Decomposition Methods for Manufacturing System Scheduling: A Survey

Fajun Yang; Kaizhou Gao; Simon Ian Ware; Yuting Zhu; Rong Su

doi:10.1109/JAS.2017.7510805

Volume 5 Issue 2

Mar. 2018

IEEE/CAA Journal of Automatica Sinica

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Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2018 > 5(2): 389-400

Fajun Yang, Kaizhou Gao, Simon Ian Ware, Yuting Zhu and Rong Su, "Decomposition Methods for Manufacturing System Scheduling: A Survey," IEEE/CAA J. Autom. Sinica, vol. 5, no. 2, pp. 389-400, Feb. 2018. doi: 10.1109/JAS.2017.7510805

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Fajun Yang, Kaizhou Gao, Simon Ian Ware, Yuting Zhu and Rong Su, "Decomposition Methods for Manufacturing System Scheduling: A Survey," IEEE/CAA J. Autom. Sinica, vol. 5, no. 2, pp. 389-400, Feb. 2018. doi: 10.1109/JAS.2017.7510805

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Decomposition Methods for Manufacturing System Scheduling: A Survey

doi: 10.1109/JAS.2017.7510805

School of Electrical and Electronic Engineering at Nanyang Technological University, Singapore 639798, Singapore

Funds: This work was conducted within the Delta-NTU Corporate Lab for Cyber-Physical Systems with funding support from Delta Electronics Inc and the National Research Foundation (NRF) Singapore under the Corp Lab@University Scheme

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Author Bio:
Fajun Yang received the B.S.degree in industrial engineering from Hunan University of Science and Technology, Hunan, China, in 2011, the Ph.D.degree in mechanical engineering from Guangdong University of Technology, China, in 2016.From 2015-2016, he was a Visiting Student with New Jersey Institute of Technology, Newark, NJ, USA. He is currently a Research Fellow with Nanyang Technological University, Singapore.He has 10+ international journal papers (majority in the IEEE Transactions).His research interests include Petri nets, production planning, discrete event systems, scheduling and control.He has served as a reviewer for a number of journals. (e-mail: fjyang@ntu.edu.sg)

Kaizhou Gao received the B.Sc.and master degrees from China in 2005 and 2008, respectively, and the Ph.D.degree from Nanyang Technological University, Singapore, 2016.From 2008 to 2012, he was with the School of Computer, Liaocheng University, China.He was a Research Associate in the School of Electronic and Electrical Engineering (EEE), NTU, Singapore, from Feb.2012 to Sep.2013.From Oct. 2013 to Mar.2015, he was a software engineer in Singapore Institute of Manufacturing Technology (SIMTech), A^*star, Singapore.Since Apr.2015, he was a Research Fellow in the School of Electronic and Electrical Engineering, NTU, Singapore.His research interests include intelligent computation, optimization, scheduling, and intelligent transportation.He has published over 50 refereed papers. (e-mail: kzgao@ntu.edu.sg)

Ian Ware Simon received the B.S.degree in software development from Waikato University, New Zealand, in 2007, the Ph.D.degree in computer science from Waikato University in 2014.He is currently a Research Fellow with Nanyang Technological University, Singapore.His research interests include discrete event systems, optimization, scheduling, and control.He has served as a reviewer for a number of journals. (e-mail: sware@ntu.edu.sg)

Yuting Zhu received the B.S.degree from Southeast University, Jiangsu, China, in 2016.Currently, she is a Ph.D.candidate at Nanyang Technological University, Singapore.Her research interests include discrete event systems, and supervisory control. (e-mail: yuting002@e.ntu.edu.sg)

Rong Su (M'11-SM'14) received the B.E.degree in automatic control from University of Science and Technology of China, Hefei, China, in 1997, and the M.A.Sc.and Ph.D.degrees both in electrical engineering from the University of Toronto, Toronto, ON, Canada, in 2000 and 2004, respectively.Since then he was affiliated with University of Waterloo and Technical University of Eindhoven before he joined Nanyang Technological University, Singapore, in 2010.His research interests include discrete event systems, supervisory control, modelbased fault diagnosis, multiagent systems, optimization and scheduling with applications in green buildings, flexible manufacturing, power management, and intelligent transportation systems.In the aforementioned areas, he has more than 130 publications in journals, book chapters, and conference proceedings, and two patents.Dr.Su is an Associate Editor of Automatica, Journal of Discrete Event Dynamic Systems:Theory and Applications, Journal of Control and Decision, and Transactions of the Institute of Measurement and Control.He is also the Chair of IEEE Control Systems Society Technical Committee on Smart Cities. (e-mail: rsu@ntu.edu.sg)
Corresponding author: Yuting Zhu, e-mail: yuting002@e.ntu.edu.sg
Received Date: 2017-07-01
Accepted Date: 2017-11-09

Abstract

Abstract

Manufacturing is the application of labor, tools, machines, chemical and biological processing, to an original raw material by changing its physical and geometrical characteristics, in order to make finished products. Since the first industrial revolution, to accommodate the large-scale production, tremendous changes have happened to manufacturing through the innovations of technology, organization, management, transportation and communication. This work first reviews the high-volume low-mix process by focusing on the quantity production, transfer line and single model assembly line. Then, it reviews the high-volume high-mix process. For such a process type, mixed/multi model assembly line is usually adopted. Hence, two main decisions on them, i.e., balancing and, sequencing are reviewed. Thereafter, it discusses the low-volume high-mix process in detail. Then, technology gap and future work is discussed, and at last, conclusions are given.
- Assembly line,
- high-mix,
- high-volume,
- low-mix,
- low-volume,
- manufacturing processes

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References(103)

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Decomposition Methods for Manufacturing System Scheduling: A Survey

doi: 10.1109/JAS.2017.7510805

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