Exploiting User-Base and Product-Return Data to Optimize End-of-Life Spare Parts Supply

Abstract

We investigate how a manufacturer can exploit existing data to optimize sourcing strategies for a spare part in its end-of-life phase. In this phase, the regular supply of the part has been discontinued, but its demand due to customer warranty claims still needs to be satisfied to maintain a high after-sales service level. Three sourcing strategies are commonly seen in practice---last-time buy, remanufacturing parts from returned products, and procuring from aftermarket suppliers. However, little is known about how to jointly rationalize these strategies, especially in the presence of data on user base, product returns and various environmental factors. Using a model that explicitly accounts for user base dynamics, product returns and parts demand, we show that the optimal joint strategy is characterized by a set of control targets, consisting of order-up-to levels for last-time buy and aftermarket procurement, remanufacture-up-to levels, and dispose-down-to levels. The optimal inventory levels grow when more products are in use or the part failure rate increases, and the manufacturer enjoys more cost savings when warranty demand and product return flows are more predictable. These results in more general models with age-differentiated parameters. In a numerical study, we demonstrate that our model can bring significant benefits to the manufacturer when more accurate and real-time data on system parameters are acquired and exploited in decisions, and the reward from the joint implementation of all sourcing strategies is also remarkable. The remanufacturing solution is more intensively used when it is less costly and more product returns are received, and aftermarket procurement contributes more to fulfilling demand in the latter stages of the service cycle.

Keywords: end-of-life inventory problem; spare parts; user base information; product returns; remanufacturing; 3D printing

JEL Classification: M11