Most control charts that assume quality characteristics of interest follow a normal or specific distribution. However, in reality there is often limited or no information regarding the underlying process distribution. Therefore, in recent years, nonparametric techniques for quality control have been developed. In this paper, the nonparametric generally weighted moving average sign chart based on repetitive sampling (hereinafter RS-GWMA sign chart) is proposed to improve performance capability of existing charts in small process shifts. Simulation studies show that the nonparametric RS-GWMA sign chart with large design and adjustment parameters outperforms competing charts considered in this article. The fill volume of soft-drink beverage bottles is as industrial example used to illustrate the application of the proposed nonparametric RS-GWMA sign chart.
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COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
