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Capacity Allocation in Flexible Production Networks: Theory and Applications

Author

Listed:
  • 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)

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.

Suggested Citation

  • Guodong Lyu & Wang-Chi Cheung & Mabel C. Chou & Chung-Piaw Teo & Zhichao Zheng & Yuanguang Zhong, 2019. "Capacity Allocation in Flexible Production Networks: Theory and Applications," Management Science, INFORMS, vol. 65(11), pages 5091-5109, November.
  • Handle: RePEc:inm:ormnsc:v:65:y:2019:i:11:p:5091-5109
    DOI: 10.1287/mnsc.2018.3169
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    References listed on IDEAS

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    1. Mabel C. Chou & Geoffrey A. Chua & Chung-Piaw Teo & Huan Zheng, 2011. "Process Flexibility Revisited: The Graph Expander and Its Applications," Operations Research, INFORMS, vol. 59(5), pages 1090-1105, October.
    2. Antoine Désir & Vineet Goyal & Yehua Wei & Jiawei Zhang, 2016. "Sparse Process Flexibility Designs: Is the Long Chain Really Optimal?," Operations Research, INFORMS, vol. 64(2), pages 416-431, April.
    3. Fernando F. Suarez & Michael A. Cusumano & Charles H. Fine, 1996. "An Empirical Study of Manufacturing Flexibility in Printed Circuit Board Assembly," Operations Research, INFORMS, vol. 44(1), pages 223-240, February.
    4. Xuan Wang & Jiawei Zhang, 2015. "Process Flexibility: A Distribution-Free Bound on the Performance of k -Chain," Operations Research, INFORMS, vol. 63(3), pages 555-571, June.
    5. William C. Jordan & Stephen C. Graves, 1995. "Principles on the Benefits of Manufacturing Process Flexibility," Management Science, INFORMS, vol. 41(4), pages 577-594, April.
    6. Aydin Alptekinoglu & Arunava Banerjee & Anand Paul & Nikhil Jain, 2013. "Inventory Pooling to Deliver Differentiated Service," Manufacturing & Service Operations Management, INFORMS, vol. 15(1), pages 33-44, September.
    7. Yuanguang Zhong & Zhichao Zheng & Mabel C. Chou & Chung-Piaw Teo, 2018. "Resource Pooling and Allocation Policies to Deliver Differentiated Service," Management Science, INFORMS, vol. 64(4), pages 1555-1573, April.
    8. Hallgren, Mattias & Olhager, Jan, 2009. "Flexibility configurations: Empirical analysis of volume and product mix flexibility," Omega, Elsevier, vol. 37(4), pages 746-756, August.
    9. Mabel C. Chou & Geoffrey A. Chua & Huan Zheng, 2014. "On the Performance of Sparse Process Structures in Partial Postponement Production Systems," Operations Research, INFORMS, vol. 62(2), pages 348-365, April.
    10. David Simchi-Levi & Yehua Wei, 2012. "Understanding the Performance of the Long Chain and Sparse Designs in Process Flexibility," Operations Research, INFORMS, vol. 60(5), pages 1125-1141, October.
    11. Mabel C. Chou & Geoffrey A. Chua & Chung-Piaw Teo & Huan Zheng, 2010. "Design for Process Flexibility: Efficiency of the Long Chain and Sparse Structure," Operations Research, INFORMS, vol. 58(1), pages 43-58, February.
    12. Xi Chen & Jiawei Zhang & Yuan Zhou, 2015. "Optimal Sparse Designs for Process Flexibility via Probabilistic Expanders," Operations Research, INFORMS, vol. 63(5), pages 1159-1176, October.
    13. David Simchi-Levi & Yehua Wei, 2015. "Worst-Case Analysis of Process Flexibility Designs," Operations Research, INFORMS, vol. 63(1), pages 166-185, February.
    14. Manu Goyal & Serguei Netessine, 2011. "Volume Flexibility, Product Flexibility, or Both: The Role of Demand Correlation and Product Substitution," Manufacturing & Service Operations Management, INFORMS, vol. 13(2), pages 180-193, March.
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    8. Liu, Kanglin & Liu, Changchun & Xiang, Xi & Tian, Zhili, 2023. "Testing facility location and dynamic capacity planning for pandemics with demand uncertainty," European Journal of Operational Research, Elsevier, vol. 304(1), pages 150-168.

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