Resumen de Causation-Based T-Squared Decomposition for Multivariate Process Monitoring and Diagnosis

Jing Li, Jionghua Jin, Jianjun Shi

• 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.