Enhancing value in reverse supply chains by sorting before product recovery

Abstract

Offering a well-designed reverse supply chain programme can significantly improve the ability of any organisation to differentiate itself, and even to take market share away, from its competitors. Reverse supply chain considerations should be a part of an organisation's corporate strategy. From a macro-level perspective, value propositions of reverse supply chains in for an organisation, and/or the industry in which the organisation operates, include considerations for both strategies (to reuse, repair, refurbish, remanufacture, retrieve parts or cannibalise components, recycle, scrap, redesign returned products, etc.) and effective operations (to handle and sort returns by value and ease of remanufacture) to sustain and even enhance organisational competency. In this article, we examine the role of sorting used products before disassembly for parts retrieval and remanufacturing under stochastic variability based on customer demand using a Markov decision process. We address a problem of managing costs in a remanufacturing environment with stochastically variable demand and model it for two types of used parts. Each part type is assumed to have varying quality and acquisition costs. The cost function includes manufacturing, holding and backlog costs components. We compute optimal purchase policy that maximises the expected average profit per period. Using a case example from photocopier industry, numerical analysis is performed to study the implications of various holding cost for two parts on optimal purchase policy in remanufacturing environments.

Keywords:

• remanufacturing system
• reverse supply chains
• optimal sorting policy
• Markov decision process

Acknowledgements

This research was made possible in part by the support of a grant from the Donald and Sally Lucas Graduate School of Business and by the JSPS Grants-in-Aid for Scientific Research No. 23510193. Earlier version of the research was presented at the 3rd World Conference on Production and Operations Management in Tokyo, Japan, in 2008. Furthermore, the authors are grateful to editors and three anonymous reviewers for insightful comments on earlier version of this article.