Prof. Lianjie SHU, Faculty of Business Administration, University of Macau. Efficient Design of Markovian-type Control Charts May 8, 2013 (Wednesday), 11:00am-12:00pm Room 510, Shun-de Building-Department of Industrial Engineering, Tsinghua University

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Prof. Lianjie SHU, Faculty of Business Administration, University of Macau. Efficient Design of Markovian-type Control Charts May 8, 2013 (Wednesday), 11:00am-12:00pm Room 510, Shun-de Building 2013.05.07

【Title】Efficient Design of Markovian-type Control Charts

【Speaker】Prof. Lianjie SHU, Faculty of Business Administration, University of Macau.

【Host】Dr. Kaibo Wang

【Time】May 8, 2013 (Wednesday), 11:00am-12:00pm

【Location】Room 510, Shun-de Building

【Abstract】The statistical control chart is conventionally designed to minimize the detection performance at a particular shift while maintaining a fixed in-control performance. This optimal design is often carried out based on Monte Carlo simulations, which require a large number of simulation replicates in order to achieve high accuracy. This talk investigates the optimal design of Markovian-type control charts. In particular, a novel gradient approach is developed for this purpose when a control chart possesses the Markovian properties. This efficiency of this approach is illustrated based on two examples: the design of exponentially weighted moving average (EWMA) control charts, and the design of cumulative sum (CUSUM) control charts under random shifts.

【Bio】Dr. Lianjie Shu is currently an Associate Professor in Faculty of Business Administration at University of Macau. He received his Bachelor degree in Mechanical Engineering and Automation from Xi'an Jiao Tong University, and his Ph.D. in Industrial Engineering and Engineering Management from the Hong Kong University of Science and Technology (HKUST). He currently serves an Associate Editor on Journal of Statistical Computation and Simulation and a Senior Editor on Journal of the Chinese Institute of Industrial Engineers. His recent research interests include statistical quality control, healthcare surveillance, and statistical computing. His publications appear on a wide variety of journals such as Statistics in Medicine, Naval Research Logistics, IIE Transactions, Journal of Quality Technology, etc.

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