ( 103) no-bake 9 ( 4 ) 2506 (1137)

Figure 1 graphically shows the size and weight distribution of

the castings measured for the various molding processes. These

feature size and weight distributions are typical of the size and

weight distributions of the industry. However, it is clear that

additional data are needed for larger castings and for large

features on castings of all weights. This data are needed to

allow for reliable statistical analyses of the entire size range

of castings produced in the industry. At the present time only

carbon and low alloy steel producers have participated in the

4

16 T o 0 00 0

00 0 0 0 a 0 0 0 0

0 0

0

0 0

0 0 0 0

0 0 0

0 . 0 0 0

2 t 0 1 1

0 1 2 3 4 5 6 FEATURE LENGTH (inches)

a)

250

0 0 0 0

0 0

0 0 0

0 0 0

0 0

b) 2 4 6 8

FEATURE LENGTH (inches)

10 12

2500

2000 1500 lo00

500

0

0 0 0

_ _ 0

Q O

03 0 0

0 0

0 8

h 0 . O O 0

1

0 5 10 15 20 25 30 35 FEATURE LENGTH (inches) C )

Figure 1: Feature length and casting weight distribution of casting features measured for various molding process a) shell mold castings b) green sand castings c) no-bake mold castings.

5

study. Another goal is to obtain a significant database for high

alloy steel castings.

CASTING DIMENSIONAL VARIABILITY RESULTS

In general, many casting-specific and feature-specific

factors influence the overall dimensional variability measured in

the study. These factors include molding process used, feature

length, casting weight, parting line and others. Before the

combined influence of these many factors are described, the

influence of some important individual factors on dimensional

variability will be presented.

Figure 2 illustrates the influence of feature length on

dimensional variability for the various molding processes. In

this and all subsequent figures, the dimensional variability is

expressed in terms of the "half tolerance1I or three standard

deviations ( 3 a ) about the mean. Each data point shown on this

figure and subsequent figures is the calculated three standard

deviation value determined from individual dimensional

measurements of the same casting feature on 18 to 30 castings,

The larger features, in general, exhibited more dimensional

variability than smaller features. (It should be noted that the

length and variability axes on each plot of Figures 2a-c are

scaled differently.) Dimensions crossing the parting line show a

slightly greater variability than those not crossing the parting

line, for each of the molding processes. Figure 3 compiles all

of the data from Figure 2 to illustrate the relationship between

6

r

3 STANDARD DEVIATIONS (inches) s- fl

(D - 0

<e* * a

* *

0

0

* *

3 STANDARD DEVIATIONS K (inches) U

P P P P P P P P ot3g8gP---- -lQbo.03

0

N E 3 L O *

0

0 0

0 * * 0

0 0

3 STANDARD DEVIATIONS (inches)

3 STANDARD DEVIATIONS (inches)

0

P 0 01

P 4

P d

01 P N

. '.8 O a n b o +- +:. 0 .

. -$ ++ + :.o 0 . 0

+3+ 0 *. *. . . 4. 0 ,s

0 ..?LO

0

e . . . . . 0

O * . .. e &*o*

4

0

.

. .

.

. 8

the green sand, no-bake and shell data. In general, somewhat

less variability is observed for shell and no-bake casting

features than for green sand features. The scatter in the data

can be largely attributed to factors other than feature length

that influence variability.

Similar plots can be used to show the influence of casting

weight on overall dimensional variability. Figure 4 indicates

that casting feature variability, in general, increases as

casting weight increases for each molding type. This suggests

that the current IS0 specifications, which do not include the

influence of weight, can significantly underestimate or -

overestimate steel casting tolerance capabilities depending on

the size of the casting. Figure 5 combines the data on the same

axes to illustrate the general influence of casting weight on

dimensional variability for all three molding processes.

The previous figures also suggest a significant influence

of parting line on dimensional variability, Figures 2 and 4. The

effect of the parting line on the overall dimensional variability

is summarized below.

