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Title: Generally weighted moving average control charts Authors:  Schalk Human - University of Pretoria (South Africa) [presenting]
Niladri Chakraborty - University of Pretoria (South Africa)
Balakrishnan Narayanaswamy - McMaster University (Canada)
Abstract: Distribution-free control charts gained momentum in recent years as they are more efficient in detecting a shift when there is a lack of information regarding the underlying process distribution. However, a distribution-free control chart for monitoring the process location often requires information on the in-control process median. This is somewhat challenging because, in practice, any information on the location parameter might not be known in advance and estimation of the parameter is therefore required. Parameter estimation from an in-control reference sample typically requires a large number of observations to attain reasonable chart performance when quick detection of a small shift in the location is important. In view of this, a time-weighted control chart, labelled the Generally Weighted Moving Average (GWMA) exceedance (EX) chart (in short GWMA-EX chart), is proposed for detection of a shift in the unknown process location; this chart is based on an exceedance statistic when there is no information available on the process distribution. An extensive performance analysis shows that the proposed GWMA-EX control chart is, in many cases, better than its contenders.