Skip to main content

Advertisement

SpringerLink
Log in

Sustainable Management of Remanufacturing in Dynamic Supply Chains

  • Published:
Networks and Spatial Economics Aims and scope Submit manuscript

Abstract

Closed-loop production systems encompass all processes for returning, remanufacturing, recycling, discarding, and repackaging products. These elements form the core of sustainable manufacturing by managing what otherwise would be waste to enable reuse and by controlling its associated pollution. This paper presents the general management model of sustainable remanufacturing within a dynamic closed-loop supply chain. Our specification encompasses agents positioned at key stages in the supply chain, e.g., manufacturers, retailers, and customers, and considers both profitability and environmental performance of their decentralized decisions. We cast the problem to allow for interdependence of agents through a Nash game. These salient features simultaneously render the mathematical model more realistic and computationally challenging. To proceed, our model is formalized by using variational inequalities, which in turn are converted to a fixed point problem that we solve using a computationally tractable algorithm. Decision rules for strategic remanufacturing and recycling are provided to complement the numerical solution in an illustrative example.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Notes

  1. For example, 80% of customers change their perfectly working cell phones within one year; there are billions of returned products annually in the United States (Guide and Wassenhove 2009).

  2. Generalization to a multi-product setting simply adds dimensionality and computational intensity.

  3. In reality, there are some exceptions where manufacturers sell their products directly to customers. (For example, Dell’s direct PC sales to end customers.) However, the vast majority of sales to customers are from retailers.

  4. The environmental coefficient can be adapted to reflect real cases. For example, it can be the amount of carbon dioxide emission per unit production for which a pollution tax can be imposed.

References

  • Browder FE (1968) The fixed point theory of multi-valued mappings in topological vector spaces. Math Ann 177:283–301

    Google Scholar 

  • Chen J-M, Chang C-I (2013) Dynamic pricing for new and remanufactured products in a closed-loop supply chain. Int J Prod Econ 146(1):153–160

    Google Scholar 

  • Chung SH, Weaver RD, Friesz TL (2012) Oligopolies in pollution permit markets: a dynamic game approach. Int J Prod Econ 140(1):48–56

    Google Scholar 

  • Chung SH, Weaver RD, Friesz TL (2013) Strategic response to pollution taxes in supply chain networks: dynamic, spatial, and organizational dimensions. Eur J Oper Res 231(2):314–327

    Google Scholar 

  • Chung SH, Weaver RD, Friesz TL (2014) Dynamic sustainability games for renewable resources - a computational approach. IEEE Trans Comput 63(1):155–166

    Google Scholar 

  • Dowlatshahi S (2000) Developing a theory of r everse logistics. Interfaces 30 (3):143–155

    Google Scholar 

  • Esenduran G, Kemahlıoğlu-Ziya E, Swaminathan JM (2017) Impact of take-back regulation on the remanufacturing industry. Prod Oper Manag 26 (5):924–944

    Google Scholar 

  • Fattahi M, Govindan K (2017) Integrated forward/reverse logistics network design under uncertainty with pricing for collection of used products. Ann Oper Res 253(1):193–225

    Google Scholar 

  • Feng Y, Gallego G (2000) Perishable asset revenue management with Markovian time dependent demand intensities. Manag Sci 46(7):941–956

    Google Scholar 

  • Finster M, Eagan P, Hussey D (2001) Linking industrial ecology with business strategy: creating value for green product design. J Ind Ecol 5(3):107–125

    Google Scholar 

  • Florida R (1996) Lean and green: the move to environmentally conscious manufacturing. Calif Manage Rev 39(1):80–105

    Google Scholar 

  • Friesz TL (2010) Dynamic optimization and differential games. Springer

  • Friesz TL, Mookherjee R (2006) Solving the dynamic network user equilibrium with state-dependent time shifts. Transp Res B 40(3):207–229

    Google Scholar 

  • Friesz TL, Mookherjee R, Rigdon M (2005) An evolutionary game-theoretic model of network revenue management in oligopolistic competition. J Revenue Pric Manag 4(2):156–173

    Google Scholar 

  • Friesz TL, Kim T, Kwon C, Rigdon M (2010) Approximate network loading and dual-time-scale dynamic user equilibrium. Transp Res B 45(1):176–207

