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"THE ECONOMIC IMPACT OF MEASUREMENT ERROR" as published in Quality Engineering, Vol. 11(1)

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    6/12/2015 11:08:10 PM
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Interpretation of the results of a gauge repeatability and reproducibility (R&R) study relies on two key metrics -- the combined gauge R&R as a percent of specification and the discrimination ratio. These metrics are useful in terms of the rules of thumb that have been developed over the years, but they fall short of effectively quantifying how well the measurement system will perform in a production environment. For any measurement system, the alpha (or producer’s) risk is defined to be the probability that the test will fail a unit of product that conforms to specification. The beta (or consumer’s) risk is defined to be the probability that the test will pass a unit that does not conform to specification. When the alpha and beta risks have been estimated, the economic impact of the performance of the measurement system can be evaluated. A method for estimation of the alpha and beta risks has existed for some time in the literature, but it is not commonly practiced in the analysis of measurement systems performance. The authors argue that risk analysis should be a fundamental component of any R&R study. A case study is provided to provide insight into the usefulness and applicability of this technique.

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