CONDITION AVERAGE

VARIABILITY (30) NUMBER OF inches (mm) FEATURES

crosses parting line 0.075 (1.90) does not cross the parting line 0.045 (1.15)

12 5 286

The difference of these two average values is an estimate

of the influence of the parting line on dimensional variability.

9

T

2 0.06

4 2; 3 0.04 n o 2 Q n

0.05

5 0.03 0.02

0.01

0

z d 0

2 0.18 Q 0.16

0.14 2; 3 0.12 0 2 0.1

0.08 2 0.06 n 2 0.04 2 0.02 r3 0

b)

2 0.25 Q 2 0.2 - > - $ 0.15 n o

5 3 Oel * 0.05

0 v)

r3

0 Feature Does Not Cross Parting tine + Feature Crosses Parting tine

a, + 8 0

0

Q i

0

0

0 2 4 6 8 10 12 14 16 CASTING WEIGHT (pounds)

0 50 100 150

CASTING WEIGHT (pounds)

200 250

4

0

+ + f 4

+ 0 0

8 O @ 0

-I

+ + 4

0 500 loo0 1500 2OOo 2500 3ooo

CASING WIGHT (pounds)

Figure 4: Influence of casting weight on overall dimensional variability a) shell mold castings b) green sand castings c) no-bake mold castings,

C)

10

+ I o *

. .

* + e** *no. ***. an*

0 0 00 0

. *** .e.* e .'e.. .

0 - 0 c

0

0

8 In

8 -

0

1 1

The data show that the total dimensional variability ( 6 a ) ,

averages 0 . 0 6 0 inches (1.5 mm) for features that crosses the

parting line. However, other factors such as feature length and

casting weight appear to have a significant influence on the

dimensional variability of features that cross the parting line.

This is perhaps to be expected; large molds made with no-bake

processes could be expected to have more parting line variability

than small green sand or shell molds.

All castings measured as part of this study were inspected

after final heat treatment and shot blasting. The influence of

type of heat treatment on overall dimensional variability is

shown below.

AVERAGE HEAT TREATMENT VARIABILITY (3a) NUMBER OF CONDITION inches (mm) FEATURES

quenched & tempered 0.036 (0 .92) 79 normalized & tempered 0.049 (1.24) 57 normalized 0.057 (1.44) 210 homogenized, quench & temper 0.073 (1.84) 65

This data must be interpreted with great care because the

average weight and feature length for each heat treatment

condition was not the same. Future analysis of the data will be

performed to determine the influence of heat treatment on casting

variability independent of the influence of other significant

variables.

The effect of core binder type on dimensional variability

for the 100 features measured across cores is shown below.

12

CORE TYPE

oil sand shell no-bake

AVERAGE VARIABILITY ( 3 U ) NUMBER OF inches (mu) FEATURE3

0.041 (1.04) 5 0.042 (1.08) 7 0.054 (1.37) aa

These preliminary observations must also be interpreted with

great care because of the low number of observations for shell

and oil sand cores, and because of the confounding influence of

core size on variability. In general, the average size of the

no-bake cores was signifi.cantly greater than the size of the oil

sand and shell cores included in the analysis. The difference in

core size is a likely explanation for the increased dimensional

variability observed for no-bake cores.

The influence of mold wash on dimensional variability has

also been evaluated. The data below are for features made from

no-bake molds, and are not across a core.

WASH CONDITION

no mold wash mold wash

AVERAGE VARIABILITY (3C) NUMBER OF inches (nun) FEATURES

0.057 (1.44) 72 0.069 (1.75) 54

This difference is not expected to be statistically significant.

The data are presented primarily to illustrate the ability of the

database developed in this study to evaluate the influence of

individual variables or combinations of variables on dimensional

variability.

