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Manufacturing network configuration in supply chains with product recovery

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  • Francas, David
  • Minner, Stefan

Abstract

Efficient implementation of product recovery requires appropriate network structures. In this paper, we study the network design problem of a firm that manufactures new products and remanufactures returned products in its facilities. We examine the capacity decisions and expected performance of two alternative manufacturing network configurations when demand and return flows are both uncertain. Concerning the market structure, we further distinguish between the case where newly manufactured and remanufactured products are sold on the same market and the case where recovered products have to be sold on a secondary market. We consider network structures where manufacturing and remanufacturing are both conducted in common plants as well as structures that pool all remanufacturing activities in a separate plant. The underlying decision problems are formulated as two-stage stochastic programs with recourse. Based on numerical studies with normally distributed demands and returns, we show that particularly network size, investment costs of (re-)manufacturing capacity, and market structure have a strong impact on the choice of a network configuration. Concerning the general role of manufacturing configuration in a system with product recovery, our results indicate that the investigated structures can lead to very different expected profits. We also examine the sensitivity of network performance to changes in return volumes, return variability and correlation between return and demand. Based on these results, we find that integrated plants are more beneficial in the common market setting. This relative advantage tends to diminish when demand is segmented, thus investing in more specialized, dedicated resources should be considered.

Suggested Citation

  • Francas, David & Minner, Stefan, 2009. "Manufacturing network configuration in supply chains with product recovery," Omega, Elsevier, vol. 37(4), pages 757-769, August.
  • Handle: RePEc:eee:jomega:v:37:y:2009:i:4:p:757-769
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    References listed on IDEAS

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    Cited by:

