A simulation-optimisation approach for reconfigurable inventory space planning in remanufacturing facilities

Although remanufacturing facilities are becoming increasingly vital components in some supply chains, significant variability over time in returned product volumes, reusable part yields, and refurbished item demand can result in significant variability in storage requirements over time. In response, manufacturers can implement reconfigurable inventory systems to accommodate off-setting swings in storage needs between types of components and processing activities, including temporary external storage. A Monte Carlo (MC) simulation-optimisation approach has first been developed to emulate a generalised remanufacturing facility with random receiving patterns, component yields, and refurbished demand. Then, a multi-dimensional golden section search algorithm is implemented to identify optimal storage capacities and reconfiguration decisions in each time period that minimise long-term expected total cost. In pilot applications, improvements over non-reconfigurable systems range from 9% to 33% reductions in total storage space costs.