13

The dimensional variability obsenred for casting features

also depends on the mold and core relationships that affect

dimensions. For example, the diameter of a cored hole is

controlled by the reproducibility of the core used to make the

hole. However, the wall thickness for that same cored feature is

also influenced by variability in core placement.

variability in wall thickness can be expected to be greater than

The

for the hole diameter itself. However, the mold to core

dimensions are typically smaller, and therefore exhibit less

variability. A summary of the overall influence of the

dimensional variability observed for some mold and core

relationships to features is shown below. Examples on these

various types of dimensions are shown schematically in Figure 6 .

DIMENSION TYPE

AVERAGE VARIABILITY (3a) NUMBER OF inches (mm) FEATURES

mold to core across casting 0.041 (1.05) 55 mold to mold across casting 0.050 (1.28) 126 core to core across core 0.052 (1.33) 100 mold to mold across

casting/core/casting 0.078 (1.97) 77

Figure 6: Schematic diagrams illustrating dimension types.

k 4 - l

II, 2

- 1 1 moldt o core across castlng 2 mold to mold across castlng 3 core to core across core 4 mold to mold across -

casting / c c ~ e / casting 14

This clearly shows that Itall dimensions are not created

The data must again be interpreted with great care, equal".

since other variables such as parting lines, influence only some

of the dimension type'categories.

ASSESSMENT OF FOUNDRY DIMENSIONAL CAPABILITIES

To date, extensive data sets have been collected for green

sand molding lines at two foundries, for no-bake molding lines at

two foundries, and for shell molding lines at two foundries.

(Work at other foundries is in progress.)

foundries will receive a comprehensive proprietary report

detailing their specific dimensional capabilities and an

assessment of their general dimensional control capabilities

compared to the rest of the industry.

Participating

A general comparison of the overall dimensional capabilities

of all of the first year participating foundries compared to the

existing SFSA tolerance standards is shown here.

PERCENTAGE OF FEATURES WITH DIMENSIONAL VARIABILITY LESS THAN THE EXISTING SFSA "T" TOLERANCE GRADES

SHELL

GREEN SAND

NO-BAKE

T3 T4 T5 T6 T7 89% 100% 100% 100% 100% . - - - - - 86% 100% 100% 100% 100%

42% 75% 88% 94% 100% 15% 62% 100% 100% 100%

64% 90% 98% 100% 100% 68% 81% 96% 100% 100%

This table summarizes the percentage of features for each foundry

molding process that exhibited dimensional variability that was

15

less than the existing "T grade" tolerance. The current oT311

grade is considered appropriate for castings produced from

special molding processes, the current trT511 grade is considered

appropriate for typical (green sand) processes, and the current

11T711 grade is considered appropriate for complex casting

configurations. When these llT1l grades were initially

established they were based loosely on the average dimensional

capability (50% conformance). Clearly, the foundries' ability to

control dimensions is considerably better than indicated by the

existing SFSA standard for a l l molding processes.

Linear regression analysis techniques can be used to

develop improved models for predicting the dimensional

variability of each individual molding process for each foundry.

The following are multiple linear regression models for each of

the six molding processes. Feature length, casting weight, and

the presence or absence of a parting line are the independent

variables used in this simple analysis.

MOLDING PROCESS REGRESSION MODELS TO PREDICT DIMENSIONAL VARIABILITY

SHELL : 3 StDev = 0.003 + 0.001 * W + 0.003 * L + 0 . 0 0 8 PL 3 StDev = -0.013 + 0.003 * W + 0.001 * L - 0.007 PL

GREEN SAND: 3 StDev = 0,048 + 0.0002 * W + 0.0005 * L + 0.002 PL 3 StDev = 0.027 + 0.0001 * W + 0 .005 * L + 0.015 PL

NO-BAKE: 3 StDev = 0.034 + 0.00002 * W + 0.003 * L + 0.015 PL 3 StDev = 0.024 + 0 .00005 * W + 0.002 * L + 0.024 PL

16

Where 3 StDev = 3 standard deviations (inches) W = casting weight (pounds) L = feature length (inches) PL = 1 if feature crosses parting line

= 0 if feature does not cross parting line

There are some important general conclusions which can be made by

comparing these equations:

- In general, foundry-to-foundry dimensional capability variations for a given molding method are less than the variations between molding processes.

