April 21st-23rd
 Nagoya, Japan

Keynote Speakers

       Prof. Felix T. S. Chan

The Hong Kong Polytechnic University


Professor Felix T. S. Chan received his BSc Degree in Mechanical Engineering from Brighton Polytechnic (now University), UK, and obtained his MSc and PhD in Manufacturing Engineering from the Imperial College of Science and Technology, University of London, UK. Professor Chan is now working at the Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, and also serving as Associate Dean (Research) at the Faculty of Engineering. His current research interests are Logistics and Supply Chain Management, Operations Management, Distribution Coordination, Systems Modelling and Simulation, AI Optimisation. To date, he has published 16 book chapters, over 300 refereed international journal papers and 250 peer reviewed international conference papers, h index= 30 under the Web of Science. He is a chartered member of the Chartered Institute of Logistics and Transport in Hong Kong. According to a study lately published in the International Journal of Production Research (http://dx.doi.org/10.1080/00207543.2015.1037935), the study measured the research contributions over a 26-year time frame (1985–2010) of academic institutions and individual authors to the field of Operations Management (OM) based on published articles in 11 top-rated and well-known academic OM journals. Professor Chan was among the top 50 prolific authors list who have made the greatest overall contribution to the field as measured by the number of distributed and shared articles published in the 11 designated journals. Also, Professor Chan was Ranked No. 3 in The top 100 authors as the most productive researchers in the field of Operations Management over the past 10 years (2001–2010).

 

     Prof. Shey-Huei Sheu

Providence University, Taiwan

Shey-Huei Sheu is a Chair Professor of Department of Statistics and Informatics Science at the Providence University. He is an Honorary Chair Professor of the Department of Industrial Management at the National Taiwan University of Science and Technology. He received his M.S. degree (1979) in applied mathematics from the National Tsing Hua University and his Ph.D. degree (1987) in statistics from the University of Kentucky. He has published in journals such as Naval Research Logistics, Journal of Applied Probability, RAIRO Operations Research, Microelectronics and Reliability, Reliability Engineering and System Safety, International Journal of Systems Science, Quality and Reliability Engineering International, International Journal of Reliability, Quality and Safety Engineering, Journal of the Operational Research Society, European Journal of the Operational Research, Computers and Operation Research, Computers and Industrial Engineering, Quality Engineering, Asia-Pacific Journal of the Operational Research, Communications in Statistics-Theory and Methods, Computers and Mathematics with Applications, Simulation Modeling Practice and Theory, Communications in Statistics-Simulation and Computation, Journal of Statistical Computation and Simulation, International Journal of Production Economics, Quality Technology and Quantitative Management, The International Journal of Advanced Manufacturing Technology, Expert Systems, International Journal of Computer Mathematics, Journal of Applied Statistics, Production Planning and Control, International Journal of Production Research, Applied Mathematical Modelling, IEEE Transactions on Reliability, and Annals of Operations Research.

 

“Multi-Attribute Replacement Policy in a Cumulative Damage Model”

Abstract-The purpose of this paper is to investigate an optimal preventive replacement policy based on multi-attributes in a two-unit system. The system is subject to two types of shocks (I and II) and the probabilities of these two shock types are age-dependent. Each type I shock causes a minor failure of unit A and yields a random amount of additive damage to unit B and type II shock causes the system to fail completely. Unit B may also fail with a probability and be rectified by a minimal repair. In this study, we consider a replacement policy based on system age, nature of failure, number of type I shocks, and the cumulative damage to unit B. To minimize the expected cost per unit time, the optimal policy is derived analytically and computed numerically. The proposed model, extending many existing models, provides a general framework for analyzing maintenance polices.

