IPC-TM-650 EN 2022 试验方法.pdf - 第21页

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 0-8738…

test groups. Prepare more than the material required to

ensure an adequate amount is available for the study in case

of lost or damaged specimens, errors, test set-up, etc.

Carefully package and label the material. Assign serial num-

bers, if possible. Identify the version of the test procedure.

Specify care and handling procedures. Provide a data sheet,

and describe any documentation required. Require a test log,

and insist that observations of any unusual events be

recorded.

5.2

Conducting the Evaluation

Ensure

the samples are

inspected on receipt. Send replacement material if damaged

or tests are performed improperly.

Inspect the data sheets when returned. Review the test logs

for unusual events. Review the results. Question unusual dis-

positions or comments. Incorrect dispositions and typos must

be fixed prior to analysis.

5.3

Analyzing the Data

Analysis may be performed on the

data sheet or on the Excel spreadsheet (see 6.2).

The basic techniques involve beginning with a set of parts or

materials for which the classification has been previously

determined. Several inspectors or testers then examine and

classify the parts and the results are compared with the

known standard classification.

The effectiveness of the test is the number of correct determi-

nations divided by the total number of classification opportu-

nities (number of parts times the number of inspectors).

E =

Number

of correct dispositions

Number

of parts x Number of testers

(1)

The

probability of a false reject and the probability of a false

accept can be defined as follows:

P(FR)=

Number of dispositions where good parts were rejected

Number

of good parts x Number of testers

(2)

P(FA)=

Number

of dispositions where bad parts were accepted

Number of bad parts x Number of testers

(3)

5.4

Preparing Analysis Conclusions

Goals

for measure-

ment precision should be established before the study begins.

The goals should be established using knowledge of the

anticipated levels of product variability (or process capability),

specifications, customer needs and the possible impact of

dispositioning test samples improperly. As a rule of thumb, the

guidelines shown in Table 1 have been extensively applied.

If the test effectiveness is inadequate, then steps should be

taken to diagnose and improve the causes of the deficiency.

The probabilities of false acceptance and false rejection

should help in this diagnosis. Marginal tests should also be

improved.

An acceptable test effectiveness rating (E) indicates that the

test method dispositions the products with reasonable cor-

rectness.

The results of this evaluation should be compared to the test

efficiency goals for this inspection. The rules of thumb noted

above have been found to be useful. These goals could be

amended, depending on the criticality of the inspection, and

the impact of incorrect disposition.

6 Notes

6.1 Methods for Analyzing Repeatability and Reproduc-

ibility

This

test method covers situations where the mea-

surements result in binary data, such as go and no-go, or

pass and fail tests. The precision of the test is determined by

calculating the consistency and correctness of the sample

dispositions.

Measurements that result in variables data can be analyzed

using IPC Test Method IPC-TM-1.9.

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 under develop-

ment.

6.2

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).

able 1 Recommended evaluation criteria

Metric

Acceptable Marginal Inadequate

>0.9 0.8 to 0.9 <0.8

P(FR) <0.05 0.05 to 0.10 >0.10

P(FA) <0.02 0.02 to 0.05 >0.05

IPC-TM-650

Number

1.8

Subject

Measurement

Precision Estimation for Binary Data

Date

01/03

Revision

age2of6

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. 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

f. ‘‘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.)

6.3

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 which

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

spreadsheet written to perform the calculations in this proce-

dure.

a. Measurement Precision Calculator For Binary Data, Excel

spreadsheet, available at http://www.ipc.org/html/

testmethods.htm, free of charge.

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

1.8

Subject

Measurement

Precision Estimation for Binary Data

Date

01/03

Revision

age3of6

Measurement

Precision Study – Binary Data

Calculations

Table 1: Data Entry Form

Enter test results into the table below.

ester

Samples

12345678910

True

Standard

Table 2: Samples Dispositioned Correctly

Score a ‘‘1’’ where disposition in Table 1 above matched the true standard.

Score a ‘‘0’’ where disposition did not match the true standard.

Note these scores for each of the testers in the table below.

ester

Samples

12345678910Total

True

Standard

IPC-TM-650

Number

1.8

Subject

Measurement

Precision Estimation for Binary Data

Date

01/03

Revision

age4of6