Abstract
Control charts are used to identify the presence of an assignable cause of variation in the process. The non-parametric control chart is an emerging area of development in the theory of SPC. Its main advantage is that it does not require any knowledge about the underlying distribution of the variable. In this paper two non-parametric control charts for controlling variability are derived based on two non-parametric tests. Their in-control state performance is analyzed for different distributions by means of simulations. Furthermore, their efficiency in detecting shifts in the variability is evaluated.
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