New EWMA Control Charts for Monitoring Mean Under Non-normal Processes Using Repetitive Sampling

Control charts in statistical process control are powerful tools for assessing the process stability. The traditional charts perform well under the assumption of normality, but when data violate the assumption of normality, the robust approaches are needed. The aim of the research is to develop exponentially weighted moving average control charts for mean (EWMAM) based on M-scale estimators with in-control variance under non-normal processes using repetitive sampling scheme. Since M-scale estimators are considered as an alternative to standard deviation, the control charts are developed using these estimators. The performance of proposed charts is compared with the traditional EWMAM chart on the basis of out-of-control average run lengths. The application on practical data set is also provided.