Exponentially weighted moving average control charts based on the moving average statistic and lnS² for monitoring a Weibull process with subgroups

In this paper, we propose 2 new exponentially weighted moving average (EWMA) control charts based on the moving average (MA) statistic and lnS2 to monitor the process mean and variability of a Weibull process with subgroups. The inverse error function is used to transform the Weibull-distributed data to a standard normal distribution. The Markov chain approach is used to derive the average run length (ARL). Subsequently, the performances of the proposed charts with other existing control charts are provided. The comparison shows that the EWMA-MA outperforms the (Formula presented.) and EWMA- (Formula presented.) control charts for monitoring the process mean of ARL values. The comparison also shows that the EWMA-lnS2 outperforms the S2 and S2-MA control charts for monitoring the process variability of ARL value. Two examples are used to illustrate the application of the proposed control charts.