Sensitive Non-Parametric Control Charts For Monitoring Process Variation

Non-parametric or distribution-free control charts are useful in statistical process control when there is limited or a lack of knowledge about essential process distribution. In this article, nonparametric control charts were considered based on Mood and Sukhatme statistics. Two non-parametric statistics were applied on Exponentially-Weighted Moving Average (EWMA) and Cumulative Sum (CUSUM) charts for monitoring process variation. Simulations showed that the EWMA control chart based on Mood statistics was more sensitive for detection of small shifts in process variation, but moderate and large shifts in CUSUM based on Mood statistics were more sensitive than other charts.

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