Exponentially weighted moving average control chart using stratified MiniMax ranked set sampling

Among various tools, the Exponentially Weighted Moving Average (EWMA) control chart proves to be effective in the early detection of moderate to small size shifts in the process mean, taking into account all the past and present data. In this study, a new method – Stratified MiniMax Ranked Set Sampling (StMMRSS) was proposed for more effective determination of parameters such as the population mean and developing an enhanced Exponentially Weighted Moving Average (EWMA) control chart. The newly proposed EWMA control chart was compared with those based on Simple Random Sampling (SRS), Stratified Random Sampling (StRS), Stratified Ranked Set Sampling (StRSS), and Stratified Extreme Ranked Set Sampling (StERSS). A simulation study using average run length (ARL) and standard deviation of run length (SDRL) demonstrates that the StMMRSS-based EWMA chart provides faster and more consistent detection of process mean shifts than SRS- and StRSS-based charts. A real dataset further confirms the practical effectiveness of the proposed method.