AS2-GWMA control chart for monitoring the process variability

Abstract

In the present article, we propose a generally weighted moving average control chart based on a three-parameter logarithmic transformation for monitoring shifts in the process variability (regarded as S 2-GWMA chart). Monte Carlo simulations are used to evaluate its performance in terms of the run-length distribution. A comparison study versus the S 2-EMWA, S 2-CUSUM, CS-EWMA, S 2-HEWMA and GWMAV charts indicates that the proposed chart is more effective than its competitors in detecting small to moderate upward shifts while it performs similarly with the other charts for large shifts. Finally, a real example is presented to display the application of the S 2-GWMA chart.

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