A Comparative Study of Different Methodologies for Fault Diagnosis in Multivariate Quality Control

Different methodologies for fault diagnosis in multivariate quality control have been proposed in recent years. These methods work in the space of the original measured variables and have performed reasonably well when there is a reduced number of mildly correlated quality and/or process variables with a well-conditioned covariance matrix. These approaches have been introduced by emphasizing their positive or negative virtues, generally on an individual basis, so it is not clear for the practitioner the best method to be used. This paper provides a comprehensive study of the performance of diverse methodological approaches when tested on a large number of distinct simulated scenarios. Our primary aim is to highlight key weaknesses and strengths in these methods as well as clarifying their relationships and the requirements for their implementation in practice. Vidal Puig, S.; Ferrer, A. (2014). A Comparative Study of Different Methodologies for Fault Diagnosis in Multivariate Quality Control. Communications in Statistics - Simulation and Computation. 43(5):986-1005. doi:10.1080/03610918.2012.720745 Arteaga, F., & Ferrer, A. (2010). How to simulate normal data sets with the desired correlation structure. Chemometrics and Intelligent Laboratory Systems, 101(1), 38-42. doi:10.1016/j.chemolab.2009.12.003 Doganaksoy, N., Faltin, F. W., & Tucker, W. T. (1991). Identification of out of control quality characteristics in a multivariate manufacturing environment. Communications in Statistics - Theory and Methods, 20(9), 2775-2790. doi:10.1080/03610929108830667 Fuchs, C., & Benjamini, Y. (1994). Multivariate Profile Charts for Statistical Process Control. Technometrics, 36(2), 182-195. doi:10.1080/00401706.1994.10485765 Hawkins, D. M. (1991). Multivariate Quality Control Based on Regression-Adiusted Variables. Technometrics, 33(1), 61-75. doi:10.1080/00401706.1991.10484770 Editorial Board. (2007). Computational Statistics & Data Analysis, 51(8), iii-v. doi:10.1016/s0167-9473(07)00125-9 Hayter, A. J., & Tsui, K.-L. (1994). Identification and Quantification in Multivariate Quality Control Problems. Journal of Quality Technology, 26(3), 197-208. doi:10.1080/00224065.1994.11979526 HOCHBERG, Y. (1988). A sharper Bonferroni procedure for multiple tests of significance. Biometrika, 75(4), 800-802. doi:10.1093/biomet/75.4.800 HOMMEL, G. (1988). A stagewise rejective multiple test procedure based on a modified Bonferroni test. Biometrika, 75(2), 383-386. doi:10.1093/biomet/7