Optimal Designs of EWMA Charts for Monitoring the Coefficient of Variation Based on Median Run Length and Expected Median Run Length

W. L. TeohJ. Y. LimMichael B. C. KhooZ. L. ChongW. C. Yeong2024-10-252024-10-252019-01-02https://doi.org/10.1520/JTE20170118https://dspace-cris.utar.edu.my/handle/123456789/4924Abstract The shape of run-length distribution changes with process shifts. This leads to complexity in interpreting the average run length performance. In this article, we show that the percentiles of the run-length distribution, especially the median run length (MRL), are more intuitive. The 5th and 95th percentiles of the run-length distribution are also provided in order to investigate the variation and spread of the run length. We develop two new optimal-design procedures for the exponentially weighted moving average (EWMA) charts, for monitoring the coefficient-of-variation (CV) squared (EWMA-γ2). These include minimization of the out-of-control MRL and the out-of-control expected MRL for deterministic and unknown shift sizes, respectively. Both the zero and steady states are discussed in this article. The optimal EWMA-γ2 chart is illustrated with real industrial data obtained from a metal sintering process. A comparative study reveals the superiority of the EWMA-γ2 charts for certain ranges of shifts in the CV.Optimal Designs of EWMA Charts for Monitoring the Coefficient of Variation Based on Median Run Length and Expected Median Run Lengthjournal-article