A modified EWMA signed rank control chart for enhanced quality monitoring in the automobile industry

Control charts may aid in maintaining and improving the efficiency of manufacturing and industrial processes. Nonparametric control charts are more dependable and practical than parametric charts when it is unclear how the data will be distributed. Also, when the distribution of the underlying process is unknown or uncertain, nonparametric control charts are required. The nonparametric charts are a reliable alternative that also can quickly detect shifts in process parameter(s). For effective process location monitoring, we have developed a nonparametric extended exponentially weighted moving average chart based on the Wilcoxon signed rank test under ranked set sampling (hereafter named REEWMA_WSR). The performance of the proposed REEWMA_WSR chart has been evaluated by calculating the run-length properties using the Monte Carlo simulations approach. The in-control and out-of-control run-length profiles of the proposed chart are also investigated under normal, non-normal, and contaminated normal distributions. Performance comparison of the proposed REEWMA_WSR chart is done with various usual and nonparametric charts. The proposed chart's practical implementation is also illustrated using a real-life application.