    Google Scholar 

  • Geyer R, Wassenhove LV (2007) The impact of limited component durability and finite life cycles on remanufacturing profit. Manag Sci 53(1):88–100

    Google Scholar 

  • Guide VDR, van Wassenhove LN (eds) (2003) Business aspects of closed-loop supply chains. Carnegie Mellon University Press, Posner Hall, Suite 341, Carnegie Mellon University Pittsburgh, PA 15213-3890 USA

  • Guide VDR, Wassenhove LNV (2009) The evolution of closed-loop supply chain research. Oper Res 57(1):10–18

    Google Scholar 

  • Hammond D, Beullens P (2007) Closed-loop supply chain network equilibrium under legislation. Eur J Oper Res 183(2):895–908

    Google Scholar 

  • Han K, Eve G, Friesz T.L (2019) Computing dynamic user equilibria on large-scale networks with software implementation. Networks and Spatial Economics, 1–34

  • He X, Huang N.-j., Li X.-s. (2019) Modified projection methods for solving multivalued variational inequality without monotonicity. Networks and Spatial Economics, 1–17

  • Inderfurth K, de Kok AG, Flapper SDP (2001) Product recovery in stochastic remanufacturing systems with multiple reuse options. Eur J Oper Res 133(1):130–152

    Google Scholar 

  • Jeihoonian M, Zanjani MK, Gendreau M (2017) Closed-loop supply chain network design under uncertain quality status: case of durable products. Int J Prod Econ 183:470–486

    Google Scholar 

  • Jeon HW, Taisch M, Prabhu V (2016) Measuring variability on electrical power demands in manufacturing operations. J Clean Prod 137:1628–1646

    Google Scholar 

  • Jeon HW, Lee S, Wang C (2019) Estimating manufacturing electricity costs by simulating dependence between production parameters. Robot Comput Integr Manuf 55:129–140

    Google Scholar 

  • Jung C, Krutilla K, Boyd R (1996) Incentives for advanced pollution abatement technology at the industry level: an evaluation of policy alternatives. J Environ Econ Manag 30(1):95–111

    Google Scholar 

  • Kadambala DK, Subramanian N, Tiwari MK, Abdulrahman M, Liu C (2017) Closed loop supply chain networks: designs for energy and time value efficiency. Int J Prod Econ 183:382–393

    Google Scholar 

  • Kenne J-P, Dejax P, Gharbi A (2012) Production planning of a hybrid manufacturing–remanufacturing system under uncertainty within a closed-loop supply chain. Int J Prod Econ 135(1):81–93

    Google Scholar 

  • Kiesmüller GP, Scherer CW (2003) Computational issues in a stochastic finite horizon one product recovery inventory model. Eur J Oper Res 146(3):553–579

    Google Scholar 

  • Kovach JJ, Atasu A, Banerjee S (2018) Salesforce incentives and remanufacturing. Prod Oper Manag 27(3):516–530

    Google Scholar 

  • Kwon C, Friesz TL, Mookherjee R, Yao T, Feng B (2009) Non-cooperative competition among revenue maximizing service providers with demand learning. Eur J Oper Res 197(3):981–996

    Google Scholar 

  • Mangun D, Thurston DL (2002) Incorporating component reuse, remanufacture, and recycle into product portfolio design. IEEE Trans Eng Manag 49(4):479–490

    Google Scholar 

  • Melanz D, Jayakumar P, Negrut D (2016) Experimental validation of a differential variational inequality-based approach for handling friction and contact in vehicle/granular-terrain interaction. J Terrramech 65:1–13

    Google Scholar 

  • Milliman SR, Prince R (1989) Firm incentives to promote technological change in pollution control. J Environ Econ Manag 17(3):247–265

    Google Scholar 

  • Minoux M (1986) Mathematical programming: theory and algorithms. Wiley

  • Nagurney A (2010) Supply chain network design under profit maximization and oligopolistic competition. Transp Res E 46(3):281–294

    Google Scholar 

  • Nagurney A, Daniele P, Shukla S (2017) A supply chain network game theory model of cybersecurity investments with nonlinear budget constraints. Ann Oper Res 248(1–2):405–427

