Strategic Planning for the Reverse Supply Chain: Optimal End-of-Life Option, Product Design, and Pricing

TR Number
Journal Title
Journal ISSN
Volume Title
Virginia Tech

A company's decisions on how to manage its reverse supply chain (RSC) are important for both economic and environmental reasons. From a strategic standpoint, the key decision a manufacturer makes is whether or not to collect products at their end-of-life (EOL) (i.e., when their useful lives are over), and if so, how to recover value from the recovered products. We call this decision as the EOL option of a product, and it determines how the RSC is designed and managed overall. Many EOL options exist for a product such as resale, refurbishment, remanufacturing and part salvage. However, many factors influence the optimal EOL option. These factors include the product's: (i) characteristics, (ii) design, and (iii) pricing. A product's characteristics are its properties that impact the various costs incurred during its production, residual part values, and customer demand. In this work, the product design is viewed as the choice of quality for each of its parts. A part's quality-level determines, among other things, its cost, salvage value, and the likelihood of obtaining it in good condition from a disassembled used product. Finally, the manufacturer must determine how to price its new and used products. This decision depends on many considerations such as whether new and used products compete and whether competition exists from other manufacturers. The choice of appropriate EOL options for products constitutes a foundation of RSC design. In this work, we study how to optimally determine a product's optimal EOL option and consider the impact of product design and product pricing on this decision.

We present a full description of the system that details the relationships among all entities. The system description reveals the use of a production planning type of modeling strategy. Additionally, a comprehensive and general mathematical model is presented that takes into consideration multi-period planning and product inventory. A unique aspect of our model over previous production planning models for RSC is that we consider the product returns as being endogenous variables rather than them being exogenous. This model forms the basis of our research, and we use its special cases in our analysis.

To begin our analysis of the problem, we study the case in which the product design and price are fixed. Both non-mandated and mandated collection are considered. Our analysis focuses on a special case of the problem involving two stages: in the first stage, new products are produced, and in the second stage, the EOL products are collected for value recovery. For fixed product design and price, our analysis reveals a fundamental mapping of product characteristics onto optimal EOL options. It is germane to our understanding of the problem in general since a multi-period problem is separable into multiple two-stage problems. Necessary and sufficient optimality conditions are also presented for each possible solution of this two-stage problem. For the two-part problem, a graphical mapping of product characteristics onto optimal EOL options is also presented, which reveals how EOL options vary with product characteristics.

Additionally, we study the case of product design under mandated collection, as encountered in product leasing. We assume new production cost, part replacement cost, and part salvage value to be functions of the quality-level of a part along with the likelihood of recovering a good-part from a returned product. These are reasonable assumptions for leased products since the customer is paying for the usage of the product over a fixed contract period. In this case, the two-stage model can still be used to gain insights. For the two-part problem, a method for mapping part yields onto optimal EOL options is presented. Closed-form optimality conditions for joint determination of part yields and EOL options are not generally attainable for the two-stage case; however, computationally efficient methods for this problem are developed for some relatively non-restrictive special cases. It is found that, typically, a part may belong to one of three major categories: (i) it is of low quality and will need to be replaced to perform remanufacturing, (ii) it is of high quality and its surplus will be salvaged, or (iii) it is of moderate quality and just enough of its amount is collected to meet remanufactured product demand.

Finally, we consider the problem of determining optimal prices for new and remanufactured products under non-mandated manufacturer's choice of collection. New and remanufactured products may or may not compete, depending on market conditions. Additionally, we assume the manufacturer to have a monopoly on the product. Again, the two-stage problem is used and efficient solution methods are developed. Efficient solution methods and key insights are presented.

Supply Chain, Reverse Supply Chain, Reverse Logistics, Production Economics, Mathematical Modeling, Optimization, Remanufacturing, Value Recovery