A Bayesian Approach to the Analysis of Gauge R&R Data

Abstract

Gauge repeatability and reproducibility (R&R) studies are used to assess precision of measurement systems. In particular, they are used to quantify the importance of various sources of variability in a measurement system. We take a Bayesian approach to data analysis and show how to estimate variance components associated with the sources of variability and relevant functions of these using the gauge R&R data together with prior information. We then provide worked examples of gauge R&R data analysis for types of studies common in industrial applications. With each example we provide WinBUGS code to illustrate how easy it is to implement a Bayesian analysis of gauge R&R data.

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