Parts quality‐based priority policy in remanufacturing environments

PurposeThe purpose of this study is to consider the acquisition of end‐of‐life products under variable quality consideration for remanufacturing so as to determine optimal control policy that minimizes per‐period expected costs that may guide future consideration by practitioners. Design/methodology/approachThe authors review recent literature on reverse supply chains and remanufacturing. They utilize an undiscounted Markov decision process methodology to ascertain the order amount of remanufacturable products using optimal control under minimum cost criterion. FindingsThe authors conclude that it makes sense for firms to focus on the cost management with production control based on quality levels with different acquisition costs of remanufacturable products. Research limitations/implicationsAlthough the Markov decision process methodology – which is well supported in literature – was diligently followed, the nature of analysis and discussion may be subject to authors’ bias. Future investigation and adoption of the methodological approach used will verify the paper findings. Practical implicationsThis study determines optimal control policy for ordering specific amount of product that minimizes per‐period expected costs for remanufacturing. Reverse supply‐chain professionals now have an easy‐to‐follow guide when acquiring end‐of‐life remanufacturable products alternatives with variable quality. Social implicationsThis study determines the optimal policy for ordering remanufacturable products. This information enables practitioners to reduce their carbon footprint in reverse supply chain through inspection/sorting before remanufacturing by processing only the type, quality, and quantity of needed product. Originality/valueFor reverse supply chain to be taken seriously by senior management in firms, it is imperative that practitioners in this field synchronize their operational‐level ordering decisions with holistic cost minimization objective (to maximize value recovery) to stay viable.