A Comparative Performance Evaluation of Some Signed-Rank Based Control Charts via Monte Carlo Simulations
Abstract
Nonparametric control charts offer a robust alternative to traditional parametric charts, particularly when the underlying process distribution is unknown or difficult to specify. This paper investigates several signed-rank (SR) based control charts, including Shewhart, cumulative sum (CUSUM), and exponentially weighted moving average (EWMA) charts, through a comprehensive comparative evaluation. The performance of the control charts is evaluated under multiple sample sizes and across various process distributions (normal, uniform, Laplace, and logistic). A practical simulation example is also provided to demonstrate each chart’s ability to detect shifts in process location. The performance of the control charts evaluated through Monte Carlo simulations, with the average run length (ARL) as a performance measure. The study provides actionable insights for selecting the most effective nonparametric control chart under varying conditions, offering both methodological and practical contributions to the literature
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References
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Published
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2026-07-09
