ARL PERFORMANCES OF CONTROL CHARTS FOR AUTOCORRELATED DATA

In the use of traditional control charts the most important assumption is that the observations on process or product characteristics are independent. However, as a result of improvements in measurement techniques sampling intervals become shorter, and this causes serial cot-relation in data. Besides this, in chemical processes serial correlation is inherent in consecutive measurements. In this case, traditional control charts such as Shewhart X and CUSUM, estimate process parameters with bias, an this causes poor ARL performance. Therefore some modifications for traditional control charts are necessary. Residual control charts such as X residual and EWMA residual are widely used control charts for autocorrelated data. In the last decade, EWMAST, ARMAST, and DFTC charts have been also introduced for this type of data. To compare the performances of control charts have attracted interest of researchers. In the relevant literature, although there have been a lot of comparison studies, in only few of them the first-order autoregressive moving average process have been investigated. In this study we compare ARL performances of Shewhart X CUSUM, X residual, EWMA residual, EWAMST, ARMAST and DFTC charts when there is shift in the mean.