    1. Georgiadis, Patroklos & Athanasiou, Efstratios, 2013. "Flexible long-term capacity planning in closed-loop supply chains with remanufacturing," European Journal of Operational Research, Elsevier, vol. 225(1), pages 44-58.
    2. Li, Kate J. & Xu, Susan H., 2015. "The comparison between trade-in and leasing of a product with technology innovations," Omega, Elsevier, vol. 54(C), pages 134-146.
    3. Hamed Soleimani & Mirmehdi Seyyed-Esfahani & Mohsen Akbarpour Shirazi, 2016. "A new multi-criteria scenario-based solution approach for stochastic forward/reverse supply chain network design," Annals of Operations Research, Springer, vol. 242(2), pages 399-421, July.
    4. Koh, S.C.L. & Gunasekaran, A. & Tseng, C.S., 2012. "Cross-tier ripple and indirect effects of directives WEEE and RoHS on greening a supply chain," International Journal of Production Economics, Elsevier, vol. 140(1), pages 305-317.
    5. Amini, Mehdi & Li, Haitao, 2011. "Supply chain configuration for diffusion of new products: An integrated optimization approach," Omega, Elsevier, vol. 39(3), pages 313-322, June.
    6. Georgiadis, Michael C. & Tsiakis, Panagiotis & Longinidis, Pantelis & Sofioglou, Maria K., 2011. "Optimal design of supply chain networks under uncertain transient demand variations," Omega, Elsevier, vol. 39(3), pages 254-272, June.
    7. Schulz, Tobias & Voigt, Guido, 2014. "A flexibly structured lot sizing heuristic for a static remanufacturing system," Omega, Elsevier, vol. 44(C), pages 21-31.
    8. Nasir, Mohammed Haneef Abdul & Genovese, Andrea & Acquaye, Adolf A. & Koh, S.C.L. & Yamoah, Fred, 2017. "Comparing linear and circular supply chains: A case study from the construction industry," International Journal of Production Economics, Elsevier, vol. 183(PB), pages 443-457.
    9. Chang Liu & Ying Ji & Xinqi Li, 2023. "Closed-Loop Supply Chain Network Design with Flexible Capacity under Uncertain Environment," Sustainability, MDPI, vol. 15(19), pages 1-38, October.
    10. Govindan, Kannan & Soleimani, Hamed & Kannan, Devika, 2015. "Reverse logistics and closed-loop supply chain: A comprehensive review to explore the future," European Journal of Operational Research, Elsevier, vol. 240(3), pages 603-626.
    11. Marta Pérez-Pérez & Canan Kocabasoglu-Hillmer & Ana María Serrano-Bedia & María Concepción López-Fernández, 2019. "Manufacturing and Supply Chain Flexibility: Building an Integrative Conceptual Model Through Systematic Literature Review and Bibliometric Analysis," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 20(1), pages 1-23, December.
    12. Nakatani, Jun & Konno, Kiyoto & Moriguchi, Yuichi, 2017. "Variability-based optimal design for robust plastic recycling systems," Resources, Conservation & Recycling, Elsevier, vol. 116(C), pages 53-60.
    13. Hong, Zhaofu & Dai, Wei & Luh, Hsing & Yang, Chenchen, 2018. "Optimal configuration of a green product supply chain with guaranteed service time and emission constraints," European Journal of Operational Research, Elsevier, vol. 266(2), pages 663-677.
    14. Gaur, Jighyasu & Amini, Mehdi & Rao, A.K., 2017. "Closed-loop supply chain configuration for new and reconditioned products: An integrated optimization model," Omega, Elsevier, vol. 66(PB), pages 212-223.
    15. Bag, Surajit & Yadav, Gunjan & Wood, Lincoln C. & Dhamija, Pavitra & Joshi, Sudhanshu, 2020. "Industry 4.0 and the circular economy: Resource melioration in logistics," Resources Policy, Elsevier, vol. 68(C).
    16. Assid, M. & Gharbi, A. & Hajji, A., 2020. "Production control of failure-prone manufacturing-remanufacturing systems using mixed dedicated and shared facilities," International Journal of Production Economics, Elsevier, vol. 224(C).
    17. Marta Mańkowska & Izabela Kotowska & Michał Pluciński, 2020. "Seaports as Nodal Points of Circular Supply Chains: Opportunities and Challenges for Secondary Ports," Sustainability, MDPI, vol. 12(9), pages 1-21, May.
    18. Genovese, Andrea & Acquaye, Adolf A. & Figueroa, Alejandro & Koh, S.C. Lenny, 2017. "Sustainable supply chain management and the transition towards a circular economy: Evidence and some applications," Omega, Elsevier, vol. 66(PB), pages 344-357.
    19. Hua, Zhongsheng & Zhang, Xuemei & Xu, Xiaoyan, 2011. "Product design strategies in a manufacturer-retailer distribution channel," Omega, Elsevier, vol. 39(1), pages 23-32, January.
    20. Barker, Theresa J. & Zabinsky, Zelda B., 2011. "A multicriteria decision making model for reverse logistics using analytical hierarchy process," Omega, Elsevier, vol. 39(5), pages 558-573, October.
    21. J. Prince Vijai, 2021. "Production network, technology choice, capacity investment and inventory sourcing decisions: operational hedging under demand uncertainty," OPSEARCH, Springer;Operational Research Society of India, vol. 58(4), pages 1164-1191, December.
    22. Lin, Yi-Kuei & Chang, Ping-Chen, 2012. "Evaluate the system reliability for a manufacturing network with reworking actions," Reliability Engineering and System Safety, Elsevier, vol. 106(C), pages 127-137.
    23. Ruiz-Benítez, Rocío & Ketzenberg, Michael & van der Laan, Erwin A., 2014. "Managing consumer returns in high clockspeed industries," Omega, Elsevier, vol. 43(C), pages 54-63.
    24. Agrawal, Saurabh & Singh, Rajesh K. & Murtaza, Qasim, 2015. "A literature review and perspectives in reverse logistics," Resources, Conservation & Recycling, Elsevier, vol. 97(C), pages 76-92.
    25. Wu, Kuo-Jui & Liao, Ching-Jong & Tseng, Ming-Lang & Chiu, Anthony S.F., 2015. "Exploring decisive factors in green supply chain practices under uncertainty," International Journal of Production Economics, Elsevier, vol. 159(C), pages 147-157.

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