Abstract:
The objective of this research are to propose a new control chart, namely, Generally Weighted Moving Average - Tukeys control chart (GWMA-TUKEY) for monitoring changes in processes when processes are symmetric and asymmetric distributions. The performance of GWMATUKEY control chart is compared with Tukeys control chart (TUKEY), Generally Weighted Moving Average (GWMA) and Exponentially Weighted Moving Average Tukeys control chart (EWMA-TUKEY) in monitoring of processes changes are measured by Average Run Length (ARL) as performance criteria. The Average Run Length of GWMA-TUKEY and EWMA-TUKEY control chart are approximated by Monte Carlo simulation and the ARL of TUKEY control chart are calculated by explicit formulas. The numerical results show that when processes are symmetric distributions the GWMATUKEY is superior to TUKEY and EWMATUKEY for all magnitudes of change. In addition, when processes are asymmetric distributions the GWMATUKEY is more efficient to detecting small and moderate change in process except exponential distribution.