Improved Nonparametric Control Chart Based on Ranked Set Sampling with Application of Chemical Data Modelling

Abstract

e statistical performance of parametric control charts is questionable when the underlying process does not follow any speci ed probability distribution. Nonparametric control charts are the best substitute for this situation. On the other hand, the ranked set sampling technique is preferred over the simple random sampling technique because it reduces the variability of process parameters and improves the control chart’s performance. is study aims to o er a nonparametric double homogeneously weighted moving average control chart under Wilcoxon signed-rank test considering the ranked set sampling technique (regarded as NPDHWMARSS), to further enhance the process location monitoring. e proposed chart’s run-length performance is compared with competing control charts, such as DEWMA-X, NPDEWMA-SR, NPRDEWMA-SR, DHWMA, and NPHWMARSS control charts. e comparison revealed that the proposed NPDHWMARSS control chart outperformed the other competing control charts, particularly for small to moderate shifts in process location. Finally, a real-life application is also o ered for quality practitioners to show the strength of the proposed control chart