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.
ACKNOWLEDGMENTS
We thank C. C. Essix for her support and encouragement, Teresa Cremers for her assistance with one of the examples, and the editor and the reviewer for their helpful comments.