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High-Dimensional Process Monitoring and Fault Isolation via Variable Selection

Summary: [This abstract is based on the authors' abstract.] A variable-selection-based multivariate statistical process control procedure is proposed for process monitoring and fault diagnosis in high-dimensional processes. Use of a forward-selection algorithm and a multivariate control chart enable in one step the detection of faulty conditions and the isolation of faulty variables. The effectiveness of the proposed procedure is demonstrated through simulation studies and a real example.

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  • Topics: Statistical Process Control (SPC), Quality Control
  • Keywords: Variable selection, Linear regression, Multivariate analysis, Statistical process control (SPC), T2 control chart
  • Author: Wang, Kaibo; Jiang, Wei
  • Journal: Journal of Quality Technology