Monitoring feedback-controlled processes using adaptive T~2 schemes

摘要

The integration of engineering process control (EPC) and statistical process control (SPC) has drawn wide attention because of its capability to minimize long-term process variation and improve product quality. However, dynamic shift patterns are usually observed when feedback-control loops exist, which consequently lead to poor charting performance. In this paper, the dynamic patterns in mean shifts of proportional integral (PI) controlled and minimum mean square error (MMSE) controlled processes are formulated and analysed. In conjunction with a model-free forecasting algorithm, an adaptive T~2 charting procedure is applied to improve detection power. This adaptive procedure is constructed upon the uniformly most powerful (UMP) unbiased test with the consideration of time-varying patterns. Monte Carlo simulations have shown that the proposed strategy possesses significantly improved detection sensitivity over intended shift ranges.