Optimization of a stochastic remanufacturing network with an exchange option

An international manufacturer of industrial equipment offers its customers a remanufacturing service consisting of a refurbishment of the most critical part in order to rejuvenate the equipment. Offering remanufacturing services is in line with a servitization strategy. We develop a strategic decision support tool to optimize the required remanufacturing network. Investment decisions have to be made, not only concerning the number and locations of remanufacturing facilities, but also concerning the appropriate capacity and inventory levels to guarantee specific service levels. These network decisions are influenced by the way remanufacturing services are offered. We consider two service delivery strategies, either a quick exchange of the used part by an available remanufactured one or re-installing the original part after it has been remanufactured. Given the high level of uncertainty, we build a stochastic, profit maximizing model to simultaneously determine the optimal network design and the optimal service delivery strategy for a multi-product, multi-level network for repairable service parts. The rapid modeling formulation with a non-linear objective function subject to non-linear constraints is solved by the differential evolution algorithm. We conduct the analysis for fast and slow moving part types. The model can be easily extended to more general settings, while the case-study provides valuable insights for practitioners.