Capacity Allocation in Flexible Production Networks: Theory and Applications

Guodong Lyu (), Wang-Chi Cheung (), Mabel C. Chou (), Chung-Piaw Teo (), Zhichao Zheng () and Yuanguang Zhong ()
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Guodong Lyu: Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, Changsha, 410073 Hunan, China, Department of Analytics and Operations, NUS Business School, National University of Singapore, SG 119245, Singapore
Wang-Chi Cheung: Department of Industrial Systems Engineering and Management, NUS Engineering, National University of Singapore, SG 117576, Singapore
Mabel C. Chou: Department of Analytics and Operations, NUS Business School, National University of Singapore, SG 119245, Singapore
Chung-Piaw Teo: Department of Analytics and Operations, NUS Business School, National University of Singapore, SG 119245, Singapore, Institute of Operations Research and Analytics, National University of Singapore, SG 117602, Singapore
Zhichao Zheng: Lee Kong Chian School of Business, Singapore Management University, SG 178899, Singapore
Yuanguang Zhong: School of Business Administration, South China University of Technology, Guangzhou, 510640 Guangdong, China

Management Science, 2019, vol. 65, issue 11, 5091-5109

Abstract: In many production environments, a fixed network of capacity is shared flexibly between multiple products with random demands. What is the best way to configure the capacity of the production network and to allocate the available capacity to meet predetermined fill rate requirements? We develop a new approach for network capacity configuration and allocation and characterize the relationship between the capacity of the network and the attainable fill rate levels for the products, taking into account the flexibility structure of the network. This builds on a new randomized allocation mechanism to deliver the desired services. We use this theory to investigate the connection between the flexibility structure and capacity configuration. We provide a new perspective to the well-known phenomenon that “long chain is almost as good as the fully flexible network”: for given target fill rates, the required capacity level in a long-chain network is close to that in a fully flexible network and is much lower than a dedicated system. We apply these insights and techniques on problems arising in the design of last-mile delivery operations and in semiconductor production planning, using real data from two companies.

Keywords: production networks; capacity configuration; process flexibility; fill rate targets (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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