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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