Modeling a Remanufacturing Reverse Logistics Planning Problem: Some Insights into Disruptive Technology Adoption

Abstract

Remanufacturing is the process to restore the functionality of high-value Endof-life (EOL) products, which is a substantial link in reverse logistics systems for value recovery. However, due to the uncertainty of the reverse material flow, the planning of a remanufacturing reverse logistics system is complex. Furthermore, the increasing adoption of disruptive technologies in Industry 4.0/5.0, e.g., Internet of things (IoT), smart robots, cloud-based digital twin, additive manufacturing, etc., have shown a great potential for a smart paradigm transition of remanufacturing reverse logistics operations. In this paper, a new mixed-integer program is modeled for supporting several tactical decisions in remanufacturing reverse logistics, i.e., remanufacturing setups, production and inventory levels, purchase and transportation, and remanufacturing line utilization and balancing. The model is further extended by incorporating utilization-dependent nonlinear idle time cost constraints and stochastic takt time to accommodate different real-world scenarios. Through a set of numerical experiments, the influences of different demand patterns and idle time constraints are revealed. The potential impacts of disruptive technology adoption in remanufacturing reverse logistics are also discussed from managerial perspectives, which may help remanufacturing companies with a smart and smooth transition in the Industry 4.0/5.0 era.