IPC-TM-650 EN 2022 试验方法.pdf - 第35页

6.3 Methods for Analyzing Repeatability and Reproduc- ibility There are several methods for calculating the mea- surement precision from the data obtained during the mea- surement precision study. Two of the most commonl…

a rule of thumb, the guidelines shown in Table 2 have been

extensively applied.

In this table, test measurement precision would be acceptable

if it is less than 10% of the specification width and less than

10% of the total product variation. A test precision that is

more than 30% of the specification width, or more than 30%

of the total product variation, would need improvement. A test

precision more than 10% but less than 30% of specification

width or total product variation would represent marginal mea-

surement precision, and should be improved. An illustration of

the relationship between specification limits and measurement

uncertainty is shown in Figure 2.

If measurement precision is judged to be marginal or worse,

for either GRR or PV, steps should be taken to reduce the

measurement variability. The repeatability and reproducibility

estimates can be examined to determine the largest contribu-

tor to total measurement uncertainty. If the largest component

of variation is repeatability, the cause of variability is with-in a

given test condition. Probable causes include problems with

calibration, lack of operator controls, excessive within part

variation or equipment problems. If the largest component of

variation is reproducibility, the cause of variability is between

test conditions. The probable causes include difference in test

procedural problems test methods, or equipment calibration.

An acceptable GRR or PV value indicates that the test method

precision is adequate and should yield data with reasonable

certainty.

Notes

6.1 Measurement System Properties

ideal measure-

ment system would have a number of properties including the

following:

a. The measurement system would have adequate resolution.

b. The measurement system would be in statistical control,

the variation in the measurements would be due to com-

mon or random causes only, with all special or definable

causes removed.

c. The variability of the measurement error would be small

when compared to the manufacturing product variability.

d. The variability of the measurement error would be small

when compared with the specification limits.

6.2

Sources of Measurement Variation

measurement

system may exhibit several types of variation, including the

following:

a. Accuracy (or bias) – The difference between an observed

measurement and the true (but perhaps unknown) value

being measured.

b. Precision – The closeness to each other of repeated mea-

surements of the same quantity. Precision can be sepa-

rated into two components:

Repeatability – Variation of a measurement system that is

obtained by repeating measurements on the same

sample(s) by the same procedure under the same mea-

surement conditions including the same operator.

Reproducibility – Variation among the averages of mea-

surements made under different measurement conditions

such as different operators, equipment, and/or locations.

c. Stability (or drift) – The variation observed when repeating

measurements on the same device and the same test set-

up, over an extended period of time.

d. Linearity – The difference in bias values through the

expected operating range of the measurement instrument.

This test method has addressed item 6.2.b above. The other

sources of variation are addressed in the references (see 6.4).

able 2 Recommended Evaluation

Criteria for GRR and PV

GRR

and PV Rating

>30

Needs improvement

10 to 30 Marginal

<10 Acceptable

IPC-19-2

Figure

2 Depiction of the Relationship Between

Measurement Precision and the Speciﬁcation Limits

Spec Width

LSL

USL

Measurement

Precision

IPC-TM-650

Number

1.9

Subject

Measurement

Precision Estimation for Variables Data

Date

01/03

Revision

age4of10

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6.3

Methods for Analyzing Repeatability and Reproduc-

ibility

There

are several methods for calculating the mea-

surement precision from the data obtained during the mea-

surement precision study. Two of the most commonly applied

techniques are applied to measurements that result in vari-

ables data, and are called the Average and Range, and

ANOVA methods.

a. Average and Range Method – This method is covered in

this test method and provides an estimate of the standard

deviation of the repeatability and reproducibility using the

ranges between the highest and lowest measurements in a

subgroup. This method allows measurement variability to

be decomposed into two components, repeatability and

reproducibility. It does not estimate the interaction effects.

b. The ANOVA (Analysis of Variance) – This method uses a

components of variance technique to decompose the

measurement variability into various categories, such as,

parts, operators, test equipment, etc. It can calculate the

interaction between any of these components. It is more

flexible, but is more challenging to calculate. This method

generally requires a computer and a certain degree of

expertise to interpret. The analysis method is described in

the references, see 6.4.

