Gauge R & R studies for angular measurements. Issue Volume 33:Issues 3(2021) (3rd July 2021)

• Record Type: Journal Article
• Authors: Hamada, Michael S.; Anderson-Cook, Christine M.; Weaver, Brian P.
• Is Part Of: Quality engineering. Volume 33:Issues 3(2021)
• Page Start: 523
• Page End: 532
• Publication Date: 2021-07-03
• Subjects: Bayesian inference -- circular data -- directional data -- Markov chain Monte Carlo -- mixed effects -- random effects -- repeatability -- reproducibility -- variance components -- von Mises distribution -- wrapped normal distribution; Quality control -- Periodicals; Production management -- Quality control -- Periodicals; 658.5
• DOI: 10.1080/08982112.2021.1928190
• Languages: English
• ISSNs: 0898-2112

Abstract

Abstract: Angular measurements lie on the circumference of a circle and have different characteristics than standard scalar measurements. For applications involving angular data, treating the measured values as scalars can lead to misinterpretation of results if its wrap-around nature is not taken into account. In this article, we propose a variance components wrapped normal model for angular measurements that is analogous to the standard normal model for continuous measurements. This model allows decomposition of contributions to the overall variance to be separated and compared to understand the drivers of the spread of the data. We analyze gauge R & R study data using Bayesian methods and illustrate the use of this wrapped normal model with simulated and real data. We also performed a small simulation study in considering the design of gauge R & R studies with angular measurements.