A Bayesian Approach to Multivariate Measurement System Assessment. Issue 3 (1st July 2016)

• Record Type: Journal Article
• Authors: Hamada, Michael S.
• Is Part Of: Journal of quality technology. Volume 48:Issue 3(2016)
• Page Start: 246
• Page End: 252
• Publication Date: 2016-07-01
• Subjects: Gauge R & R Study -- Markov-Chain Monte Carlo -- Multivariate Normal Distribution -- Random Effects -- Repeatability -- Reproducibility -- Scaled Inverse Wishart Prior Distribution -- Uncertainty -- Variance Components; Quality control -- Periodicals; Qualité -- Contrôle -- Périodiques; Quality control; Quality control; Periodicals; 620.0045
• DOI: 10.1080/00224065.2016.11918164
• Languages: English
• ISSNs: 0022-4065

Abstract

Abstract : This article considers system assessment for multivariate measurements and presents a Bayesian approach to analyzing gauge R & R study data. The evaluation of variances for univariate measurement becomes the evaluation of covariance matrices for multivariate measurements. The Bayesian approach ensures positive definite estimates of the covariance matrices and easily provides their uncertainty. Moreover, various measurement-system assessment criteria are easily evaluated. The approach is illustrated with data from a real gauge R & R study as well as simulated data.