Measurements which result in binary data, such as go and

no-go, or pass and fail tests, can be analyzed for consistency

and correctness of disposition, see IPC Test Method IPC-TM

1.8.

In some cases, the measurement cannot be repeated more

than once on the same sample. This is common where the

sample is consumed during the test, such as chemical analy-

sis, or changed during testing, such as solderability evalua-

tions. In these cases, the analysis using a modified average

and range method is possible. This method is currently under

development.

6.4

References

ISO 5725-1 Accuracy (trueness and precision) of measure-

ment methods and results (parts 1 to 6), 1998(E), Interna-

tional Organization for Standardization, Geneva, Switzer-

land (www.iso.org).

b. Measurement Systems Analysis, 2nd edition, June 1998,

Automotive Industry Action Group (AIAG), 26200 Lahser

Road, Southfield, MI 48034 (www.aiag.org).

c. Standard Practice for Conducting an Interlaboratory Study

to Determine the Precision of a Test Method, E691-99,

ASTM, Philadelphia, PA (www.astm.org).

d. Concepts for R&R Studies, Larry B. Barrentine, (ISBN

0-87389-108-2), ASQC Press, Milwaukee, WI (www.quali-

typress.asq.org).

e. Statistical Process Control Guidelines, Texas Instruments,

Dallas, TX

f. Introduction to Statistical Process Control, 3rd edition,

Douglas C. Montgomery, 1997, John Wiley and sons,

ISBN 0-471-30353-4, pages 455-467

g. Basic Statistics, 4th Edition, Mark J Kiemele, Stephen R.

Schmidt, Ronald Berdine, Air Academy Press, 1997, ISBN

1-880156-06-7, pages 9-71 to 9-77.

h. ‘‘Is 100% Test 100% Effective,’’ W. Russell, 1998 IPC

EXPO, San Jose, CA (gives methods for calculating the

likely outcomes on product test for differing levels of mea-

surement precision.)

6.5

Software

Measurement

precision studies are greatly

facilitated by use of software to perform the calculations.

Below are just a few of the many software packages that can

be used for this purpose. Reference (a) is an Excel spread-

sheet written to perform the calculations in this procedure.

a. Measurement Precision Calculator, Excel spreadsheet,

available at http://www.ipc.org/html/testmethods.htm for

free download.

b. Statgraphics Plus, Manugistics Corp, 2115 East Jefferson

Street, Rockville, MD, 20852-4999 (www.statgraphic-

s.com).

c. SPC XL, Air Academy Press, 1155 Kelly Johnson Blvd,

Colorado Springs, CO 80920 (www.airacad.com).

d. Minitab, Minitab. Inc., 3081 Enterprise Dr, State College,

PA 16801 (www.minitab.com).

e. Interlaboratory Data Analysis Software for E691, ASTM,

100 Barr Harbor Dr, West Conshohocken, PA 19428

(www.astm.org).

IPC-TM-650

Number

1.9

Subject

Measurement

Precision Estimation for Variables Data

Date

01/03

Revision

age5of10

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Measurement

Precision Study - Data Sheet

Condition

A Reading

Sample

Average12345678910

Average

Range

Condition

B Reading

Sample

Average12345678910

Average

Range

Measurement

Precision Study - Information Sheet

Test

Method

Parameter Measured

Company

Name of Study Organizer

Study Completion Date

Instrument

Measurement Units

Lower Specification Limit, LSL

Upper Specification Limit, USL

Number of Conditions, m

Number of Samples, n

Number of Repeat Readings, k

IPC-TM-650

Number

1.9

Subject

Measurement

Precision Estimation for Variables Data

Date

01/03

Revision

age6of10

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