Nonparametric adaptive cumulative sum charting scheme for monitoring process location

Abstract

Abstract For effective monitoring of the range of sustainable changes in the process median, a nonparametric adaptive cumulative sum signed‐rank (NPACUSUM‐SR) control chart has been suggested in this study. Through the use of Monte Carlo simulation, the numerical analysis of the suggested NPACUSUM‐SR scheme has been calculated for zero and steady states. Run length (RL) profiles have been used to explore and compare the proposed NPACUSUM‐SR chart's in‐control resilience under various symmetrical heavy‐tailed, light‐tailed, and contaminated normal distributions. The suggested NPACUSUM‐SR chart has undergone a thorough investigation of the competition using Wilcoxon signed‐rank statistics and sign statistics under steady‐state and zero‐state conditions. The comparison shows that the suggested NPACUSUM‐SR design is superior to its competitors, especially when considering steady‐state performance over a wide range of shifts. This study examines the viability of the suggested design through a manufacturing‐related application.

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