Research Output
The performances of mixed ewma-cusum control charts based on median-based estimators under non-normality
The effectiveness of robust mixed EWMA-CUSUM control chart on G-and-H distribution
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Publication
Exponentially weighted moving average (EWMA) and cumulative sum (CUSUM) charts have been regularly used to monitor small process mean shifts. More recently, a mixture of EWMA and CUSUM charts known as mixed EWMA-CUSUM (MEC) control chart has been introduced for better small shift detection. However, like its predecessor, the MEC chart requires the normality assumption to ensure optimal performances. In the presence of outliers, which is the cause of non-normality, the parameters of the chart may be overestimated, leading to an unreliable monitoring process. To mitigate this problem, this paper employed median-based estimators namely, the median and modified one-step M-estimator (MOM), to control the location parameter via the MEC control chart. In this study, the performance of robust MEC charts for Phase II monitoring of location was compared with the standard MEC chart that is based on the sample mean. The performance of the robust MEC charts in terms of the average run length (ARL) on various g-and-h distributions clearly shows that a robust MEC chart based on the MOM estimator performs well regardless of the distributional shapes.
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Publication
Cumulative sum (CUSUM) chart and exponentially weighted moving average (EWMA) chart are popularly used in statistical process control (SPC) as they can quickly detect small shifts in the process mean. Recently, a Mixed EWMA-CUSUM (MEC) control chart was introduced for better detection of small shifts. Like the EWMA and CUSUM control charts, the MEC chart relies on the normality assumption for optimal performances. In the case that the underlying distribution of the data is non-normal, the chart may no longer be effective in signaling a true out-of-control process. Therefore, this paper proposed the use of a median estimator for Phase II monitoring of location via the MEC chart. The performance of this robust MEC control chart was tested on various g-and-h distributions in terms of the average run length (ARL). It has been found to perform well regardless of the distributional shapes compared to the standard MEC chart which uses the mean as the estimator.