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RICK HAYNES | 09/10/2013

How to Understand a Measurement SystemAnalysis

A true MSA measures more than just the gauge

easurement system analysis of uncertainty is one topic in lean Six

Sigma training that is too often ignored or under-taught. I believe

that it is under-taught because most instructors have never used or

understood it. Therefore, this column will dive deep into what it is and why

you should learn about it. Keep in mind that this methodology is not for

destructive sampling or attribute or classification gauges. It only works on

measurement systems that allow remeasuring of the same sample and

reporting a continuous value for the measurement output.

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Measurement system analysis or gauge study

I first learned about this topic as a measurement system analysis (MSA). The

term “gauge study” is only one element of the process, but many consider

gauge study and MSA to be synonyms. MSA is probably the best term for the

concept because its title implies measuring more than just the gauge. A true

MSA includes estimating the impact of the gauge, the fixturing or setup of the

gauge, the operator, and the variation over time.

The best reference book

The best reference for MSA is the Automotive Industry Action Group’s

(AIAG) blue book, Measurement System Analysis, Fourth Edition. This book

has all the information on the definitions and methods that are in common

use, along with very good examples. When I taught at Bechtel, we required

every lean Six Sigma Black Belt to obtain a copy. Currently I teach out of

Forrest Breyfogle’s book, Integrated Enterprise Excellence, Volume 3, which

has licensed portions of the AIAG material, and it is also an excellent

reference book.

Ratio of items to appraisers to repeat measurements

The general answer to this ratio is to measure multiple items, multiple times,

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by multiple people. The most common ratios when all the analysis was

performed by hand were 10 items, two measurements, by three people. I seem

to recall that this ratio provided a good balance of the uncertainties, but it is

far from being a requirement. You do need a minimum of two appraisers and a

minimum of two measurements of each item by each appraiser, but the

number of items to be measured can vary a good deal.

My guidance to most people is to consider where you believe the greatest

sources of variation exist and increase the factor that would allow the best

estimation of that factor.

• If the difference in appraisers (people) is expected to be high, use three or

four appraisers of widely different experience levels

• If you expect that slight differences in the measured items may impact the

reported measurement, make sure you include a full range of eight to 12 items

that include at least one item outside the specification.

• If you believe that there may be a time-to-time change in the measurement

system because of adjustments or setups methods, then include at least three

replicated measurements from each appraiser of each item.

Analysis method

There are two accepted MSA methods: ANOVA and X-bar R. I have always

trusted the ANOVA method because it provides the ability to evaluate an

interaction between the appraiser and the items. The X-bar R method is

preferred when you are doing MSA by hand or using a calculator. When using

a statistical analysis program, I recommend always using the ANOVA method.

What is precision or gauge repeatability and

reproducibility?

There are two components of uncertainty in a MSA: repeatability and

reproducibility. This combination is labeled as the precision of a

measurement system.

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Repeatability is the variation found in a measurement system when the same

item is measured over and over again without changing its position or who

appraised it, and all at the same time. Get it: repeated measurements. This

uncertainty estimate is really the smallest error you can get on a measurement

system without fundamentally changing the equipment or the measurement

process. It is reported as a standard deviation.

Repeatability: variation in measuring something the same way,

same person, same time, same conditions, same, same, same.

Reproducibility is the variation found when trying to reproduce the

measurement under different conditions. These different conditions will

include the difference in appraisers, the difference in fixturing or positioning

the item in the measurement tool, different times, and different calibrations.

When this value is high, it implies that the measurement process is

inadequate. It is reported as a standard deviation.

Reproducibility: variation in measuring something in different

ways, different times, different people, different, different,

different.

The precision is considered the true measurement system uncertainty.

Precision is the square root of the sum of the squared repeatability value and

squared reproducibility value. The precision value is the one that is compared

to the specification and the process variability to determine the goodness. A

large precision value may derive from a large repeatability value, a large

reproducibility value, or both values being large. The component that has the

largest contribution to the precision is where you address improvements.

Precision: The total measurement system variation estimate. It

includes repeatability and reproducibility.

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What is “good” for a measurement system?

This is probably the most difficult part of the entire MSA concept to get

across to students because the definition of “good” can depend on who taught

you. The AIAG reference books list multiple methods to judge goodness, but I

believe there are only two that matter: percent of the tolerance and percent of

the process. Comparing the precision value to the requirements or

specifications will tell you about the ability of the measurement system to be

used for quality assurance. Comparing the precision to the process variation

reported by the measurement system tells you about the ability of the

measurement system to be used for quality control.

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ABOUT THE AUTHOR

Rick Haynes

Rick Haynes is a statistician and Master Black Belt who has worked in

manufacturing, R&D, and nonmanufacturing businesses performing process

improvements and statistical support for scientists and engineers since 1986.

His original Six Sigma training was with Motorola in the 1980s, and Haynes

has been an instructor of Six Sigma and statistics since the mid-1990s.

09/18/2013 - 03:35 AM — PETER FRANKOVIC

Comments

Percentage of acceptability

I have a book from Dr. Wheeler Evaluating the Measurement Process III and I fully agree with his

opinion about percentages of acceptability of measurement system. In short these percentages are

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09/17/2013 - 07:21 AM — UMBERTO MARIO TUNESI

deteriorating the measurement system. If the measurement system is stable, predictable and

consistent validated by process behavior charts, I will not say that MSA with R&R = 35% is

unacceptable. Depends on use. One of the purpose of measurement system is to be able to track

process changes and for that is MSA with R&R = 50% still enough. I work in a machinery company with

lots of single-purpose process measures and with this approach we should scrap half of them and

then stop the lines. Unfortunately our customers request this approach because they are widely using

AIAG studies as a Holy Bible which is unfortunately wrong.

I propose to read Dr. Wheeler´s article "Problems with Gauge R&R Studies" here on Quality Digest for

more information and for different view. http://www.qualitydigest.com/inside/twitter-ed/problems-gauge-

rr-studies.html

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MSA

MSA is probably one of the least understood and one of the most abused of investigation methods on

reliability of measuring systems: I've seen it carried out on destructive measurements, by laboratory

technicians instead of line operators only because Registrars' auditors request it. Even when the

system is evidently stable, third party auditors request MSA be carried out once a year, at a company's

great expense of time and money. And we are talking of auditors as graduated engineers, not of

common laymen. It is therefore no wonder that companies' metrologists seldom care for it: once the

output is within specs, it's cooked and ready for serving.

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