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Flexible long-term capacity planning in closed-loop supply chains with remanufacturing

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  • Georgiadis, Patroklos
  • Athanasiou, Efstratios

Abstract

We deal with long-term demand-driven capacity planning policies in the reverse channel of closed-loop supply chains (CLSCs) with remanufacturing, under high capacity acquisition cost coupled with uncertainty in actual demand, sales patterns, quality and timing of end-of-use product returns. The objective is to facilitate the decision-making when the management faces the dilemma of implementing either a strategy of early large-scale investments to benefit from economies of scale and capacity readiness, or a flexible strategy of low volume but more frequent capacity expansions. We consider a CLSC with two sequential product-types. We study the system’s response in terms of transient flows, actual/desired capacity level, capacity expansions/contractions and total supply chain profit, employing a simulation-based system dynamics optimization approach. Extensive numerical investigation covers a broad range of real-world remanufacturable products under alternative scenarios in relation to the market preference over product-types. The key findings propose flexible policies as improved alternatives to large-scale capacity expansions/contractions in terms of adaptability to the actual pattern of end-of-use product returns and involved risk in the investments’ turnover. Flexible policies are also proposed as practices to avoid overcapacity phenomena in collection and remanufacturing capacity and as robust policies to product demand. Their implementation is revealed to be even more important for the case of remanufacturing, when a high capacity acquisition unit-cost ratio (remanufacturing/collection) is coupled with strong economies of scale. Finally, results under different information sharing structures show changes in remanufacturing policies, thus justifying the importance of coordination between the decision-maker and the distributor.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:ejores:v:225:y:2013:i:1:p:44-58
    DOI: 10.1016/j.ejor.2012.09.021
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    1. Wang, Qifei & Li, Jianbin & Yan, Hong & Zhu, Stuart X., 2016. "Optimal remanufacturing strategies in name-your-own-price auctions with limited capacity," International Journal of Production Economics, Elsevier, vol. 181(PA), pages 113-129.
    2. He, Yuanjie, 2015. "Acquisition pricing and remanufacturing decisions in a closed-loop supply chain," International Journal of Production Economics, Elsevier, vol. 163(C), pages 48-60.
    3. He, Yuanjie, 2017. "Supply risk sharing in a closed-loop supply chain," International Journal of Production Economics, Elsevier, vol. 183(PA), pages 39-52.
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    5. Sudarto, Sumarsono & Takahashi, Katsuhiko & Morikawa, Katsumi, 2017. "Efficient flexible long-term capacity planning for optimal sustainability dimensions performance of reverse logistics social responsibility: A system dynamics approach," International Journal of Production Economics, Elsevier, vol. 184(C), pages 179-192.
    6. Muris Lage Junior & Moacir Godinho Filho, 2017. "Master disassembly scheduling in a remanufacturing system with stochastic routings," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 25(1), pages 123-138, March.
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    8. Yu-Chung Tsao & Vu-Thuy Linh & Jye-Chyi Lu & Vincent Yu, 0. "A supply chain network with product remanufacturing and carbon emission considerations: a two-phase design," Journal of Intelligent Manufacturing, Springer, vol. 0, pages 1-13.
    9. Xuejie Bai & Yankui Liu, 2016. "Robust optimization of supply chain network design in fuzzy decision system," Journal of Intelligent Manufacturing, Springer, vol. 27(6), pages 1131-1149, December.
    10. repec:gam:jsusta:v:9:y:2017:i:9:p:1503-:d:109643 is not listed on IDEAS
    11. Ondemir, Onder & Gupta, Surendra M., 2014. "A multi-criteria decision making model for advanced repair-to-order and disassembly-to-order system," European Journal of Operational Research, Elsevier, vol. 233(2), pages 408-419.
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    15. Federico Cosenz & Guido Noto, 2016. "Applying System Dynamics Modelling to Strategic Management: A Literature Review," Systems Research and Behavioral Science, Wiley Blackwell, vol. 33(6), pages 703-741, November.
    16. repec:eee:proeco:v:190:y:2017:i:c:p:45-59 is not listed on IDEAS
    17. Wang, Kung-Jeng & Nguyen, Phuc Hong, 2017. "Capacity planning with technology replacement by stochastic dynamic programming," European Journal of Operational Research, Elsevier, vol. 260(2), pages 739-750.
    18. Yan, Wei & Xiong, Yu & Xiong, Zhongkai & Guo, Nian, 2015. "Bricks vs. clicks: Which is better for marketing remanufactured products?," European Journal of Operational Research, Elsevier, vol. 242(2), pages 434-444.
    19. Rajesh, R., 2017. "Technological capabilities and supply chain resilience of firms: A relational analysis using Total Interpretive Structural Modeling (TISM)," Technological Forecasting and Social Change, Elsevier, vol. 118(C), pages 161-169.
    20. Zhen-Zheng Zhang & Zong-Jun Wang & Li-Wen Liu, 2015. "Retail Services and Pricing Decisions in a Closed-Loop Supply Chain with Remanufacturing," Sustainability, MDPI, Open Access Journal, vol. 7(3), pages 1-24, February.

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