Phase II monitoring of generalized linear proles under dierent types of changes

Various control charts have been proposed to monitor generalized linear proles in Phase II. However, the robustness of the proposed methods in detecting dierent types and especially dierent directions of changes is not well-studied in the literature. In realworld applications, dierent kinds of change such as drift and multiple changes are likely to occur, which can be isotonic (increasing) or antitonic (decreasing). This paper studies the robustness of the Rao Score Test (RST) method, T2, and Multivariate Exponential Weighted Moving Average (MEWMA) in dierent types, drift and multiple, and directions of changes. The RST method also benets from a change-point detection approach whose performance is studied as well. According to the results, generally, the RST method shows a better performance in detecting dierent types of changes. Moreover, the performance of the RST method is robust to the direction of the change, while T2 and MEWMA are not ARL-unbiased and show dierent performances under isotonic and antitonic changes. Therefore, to address this issue, a bias-reduced estimator is proposed for use in T2. The results demonstrate that the proposed control chart outperforms T2 and is less biased than T2. Finally, a real-world problem is presented in which the aforementioned methods are applied to real data.