Control charts require a reference distribution of typical process behavior in which to judge abnormal behavior. Unfortunately, the mere presence of special causes taints the grand average and pooled variance, which alters the construction of control chart limits and diminishes the ability of the chart to accurately detect process changes. This paper describes a short-run charting approach incorporating robust median-based centerline estimates that will yield the intended performance of the theoretical chart.
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