Assessment of \(T^2\)- and \(Q\)-statistics for detecting additive and multiplicative faults in multivariate statistical process monitoring

DOI10.1016/j.jfranklin.2016.10.033zbMath1359.62285OpenAlexW2547275952MaRDI QIDQ509339

Yong-Cai Geng, Sumit K. Garg

Publication date: 9 February 2017

Published in: Journal of the Franklin Institute (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jfranklin.2016.10.033

zbMATH Keywords

fault detection\(Q\)-statistic\(T^2\)-statisticmultivariate statistical process monitoring (MSPM)

Mathematics Subject Classification ID

Multivariate analysis (62H99) Applications of statistics in engineering and industry; control charts (62P30)

Related Items (4)

Online reconstruction and diagnosibility analysis of multiplicative fault models for process-related faults ⋮ Canonical correlation analysis-based explicit relation discovery for statistical process monitoring ⋮ Multivariate statistical process monitoring based on principal discriminative component analysis ⋮ KPI relevant and irrelevant fault monitoring with neighborhood component analysis and two-level PLS

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