Optimization of resource allocation in remanufacturing systems: A labor and automation perspective

Remanufacturing depicts a pivotal strategy within the circular economy framework to conserve and reintroduce high-quality components after their end-of-use period. Despite its acknowledged labor-intensive nature, existing literature lacks comprehensive models to aid decision-makers in allocating resources efficiently. Moreover, there is a conspicuous absence of scheduling approaches tailored to optimize labor resource allocation amidst fluctuating supply and demand dynamics. In response, this paper introduces a quantitative optimization model that enables optimal resource allocation over discrete time intervals, that facilitate industrial decisionmakers to plan their remanufacturing systems accordingly. Through an illustrative example, we evaluate the feasibility of our model by applying a dynamic programming algorithm to find the optimal resource allocation strategy. Here, we find that due to the variety of complexities associated with remanufacturing the achievement of an optimal solution necessitates judicious simplifications.