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QICID: 24024
Title: Causation-Based T-Squared Decomposition for Multivariate Process Monitoring and Diagnosis
Copyright: ASQ
Author: Li, Jing; Jin, Jionghua; Shi, Jianjun
Organization:
Subject: Bayesian methods, Cause and effect analysis, Statistical process control (SPC), Hotelling's T2 statistic, Root cause analysis (RCA);
Series: Journal of Quality Technology, Vol. 40, No. 1, January 2008, pp. 46-58
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Abstract: [This abstract is based on the authors' abstract.]
The Hotelling T² control chart widely used in multivariate process monitoring can effectively detect a change in a system, but cannot diagnose the root causes of the change. The MTY approach improves diagnosability by decomposing the T² statistic, but is computationally intensive and has limited capability in root-cause diagnosis when the dimension of variables is high. A causation-based T² decomposition method is proposed that integrates the causal relationships revealed by a Bayesian network with the MTY approach. Simulation studies reveal that the proposed method reduces the computational complexity and enhances the diagnosability when compared to the MTY approach.
Number of pages: 13
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