- Coefficients on the weight terms in the regression equations differ significantly for the different molding processes. Casting weight is much more of a dimensional variability factor for green sand than for no-bake molds This is no doubt due to the rigidity of no-bake molds compared to green sand molds. control of green sand molding processes are key to insuring casting dimensional control.

This also suggests that

An example of a dimensional capability table generated for a

particular foundry based on its linear regression table is shown

in Table 1. This type of information can be effectively used by

participating foundries to better predict their dimensional

capabilities.

In order to put the dimensional variability measured to date

in this study in perspective, a comparison was made between the

dimensional variability predicted using the new equations and the

current SFSA "T" equations. Comparisons for some representative

casting features are presented in Table 2. This shows some

differences in the ability of foundries to control dimensional

variability. In most cases, foundry dimensional control is

significantly better than indicated by current tolerance

guidelines.

17

,;, - -

Table 1: Sample tolerance table for a particular foundry molding process

2 4 6 8

10 15 20 30

CASTlNG WEIGHT (pounds)

10 20 50 75 100 200 250 500 0.040 0.040 0.040 0.041 0.041 0.043 0.043 0.047 0.046 0.046 0.047 0.047 0.047 0.049 0.050 0.054 0.052 0.053 0.053 0.053 0.054 0.055 0.056 0.060 0.059 0.059 0.059 0.060 0.060 0.062 0.063 0.067 0.065 0.065 0.066 0.066 0.067 0.068 0.069 0.073 0.081 0.08 1 0.082 0.082 0.083 0.084 0.085 0.089 0.097 0.097 0.098 0.098 0.099 0.100 0.101 0.105 0.129 0.129 0.130 0.130 0.131 0.132 0.133 0.137

Table 2: Comparison between predicted feature variability using the new equations and the current SFSA tolerance guidelines for selected casting features. Note values in bold are the result of extrapolation.

LENGTH (inches) WEIGHT (pounds)

18

PATTERN SHRINKAGE ALLOWANCES

Corresponding pattern dimensions were also measured for many

of the casting features in this study. By comparing pattern

dimensions to average casting feature dimensions, an accurate

estimate of the casting shrinkage amount for each feature can be

obtained.

measurement errors, these data are perhaps the first reliable set

of shrinkage allowance information developed for the industry.

Figure 7 shows the distribution of actual shrinkage values for

the features measured in this study. The average shrinkage

factor measured (2.02%) is virtually identical to the llstandardll

pattern shrinkage allowance used throughout the industry (2.08%

or 1/4 in. per ft).

of the pattern shrinkage values obtained. Clearly, these wide

variations in pattern shrinkage amounts have a substantial effect

on the foundries' ability to produce castings that meet customer

dimensional requirements, and must be carefully studied. Many

Because close attention has been paid to controlling

However, of great concern is the wide range

features had shrinkage allowances considerably greater than and

considerably less than 2.08%.

each of the molding processes is as follows.

data is continuing. .

The average shrinkage amount for

Analysis of the

MOLDING PROCESS

shell green sand no-bake

19

. --

AVERAGE SHRINKAGE NUMBER OF FEATCJRES PERCENTAGE

2.4 1.7 2.0

26 41 83

45

40

35

15

10

5

0

INCHES / FOOT

o m 0 9 c u 9 P 3 9

m F c

I

o l n o m o m o 9 c u s cu - 2 2 : 7 4

SHRINKAGE PERCENTAGE

Figure 7: Distribution of observed shrinkage amounts.

