A New Modified EWMA Control Chart for Monitoring Processes Involving Autocorrelated Data

Control charts are one of the tools in statistical process control widely used for monitoring, measuring, controlling, improving quality, and detecting problems processes various fields. The average run length (ARL) can be to determine efficacy a chart. In this study, we develop new modified exponentially weighted moving (EWMA) chart derive explicit formulas both two-sided ARLs p-order autoregressive (AR(p)) with exponential white noise on EWMA accuracy was compared that well-known numerical integral equation (NIE) method. Although methods were highly consistent an absolute percentage difference less than 0.00001%, ARL using method could computed much more quickly. Moreover, performance better standard based relative mean index (RMI). addition, illustrate applicability proposed practice, also applied real data from energy agricultural