Inventory planning for remanufacturing

Remanufacturing is a process by which a used product called a "core" is restored to like-new condition. The process involves disassembling the core down to its constituent used parts, differentiating between serviceable parts and scrap, and using a combination of serviceable parts and new parts to rebuild the product. A critical component of the process from an operational standpoint is the planning of core purchases, disassemblies, and new part purchases. These three unique inventory planning decisions have been scarcely addressed in the literature to date. This research presents and tests two alternative techniques for solving the remanufacturing inventory planning problem. The first is a deterministic network linear programming formulation with safety stock (ReNet), while the second is a stochastic formulation that explicitly accounts for uncertain yields (SIPR). The experiment is designed to test the relative performance of the two techniques and the effects of yield uncertainty and product characteristics on the solution cost. The results indicate that SIPR outperforms ReNet, particularly for higher levels of uncertainty. Further, product characteristics were shown to have a significant effect on both the relative performance and the solution cost. In particular, the expected yields of the highest-cost parts tend to drive the solution. Remanufacturing managers should therefore focus their resources on increasing the yields of high-cost parts through design and quality control initiatives. Since reducing yield uncertainty also significantly reduces cost, managers should further consider implementing procedures or investing capital to more accurately forecast yields.