0

2

ANALYSIS OF FOUNDRY MEASUREPENT SYSTEMS

Throughout this study, the repeatability of measurement

systems used to measure casting and pattern dimensions at

various foundries has been characterized.

repeatability obtained from a wide variety of foundry inspection

department measurement systems. This table does not include

reproducibility errors that may be introduced from operator

variability. Rather, it simply indicates the equipment's

baseline repeatability when used by a trained operator.

measurement error (gage R & R) must be less than 30% of the

the

Table 3 summarizes the

The

feature tolerance for the measurement system to be adequate. 11

Portage layout machines have considerably more repeatability

20

Table 3: Repeatability errors for some commonly used measurement instruments

MEASUREMENT INSTRUMENT

micrometer CMM Digital Caliper - not a diameter Digital Caliper - diameter Portage Machine Scale / Ruler

REPEATABILITY (inches) SAMPLE AVERAGE MINIMUM MAXIMUM SIZE

0.004 1 0.008 0.004 0.01 1 2 0.01 2 0.006 0.029 12 0.023 0.01 9 0.026 4 0.028 0.012 0.041 4 0.056 0.055 0.057 2

Tolerances (?inches) for Tolerance Grade T3 (S) Casting Weight. Ib

L* 2 5 10 20 50 75 100 150 200 250 500 750 1000 I250 I500 2000 3000 4OOO 5000

.047 -049 .OS7 -063 -068 -071 .075 .08 I .090 .097 .I03 -051 .OS4 .062 .068 .072 -076 .079 .OS5 .094 .IO1 .I08 .OS7 .OS9 .068 .073 .078 -082 -085 .09 I . I 0 0 .I07 . I 13 .064 .067 .075 .081 -085 .089 .092 .098 .I07 . I 14 .I21

6. .069 .072 .080 -086 -090 .094 -097 . I03 - 1 I2 .I20 -126 8.0 .OS0 .OS3 .OS5 .OS8 .063 .065 .067 -071 .073 .076 -084 .090 -094 -098 .lo1 ,107 .116 -124 .I30

10.0 .OS4 .OS6 . .OS8 .061 .066 .069 .071 -074 .On .079 .087 -093 -098 -101 . IO5 .I11 .I20 .I27 .I33 15.0 .061 .063 .065 -068 .073 .076 .078 .081 .084 -086 .094 -100 .I@ .I08 . I I2 .I17 -127 .134 -140 20.0 -066 .069 -071 .074 .078 .081 .083 .087 -089 .091 .I00 . IO5 . I 10 .I14 . I 17 . I 2 3 .I32 .I39 .I45 30.0 .075 .077 .079 .082 -087 .090 -092 -095 .098 .I00 .I08 .I14 .I19 -123 .I26 .I32 -141 -148 .154 40.0 .082 .084 ,086 .089 -094 -097 .099 .I02 . IO5 .I07 -115 -121 -126 .I29 .I33 .I39 .I48 .I55 .I61 50.0 .088 .090 .092 .095 -100 .I03 -105 .I08 .111 .I13 .I21 .I27 -131 -135 .I39 -144 -154 -161 .I67 60.0 .093 .095 .097 -100 . IO5 .I08 .I10 -113 -116 -118 .126 .I32 -137 . I 4 0 -144 -150 .I59 -166 .I72

'Dimension l eq th in inches

Figure 8: SFSA 1tT3tt tolerance table with the tolerances that cannot be measured with a measurement instrument with measurement error of 0.028 inches (0.71 mm) indicated

21

error than some other types of instruments and must be used with

great caution. Based on the average repeatability of 0.028

inches (0.71 mm), a measurement error requirement of less than

30%, and assuming negligible reproducibility error, the smallest

total feature tolerance that the Portage can be used for is 0.093

(2.37 m m ) . Figure 8 is a copy of the SFSA T3 table with

tolerances that cannot be measured with the Portage machine

indicated. Work is continuing to characterize the gage R & R of

this and other commonly used foundry measurement analysis

instruments and to determine the influence of surface

characteristics on gage R & R .

