Mohammad javad Ershadi - M.Sc student Department of Industrial Engineering, Sharif University of Technology, Tehran, Iran
Seyed Taghi Akhavan Niaki - Ph.D., Professor Department of Industrial Engineering, Sharif University of Technology

Among the multivariate controtl charts that are used to monitor more than one correlated quality characteristics, the multivariate exponentially weghted moving average (MEWMA) is one of the best to detect small shifts in the process parameters. Design of a MEWMA control chart to possess minimum cost and high statistical properties is one of the major tasks in multivariate quality control environments. in this paper, the economic-statistical model of the MEWMA chart is considered and a genetic algorithm (GA) method is proposed to solve the model. then, the results of the proposed method are compared to the ones of an existing method through simulation study. the results show that while the optimal solutions are different, identical costs are obtained in an easire way with less effort. at the end, a sensitivity analysis and some practical results are presented.

control chart, Economic- Statistical Design, MEWMA, Genetic Algorithm