Easy Auditing
Simsack meets gage R&R.

Michael J. Cleary, Ph.D.
mcleary@qualitydigest.com

Rock DeBote, CEO of Greer Grate & Gate, calls it good news. Hartford Simsack, quality manager, calls it rotten luck. The company is about to undergo an ISO 9001 audit, and DeBote anticipates that with the preparation the company has given to the audit, it will all go swimmingly. Simsack, wondering how he’ll ever be able to respond to any serious questions relating to SPC, just wishes it would all go away.

Unfortunately, Les Ismore, who’s been responsible for all gage calibrations and inventories, has recently left the company for a position with another organization. DeBote has suggested that Simsack temporarily take over Ismore’s responsibilities, at least until after the audit. “We don’t have time to train someone new,” DeBote points out, not realizing that Simsack himself knows nothing about gage management and precious little about SPC. So far, he’s managed to disguise the paucity of his statistical understanding with language garnered from his mentor, Dr. Stan Deviation. Simsack is in trouble.

Hastily leafing through a catalog of workshops offered by the local community college, Simsack is relieved to see that a seminar on gage management, taught by

Professor Cal Ebbrate, is scheduled for an evening session. “Perfect,” Simsack says. He arrives at the seminar ready to take notes so he can at least use the terminology to impress his colleagues and win over the auditors. His concentration, however, is somewhat flawed, compounded by the fact that the class takes place in the evening—and by his propensity not to pay attention to lectures.

Professor Ebbrate, discussing the uses of R&R, points out that systems which correctly utilize the power of R&R are far more likely to pass their audits. Simsack is suddenly alert. “I knew I’d get something out of this,” he mutters to himself.

The next day, Simsack returns to GG&G and schedules a meeting with DeBote to review the requirements for the upcoming audit and the strategies his company will pursue to ensure success. “We need to have the entire quality department experience R&R” (which he assumes means rest and relaxation), Simsack asserts. “Professor Ebbrate says it’s the most useful thing we can do, and I know that the best advice to someone preparing for a test is to get enough rest, so I’m sure this will help.” DeBote is somewhat dubious but nonetheless listens and reluctantly agrees when Simsack suggests a day at the beach for all employees.

Where does Simsack’s suggested strategy fall?

a) Into the catcher’s glove

b) Near the left field bleachers

c) Out of the ballpark: It’s such a good idea that it will be a home run for the company.

The answer is b. Simsack has hit a foul ball. His habit of depending only on terminology without understanding its meaning has created a monster.

R&R studies, of course, refer to “repeatability and reproducibility,” not “rest and relaxation,” and they play a key role in any gage management system. Repeatability is the “variation in measurement obtained with one measurement instrument when used several times by an appraiser while measuring the identical characteristic on the same part” (Measurement System Analysis, AIAG, 1995, p. 17).

“Reproducibility,” according to the AIAG source cited, “is the variation in the averages of the measurements made by the different appraisers using the same measuring instrument when measuring the identical characteristic on the same part.”

A typical test for repeatability includes having two operators measure five identical parts three times each and then creating a range chart for all 10 trials. If the range chart is in control, the gage’s repeatability can be calculated. The estimate for the standard deviation for repeatability is:

Where R is the average range from the study, d 2* is the weighting factor derived by the number of trials taken, the number of parts and the number of appraisers. The larger the se, the less the repeatability of the instrument. For a more complete explanation of repeatability and reproducibility, see the AIAG manual referred to above.

About the author

Michael J. Cleary, Ph.D., is a professor emeritus at Wright State University and founder of PQ Systems Inc. He has published articles on quality management and statistical process control in a variety of academic and professional journals. Letters to the editor regarding this column can be e-mailed to letters@qualitydigest.com.