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Supply-Chain Management for Recoverable Manufacturing Systems


  • V. Daniel R. Guide

    (A. J. Palumbo School of Business Administration, 920 Rockwell Hall, Duquesne University, Pittsburgh, Pennsylvania 15282)

  • Vaidyanathan Jayaraman

    (Department of Management and Systems, Washington State University, Vancouver, Washington 98686)

  • Rajesh Srivastava

    (Department of Graduate Logistics Management, Graduate School of Logistics and Acquisition Management, Air Force Institute of Technology WPAFB, Ohio 45433-7765)

  • W. C. Benton

    (Department of Management Science, Fisher College of Business, Ohio State University, Columbus, Ohio 43210-1399)


Recoverable manufacturing systems minimize the environmental impact of industry by reusing materials, reducing energy use, and reducing the need to landfill industrial products. These systems are widespread in the United States and are profitable, in addition to contributing to sustainable development. However, the management of supply-chain activities can differ greatly from management activities in traditional manufacturing supply chains. Seven complicating characteristics increase uncertainty. Managers must take actions to reduce uncertainty in the timing and quantity of returns, balance return rates with demand rates, and make material recovery more predictable. Managers must also plan for the collection of products from end-users. The use of information systems with new production-planning and control techniques makes management of these activities more predictable.

Suggested Citation

  • V. Daniel R. Guide & Vaidyanathan Jayaraman & Rajesh Srivastava & W. C. Benton, 2000. "Supply-Chain Management for Recoverable Manufacturing Systems," Interfaces, INFORMS, vol. 30(3), pages 125-142, June.
  • Handle: RePEc:inm:orinte:v:30:y:2000:i:3:p:125-142
    DOI: 10.1287/inte.

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    References listed on IDEAS

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    Cited by:

    1. Renzheng Xue & Fengbin Zhang & Feng Tian, 2018. "A System Dynamics Model to Evaluate Effects of Retailer-Led Recycling Based on Dual Chains Competition: A Case of e-Waste in China," Sustainability, MDPI, Open Access Journal, vol. 10(10), pages 1-18, September.
    2. Dormady, Noah & Roa-Henriquez, Alfredo & Rose, Adam, 2019. "Economic resilience of the firm: A production theory approach," International Journal of Production Economics, Elsevier, vol. 208(C), pages 446-460.
    3. Byung Duk Song & Young Dae Ko, 2017. "Effect of Inspection Policies and Residual Value of Collected Used Products: A Mathematical Model and Genetic Algorithm for a Closed-Loop Green Manufacturing System," Sustainability, MDPI, Open Access Journal, vol. 9(9), pages 1-14, September.
    4. Chen, Daqiang & Ignatius, Joshua & Sun, Danzhi & Zhan, Shalei & Zhou, Chenyu & Marra, Marianna & Demirbag, Mehmet, 2019. "Reverse logistics pricing strategy for a green supply chain: A view of customers' environmental awareness," International Journal of Production Economics, Elsevier, vol. 217(C), pages 197-210.
    5. Forlin, Valeria & Scholz, Eva-Maria, 2020. "Strategic take-back programs when consumers have heterogeneous environmental preferences," Resource and Energy Economics, Elsevier, vol. 60(C).
    6. Jie Xu & Nan Liu, 2017. "Research on closed loop supply chain with reference price effect," Journal of Intelligent Manufacturing, Springer, vol. 28(1), pages 51-64, January.
    7. Paul Rowe & Burak Eksioglu & Sandra Eksioglu, 2017. "Recycling procurement strategies with variable yield suppliers," Annals of Operations Research, Springer, vol. 249(1), pages 215-234, February.
    8. Chang Fang & Xinbao Liu & Jun Pei & Wenjuan Fan & Panos M. Pardalos, 2016. "Optimal production planning in a hybrid manufacturing and recovering system based on the internet of things with closed loop supply chains," Operational Research, Springer, vol. 16(3), pages 543-577, October.
    9. Eleonora Bottani & Maria Carmen Gentilotti & Marta Rinaldi, 2017. "A Fuzzy Logic-Based Tool for the Assessment of Corporate Sustainability: A Case Study in the Food Machinery Industry," Sustainability, MDPI, Open Access Journal, vol. 9(4), pages 1-29, April.
    10. Hiroko Nakamura & Shinji Suzuki & Tomobe Hironori & Yuya Kajikawa & Ichiro Sakata, 2011. "Citation lag analysis in supply chain research," Scientometrics, Springer;Akadémiai Kiadó, vol. 87(2), pages 221-232, May.
    11. Anil Jindal & Kuldip Singh Sangwan, 2017. "Multi-objective fuzzy mathematical modelling of closed-loop supply chain considering economical and environmental factors," Annals of Operations Research, Springer, vol. 257(1), pages 95-120, October.
    12. Hsien-Jen Lin, 2015. "Two-echelon stochastic inventory system with returns and partial backlogging," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(6), pages 966-975, April.
    13. Chang, Jiyoun C. & Graves, Stephen C. & Kirchain, Randolph E. & Olivetti, Elsa A., 2019. "Integrated planning for design and production in two-stage recycling operations," European Journal of Operational Research, Elsevier, vol. 273(2), pages 535-547.
    14. Jian Yang & Boaz Golany & Gang Yu, 2005. "A concave‐cost production planning problem with remanufacturing options," Naval Research Logistics (NRL), John Wiley & Sons, vol. 52(5), pages 443-458, August.
    15. Ponte, Borja & Naim, Mohamed M. & Syntetos, Aris A., 2019. "The value of regulating returns for enhancing the dynamic behaviour of hybrid manufacturing-remanufacturing systems," European Journal of Operational Research, Elsevier, vol. 278(2), pages 629-645.


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