<b>Comparisons of multivariate GR&R methods using bootstrap confidence interval

• Main Authors: Rogério Santana Peruchi, Helio Maciel Junior, Nilson José Fernandes, Pedro Paulo Balestrassi, Anderson Paulo Paiva
• Format: Article
• Language: English
• Published: Universidade Estadual de Maringá 2016-08-01
• Series: Acta Scientiarum: Technology
• Subjects: measurement system analysis; repeatability and reproducibility; multivariate analysis of variance; principal component analysis.
• Online Access: http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/29294

This paper aimed to compare the performance of multivariate GR&R (gage repeatability and reproducibility) studies based on PCA (principal component analysis) and Manova (multivariate analysis of variance) methods. To estimate the multivariate gauge index, geometric and arithmetic means have been implemented with and without weighting strategies. Bootstrap confidence interval based on BCa (bias-corrected and accelerated) method has been adopted to determine multivariate gauge index adequacy. This confidence interval was calculated for the mean of univariate gauge indices estimated from each quality characteristic. The result analyses have shown that weighted approaches provided the best estimates of gauge index in multivariate GR&R studies.