An efficient mixed-memory-type control chart for normal and non-normal processes

Abstract

Statistical Process Control (SPC) techniques are commonly used to monitor process performance. Control charting technique is the most sophisticated tool of SPC and is categorized as memory-less and memory-type control charts. Shewhart-type control charts are of low efficiency in detecting small changes in the process parameters and are named as memory-less control charts. Memory-type control charts (e.g., Cumulative Sum (CUSUM) and ExponentiallyWeighted Moving Average (EWMA) charts) are very sensitive to small persistent shifts. In connection with enhancing the performance of CUSUM and EWMA charts, an efficient variant of memory-type charts for the location parameter is developed based on mixing the Double ExponentiallyWeighted Moving Average (DEWMA) chart and CUSUM chart by performing exponential smoothing twice. Performance of the proposed efficient variant is compared with existing counterparts under normal and nonnormal (heavy tails and skewed) environments. This study also provides an industrial application related to the monitoring of weights of quarters made by mint machine placed into service at U.S. Mint. From theoretical and numerical studies, it is revealed that the proposed variant of memory-type charts outperforms the counterparts in detecting shifts of small and moderate magnitudes.