Design of an adaptive control chart with variable sampling intervals using the maximum exponentially weighted moving average (EWMA) of squared deviations
Volume 5, Issue 1, Spring 2015, Pages 1-12
Amir hossain Amiri, Atena Rahimi Jafari, Reza Kamranrad
Abstract Control chart is one of the most widely used statistical control tools of processes that plays an important role in improving their quality. One of the weaknesses of its low speed control diagrams is the detection of changes in the process parameter. To this end, adaptive control charts have been developed to improve the performance of control charts to detect small changes. In this paper, the adaptive method of variable sampling distance is used to improve the performance of the control chart of the maximum exponentially balanced moving average squared-exponential moving average squared deviation to detect changes in mean and variance and simultaneous changes in mean and variance. The performance of the proposed method is compared with the sampling control diagram at fixed intervals using simulations and the criteria of mean time to alert and moderate time to alarm occurrence. The results show that the proposed method performs better than the control chart results in the research literature for large changes.