On monitoring the standard deviation of log-normal process

Control charts are widely used in the manufacturing and service sectors to track, regulate, and enhance process output. A manufacturing industry desires to utilize a control chart that has an effective structure and is sensitive to detect infrequent variations in the process. Generally, control charts are developed with the presumption that the understudy quality variable is normally distributed. In actual application, many processes have skewed distributions. The purpose of this study is to use the moving average (MA) charts to track the dispersion of a log-normal distribution. The design of the proposals is developed and the performance is assessed by run-length properties. The cumulative distributions of run-length under in-control and out-of-control are provided to have a broad view of the performance. The simulation findings show that when the value of the log-normal dispersion parameter is large, the proposed chart is more sensitive to the changes in the dispersion. Additionally, an industrial application is given to illustrate the suggested charts in this research.