This analysis introduces a nonparametric control chart using the signed-rank statistic, suggesting improved efficiency while monitoring location parameters.
Nonparametric control charts are widely used in many manufacturing processes when there is a lack of knowledge about the distribution that the quality characteristic of interest follows. If there is evidence that the unknown distribution is symmetric, then the signed-rank statistic is preferred over other nonparametric statistics because it makes control charts more efficient. In this article, a nonparametric double homogeneously weighted moving average control chart based on the signed-rank statistic, namely, the DHWMA-SR chart, is introduced for monitoring the location parameter of an unknown, continuous and symmetric distribution. Monte Carlo simulations are used to study the run-length distribution of the proposed chart. A performance comparison study with the EWMA-SR, DEWMA-SR and HWMA-SR charts indicates that the DHWMA-SR chart is more effective under the zero-state scenario, while its steady-state performance is poor. Finally, two illustrative examples are given to demonstrate the application of the proposed chart.
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Vasileios Alevizakos (2025) studied this question.
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