Multistage process control and monitoring via group EWMA schemes

Based on an engineering model, a statistical process control (SPC) method for processes with multiple stages is proposed in this paper. In phase I of the SPC analysis, a maximum likelihood estimation procedure is developed using EM algorithm. In phase II, the complex multistage monitoring problem is transferred to a simple multi-stream monitoring problem by applying group exponential weighted moving average charts to the one-step forecast errors of the model. Run length results show the efficiency of proposed charting method, and a heuristic run-rule-like approach is suggested to improve the traceability along the multiple stages. Two real multistage examples in hood manufacturing and workpiece assembly are presented to illustrate the efficiency of the proposed method.