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A gradient approach to efficient design and analysis of multivariate EWMA control charts
Authors:Wenpo Huang  Wei Jiang
Institution:1. School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an, Shaanxi, People's Republic of China;2. Antai College of Economics and Management, Shanghai Jiao Tong University, Shanghai, People's Republic of China
Abstract:Compared to the grid search approach to optimal design of control charts, the gradient-based approach is more computationally efficient as the gradient information indicates the direction to search the optimal design parameters. However, the optimal parameters of multivariate exponentially weighted moving average (MEWMA) control charts are often obtained by using grid search in the existing literature. Note that the average run length (ARL) performance of the MEWMA chart can be calculated based on a Markov chain model, making it feasible to estimate the ARL gradient from it. Motivated by this, this paper develops an ARL gradient-based approach for the optimal design and sensitivity analysis of MEWMA control charts. It is shown that the proposed method is able to provide a fast, accurate, and easy-to-implement algorithm for the design and analysis of MEWMA charts, as compared to the conventional design approach based on grid search.
Keywords:Optimal design  sensitivity analysis  false position method  Markov chain
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