Int. J. Productivity and Quality Management, Vol. 11, No. 2, 2013 131 Copyright © 2013 Inderscience Enterprises Ltd. Multi-objective economic-statistical design of MEWMA control chart Amirhossein Amiri*, Hamed Mogouie and Mohammad H. Doroudyan Industrial Engineering Department, Faculty of Engineering, Shahed University, Tehran, P.O. Box 18151/159, Iran Fax: (+9821) 51212021 E-mail: amiri@shahed.ac.ir E-mail: mogouie@shahed.ac.ir E-mail: doroudyan@shahed.ac.ir *Corresponding author Abstract: The various advantages of MEWMA control chart such as the ability to detect small shifts in the process with multiple quality characteristics have motivated users to apply this chart for process monitoring. Considering the high costs of implementing MEWMA control chart, the economic-statistical design of this chart has been increasingly investigated. In most of the previous studies the cost function has been considered as the objective function while the statistical properties have been modelled as constraints in a mathematical programming. According to the dependency of the cost function on statistical properties in the constraints, the results of these methods are not efficient enough. In this paper, two multi-objective approaches, an aggregative and a non-aggregative approach are applied and optimised using a genetic algorithm. The proposed approaches are evaluated through a numerical example from the literature and the efficiency of the multi-objective approaches are verified in comparison with the previous methods. Keywords: MEWMA control chart; economic-statistical design; Lorenzen and Vance cost function; multi-objective approach; genetic algorithm; GA. Reference to this paper should be made as follows: Amiri, A., Mogouie, H. and Doroudyan, M.H. (2013) ‘Multi-objective economic-statistical design of MEWMA control chart’, Int. J. Productivity and Quality Management, Vol. 11, No. 2, pp.131–149. Biographical notes: Amirhossein Amiri is an Assistant Professor at Shahed University. He holds a BS, MS, and PhD in Industrial Engineering from Khajeh Nasir University of Technology, Iran University of Science and Technology, and Tarbiat Modares University, respectively. He is a member of the Iranian Statistical Association. His research interests are statistical quality control, profile monitoring, and Six Sigma. Hamed Mogouie is an MSc student of Industrial Engineering at Shahed University. His research interests are of design of experiments, statistical process control and quality management. Mohammad H. Doroudyan is an MSc student at Shahed University. He holds BS in Industrial Engineering from Azad University-South Tehran Branch. His research interests are statistical quality control and design of experiments.