A COMBINED MLE AND EWMA CHART APPROACH TO ESTIMATE THE CHANGE POINT OF A GAMMA PROCESS WITH INDIVIDUAL OBSERVATIONS

作者：Shao Yuehjen E; Hou Chia Ding^*

来源：International Journal of Innovative Computing Information and Control, 2011, 7(5A): 2109-2122.

• Exponentially weighted moving average
• Gamma process
• Individual observations
• Change point
• Maximum likelihood estimation

Statistical process control (SPC) charts are commonly used for detecting process disturbances. However, they do not provide enough information to identify the root causes of an out-of-control process. This difficulty can be overcome if we are able to promptly estimate the change point of a process, due to the fact that the change point usually reveals the most accurate information about root causes. As a consequence, this estimation becomes a very important research issue in SPC applications. Although recent studies have shown that the maximum likelihood estimation (MLE) estimator could be an effective estimate of the change point for a normal process, very little is known about the feasibility of using an MLE estimator for a gamma process with individual observations. In this study, our goal is to propose a fruitful approach to solving this problem. This study proposes the combination of MLE and the exponentially weighted moving average (EWMA) control charts to estimate the change point of a gamma process. We investigate various SPC modes and gamma process designs in this study, and the results show that an effective change point estimator could be achieved.

• 出版日期2011-5