Design and Analysis of Gauge R and R Studies：Making Decisions with Confidence Intervals in Random and Mixed ANOVA Models

This book provides a protocol for conducting gauge repeatability and reproducibility (R&R) experiments, which are required whenever a new test system is developed to monitor a manufacturing process. This protocol—not currently available in other books or technical reports—is used to determine whether the testing system is capable of monitoring the manufacturing process with the desired level of accuracy and precision.The book presents an up-to-date summary of methods used to construct confidence intervals in normal-based random and mixed analysis of variance (ANOVA) models. Thus, this comprehensive book will be useful to scientists in all fields of application who wish to construct interval estimates for ANOVA model parameters. It includes approaches that can be applied to any ANOVA model, and because it contains detailed examples of all computations, practitioners will be able to apply the methods easily. The book describes methods for constructing two types of confidence intervals: modified large-sample (MLS) and generalized confidence intervals. Computer codes written in SAS and Excel are provided to perform the computations. Appendices are included for readers who are unfamiliar with confidence intervals or lack a basic understanding of random and mixed ANOVA models.Design and Analysis of Gauge R&R Studies: Making Decisions with Confidence Intervals in Random and Mixed ANOVA Models is directed at two audiences: engineers who conduct gauge R&R studies as part of a measurement systems analysis, and investigators who use ANOVA methods in their research.

Richard K. Burdick is Professor of Statistics in the W. P. Carey School of Business at Arizona State University, Tempe. He is the author or coauthor of three books and more than 50 journal articles on statistical methods. His primary research efforts have considered interval estimation in linear models with applications in manufacturing, engineering, and pharmaceuticals. He is a Fellow of the American Statistical Association and a member of the American Society of Quality. Connie M. Borror is Assistant Professor of Engineering in the Department of General Engineering at the University of Illinois at Urbana–Champaign. She is the author or coauthor of over 35 journal articles. Her research interests include advances in experimental design, response surface methodology, statistical process control, and measurement systems analysis. She is a Senior Member of the American Society of Quality. Douglas C. Montgomery is the ASU Foundation Professor of Engineering at Arizona State University, Tempe. He is the author of 13 books and over 160 technical papers, and is a recipient of the Shewhart Medal, the Brumbaugh Award, the Hunter Award, the Ellis R. Ott Award, and the Shewell Award (twice) from the American Society for Quality Control. He is one of the Chief Editors of Quality & Reliability Engineering International, a former Editor of the Journal of Quality Technology, and a member of several other editorial boards. Professor Montgomery is a Fellow of the American Statistical Association and the American Society of Quality.