Abstract
This paper examines the performance of the Homogeneously Weighted Moving Average on Wilcoxon Rank- Sum statistic (W-HWMA) and the Enhanced W-HWMA (W-EHWMA) control charts under different distributional conditions. The enhanced scheme adds an extra smoothing-parameter weighting to the variance structure to increase sensitivity to small and moderate size changes in processes without affecting the long-memory characteristics of weighted-average charts. The performance of the proposed chart was investigated in terms of the run length properties using comprehensive Monte Carlo simulations under the Normal, Student-t, Exponential and Weibull distributions. The findings indicate that the distributional robustness of both charts is high, but the novel W-EHWMA chart is more effective than the W-HWMA chart and across the investigated distributions and smoothing parameters, the proposed scheme generally produced lower ARL₁ and EARL values than the W-HWMA scheme, with the magnitude of improvement depending on the distribution, shift size and smoothing parameter. The superior design also produces narrower and more stable control limits that favours earlier out-of-control detection capability for small deviations in the process irrespective of the type of distribution. The simplicity and effectiveness in the practicality of the proposed W-EHWMA chart offer a significant advantage over the existing nonparametric charts.