SUMMARY

Work with SFSA member foundries is continuing so that

improved casting tolerance guidelines can be developed, improved

pattern shrinkage allowances can be obtained, and dimensional

control strategies can be developed for the membership. The data

presented in this paper will continue to be analyzed in order to

fully understand the influence of the many interacting variables

on dimensional variability. Additional data need to be collected

during the second and third years of the project so that a

comprehensive database can be developed for the industry.

database will provide the dimensional information and the

dimensianal CQILLZQL strategies for satisfying the dimensional

needs of the steel casting customer.

This

22

As a result of the first year of study, the following

preliminary conclusions can be made:

- Adequate measurement system gage R & R is attainable but requires vigilance.

- Initial tests on Portage machines indicate relatively poor repeatability. More information is being collected.

- Observed casting feature variability is considerably less than indicated by current SFSA standards.

- Many processing and geometry variables have measurable effects on dimensional variability.

- More data and analysis is needed to determine if there are significant foundry-to-foundry dimensional variability differences and to identify individual sources of variability.

- Current shrinkage allowance factors are inadequate. Work is ongoing to develop improved allowances.

REFERENCES

1 ROSS, P. J. ; "Measurement System Capability Project, It Steel Founders' Society o f America T & 0 Conference, Chicago, IL (November 1990) .

2

3

4

5

6

Ross, P.J.; ##Measurement System Capability Project - 1992 Update, Steel Founders' Society o f America T & 0 Conference, Chicago, IL (November 1992).

Peters, F.E. and R.C. Voigt; "Casting Inspection Strategies for Determining Dimensional Variability," Steel Founders' Society o f America T & 0 Conference, Chicago, IL (November 1993).

Law, T.D.; "Dimensional Tolerances in Steel CastingsIii The B r i t i s h Foundryman, vol 71, part 9, p 223 (1978).

Aubrey, L. S . et a1 . ; Dimensional Tolerances, Research Report No. 84 , Steel Founders' Society of America, Des Plaines, IL (1977) .. IBF Technical Subcommittee TS71; "Second Report of Technical Sub-Committee TS71 - Dimensional Tolerances in Castings," The B r i t i s h Foundryman, vol 64, part 10, p 364 (1971).

T - -- - - -

23

7

8

9

Wieser, P.F., ed.; Steel Castings Handbook, 5th ed, Steel Founders' Society of America, Rocky River, OH (1980).

ISO; Castings - System of Dimensional Tolerances, IS0 8062 (1984).

Voigt, R.C. and F.E. Peters; lfDimensional Tolerances and Shrinkage Allowances for Steel Castings,ii Steel Founders' Society o f America T & 0 Conference, Chicago, IL (November 1992.

10 Peters, F.E. and R.C. Voigt; llDimensional Capabilities of Steel CastingsIii Proceedings o f the Near-Net-Shape Manufacturing: Examining Competitive Processes Conference, Pittsburgh, PA (September 1993).

11 Measurement Systems Analysis - Reference Manual, Automotive Industry Action Group (1990).

The authors wish to thank the U.S. Department of Energy, the Assistant Secretary for Energy Efficiency and Renewable Energy, under DOE Idaho Operations Office, Contract DE-FC07- 93ID13235, for providing funds to support this research. The authors would also like to thank the SFSA Carbon and Low Alloy Research Committee, and the participating foundries, for their support and guidance for this project. Finally, technical support provided by Chad Hafer is greatly appreciated.

DISCLAIMER

This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thcreof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsi- bility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Refer- ence herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recom- mendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.

24

Prepared for the U.S. Department of Energy

Assistant Secretary for Energy Efficiency and Renewable Energy Under DOE Idaho Operations Office

Contract DE-FC07-93ID13235