 

      Prof.George Zhang

Western Washington University, USA


Zhe George Zhang is a professor of Management Science in the Department of Decision Sciences at Western Washington University and a professor of Operations Management in Beedie School of Business at Simon Fraser University. He is also visiting professor of Sauder School of Business at the University of British Columbia. Dr. Zhang received his BS in Computer Science and MA in Economics from Nankai University, China; his MBA from the Schulich School of Business at York University; and his PhD in Operations research from the University of Waterloo. Professor Zhang has published many papers in prestigious journals such as Management Science, Operations Research, Manufacturing & Service Operations Management, Production and Operations Management, IIE Transactions, IEEE Transactions, Queueing Systems, Journal of Applied Probability. Co-authored with Professor Tian in 2006, he published the research monograph "Vacation Queueing Models - Theory and Applications," the first book on this particular topic (now highly cited). Professor Zhang's research interests include queueing theory and applications and stochastic models for manufacturing and service systems. The main theme of his research is to bridge the gap between theory and application, obtaining unobservable and sometimes counter-intuitive but significant/practical management insights via modeling and quantitative analysis. Currently, he is particularly interested in the quantitative and economic analysis of the congestion problems in urban/mass transportation networks, health/medical care systems, and public service systems with both customer service quality and security concerns. As an expert in data analysis and quantitative modeling, he has consulted in industry and has given research seminars and short lectures at leading universities around the world. He was invited to present plenary or keynote talks in several international conferences.Professor Zhang is the one of Editor-in-Chiefs for new journal Queueing Models and Service Management, aan associate editor of INFOR (Information Systems and Operations Research), and is on the editorial board of several international journals in Operations Research and Management Science.

 

Plenary Speaker

      Professor Wheyming Song

National Tsing Hua University, Taiwan


WHEYMING TINA SONG is a professor in the Department of Industrial Engineering and Engineering Management at the National Tsing Hua University, Taiwan, R.O.C. She received her undergraduate degree in statistics and master's degree in industrial engineering at Cheng-Kung University in Taiwan. She then received her master's degree in applied mathematics and industrial engineering from the University of Pittsburgh. Her Ph.D. is from the School of Industrial Engineering at Purdue University. She was also a visiting professor of Medical School at UC Davis, USA (2018); School of Industrial Engineering at Purdue University, USA (2015); Department of Electrical Engineering and Computer Science at U.C. Berkeley, USA (2012); and Department of Industrial Engineering and Management Science at Northwestern University, USA (1997).

   Professor Song's research interests are quality management, stochastic simulation, big data analysis, and reliability for semiconductor manufacturing systems. She has published many papers in prestigious journals such as Management Science, Operations Research, IEEE Transactions on Automatic Control, IIE Transactions, and European Journal of the Operational Research.

   Professor Song is currently an area editor of Journal of Simulation Modeling Practice and Theory. She is on the editorial board of European Journal of Industrial Engineering, and IASTED International Conference on Modeling, Identification and Control. Professional activities also include having served as the referee of Operations Research, Management Science, European Journal of Operational Research, IEEE Transactions of Reliability, Operations Research on Computing, and IEEE Transactions on Automatic Control.

Professor Song has more than 20 years consulting experience in industry, including Taiwan Semiconductor Manufacturing Company (TSMC), PowerTech Technology Inc., Industrial Technology Institute, Institute of Information Industry, and Chinese Telecommunication Laboratories. She has served as a quality control and reliability consult for Sino-American Silicon Product Inc. since 2012.

   Professor Song awards include the 1996 Distinguish Research Award from the National Science Council of the Republic of China, the 1995 and 2013 Best Paper Awards for the Journal of Chinese Industrial Engineering, the 1993 National Tsing Hua University outstanding teaching award. As a graduate student she received the 1990 IIE Doctoral Dissertation Award and the 1988 Omega Rho Student Paper Award. Professor Song led Tsing Hua University student groups that were recognized with the 2016 "Think Big" university-wide reading-club award, the 2017 "Poetry in Math, and Math in Poetry" university-wide reading-club award, and the 2017 TSMC big-data-analysis award.
 

"Perspectives on Academia/Industry Collaborations in Data-Analysis Education"

Abstract: As a university professor and industry consultant for more than 20 years, I have experienced first-hand the gap between what industry needs in terms of data analysis and what universities offer in data-analysis education. Too often, industry is trying to find solutions to problems while academia is looking for problems to its solutions. Put another way, industry is focused on product development while academia focuses on fundamental science or basic research.

   To close this gap, the author proposes a comprehensive collaboration between academic programs and industry education on the data-analysis issue. Specifically, the author suggests the ``begin with the end" principle to inform design of academic data-analysis programs. Such a collaboration will enhance the visibility of the university to industry and meet industry's education and training goals.

 

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