Distribution-free monitoring of univariate processes

Peihua Qiu and Zhonghua Li

Statistics & Probability Letters, 2011, vol. 81, issue 12, 1833-1840

Abstract: We consider statistical process control (SPC) of univariate processes when observed data are not normally distributed. Most existing SPC procedures are based on the normality assumption. In the literature, it has been demonstrated that their performance is unreliable in cases when they are used for monitoring non-normal processes. To overcome this limitation, we propose two SPC control charts for applications when the process data are not normal, and compare them with the traditional CUSUM chart and two recent distribution-free control charts. Some empirical guidelines are provided for practitioners to choose a proper control chart for a specific application with non-normal data.

Keywords: Distribution-free; Non-Gaussian data; Nonparametric procedures; Transformation; Wilcoxon signed-rank test (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (3)

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DOI: 10.1016/j.spl.2011.07.004

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