    Google Scholar 

  • Pang J-S, Stewart D (2008) Differential variational inequalities. Math Program 113(2):345–424

    Google Scholar 

  • Pati RK, Vrat P, Kumar P (2008) A goal programming model for paper recycling system. Omega 36:405–417

    Google Scholar 

  • Qiang QP (2015) The closed-loop supply chain network with competition and design for remanufactureability. J Clean Prod 105:348–356

    Google Scholar 

  • Qiang Q, Ke K, Anderson T, Dong J (2013) The closed-loop supply chain network with competition, distribution channel investment, and uncertainties. Omega 41(2):186–194

    Google Scholar 

  • Richter K, Weber J (2001) The reverse Wagner/Whitin model with variable manufacturing and remanufacturing cost. Int J Prod Econ 71:447–456

    Google Scholar 

  • Sarkis J, Cordeiro JJ (2001) An empirical evaluation of environmental efficiencies and firm performance: pollution prevention versus end-of-pipe practice. Eur J Oper Res 135(1):102–113

    Google Scholar 

  • Savaskan R, Bhattacharya S, Van Wassenhove L (2004) Closed-loop supply chains models with product remanufacturing. Manag Sci 50(2):239–252

    Google Scholar 

  • Scrimali L (2019) On the stability of coalitions in supply chain networks via generalized complementarity conditions. Netw Spatial Econom, 1–16

  • Shankar R, Bhattacharyya S, Choudhary A (2018) A decision model for a strategic closed-loop supply chain to reclaim end-of-life vehicles. Int J Prod Econ 195:273–286

    Google Scholar 

  • Srivastava SK (2008) Network design for reverse logistics. Omega 36(4):535–548

    Google Scholar 

  • Tian X, Liu T, Wang Q, Dilmurat A, Li D, Ziegmann G (2017) Recycling and remanufacturing of 3d printed continuous carbon fiber reinforced pla composites. J Clean Prod 142:1609–1618

    Google Scholar 

  • Toyasaki F, Daniele P, Wakolbinger T (2014) A variational inequality formulation of equilibrium models for end-of-life products with nonlinear constraints. Eur J Oper Res 236(1):340–350

    Google Scholar 

  • van der Laan EA (2019) Closed loop supply chain management. In: Operations, logistics and supply chain management. Springer, pp 353–375

  • van Loon P, Van Wassenhove LN (2018) Assessing the economic and environmental impact of remanufacturing: a decision support tool for OEM suppliers. Int J Prod Res 56(4):1662–1674

    Google Scholar 

  • VDR Guide GS (2006) Time value of commercial product returns. Manag Sci 52(8):1200–1214

    Google Scholar 

  • Wang L, Cai G, Tsay AA, Vakharia AJ (2017) Design of the reverse channel for remanufacturing: must profit-maximization harm the environment? Prod Oper Manag 26(8):1585–1603

    Google Scholar 

  • Yang Y, Huang Z, Qiang QP, Zhou G (2017) A mathematical programming model with equilibrium constraints for competitive closed-loop supply chain network design. Asia-Pacific J Oper Res 34(05):1750026

    Google Scholar 

  • Yu M, Cruz JM, et al. (2019) The sustainable supply chain network competition with environmental tax policies. Int J Prod Econ 217:218–231

    Google Scholar 

  • Zhu W, He Y (2017) Green product design in supply chains under competition. Eur J Oper Res 258(1):165–180

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Systems Science and Industrial Engineering, Binghamton University, Binghamton, NY, USA

    Sung Hoon Chung

  2. Department of Agricultural Economics, The Pennsylvania State University, University Park, PA, USA

    Robert D. Weaver

  3. Department of Mechanical and Industrial Engineering, Louisiana State University, Baton Rouge, LA, USA

    Hyun Woo Jeon

Authors
  1. Sung Hoon Chung
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Robert D. Weaver
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hyun Woo Jeon
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sung Hoon Chung.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chung, S.H., Weaver, R.D. & Jeon, H.W. Sustainable Management of Remanufacturing in Dynamic Supply Chains. Netw Spat Econ 20, 703–731 (2020). https://doi.org/10.1007/s11067-020-09493-7

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11067-020-09493-7

Keywords

Search

Navigation