Modeling and optimization for disassembly planning

For the past two decades, increased efforts by both governments and the general public have been enforced through stricter legislations and more awareness to make manufacturing more environmentally conscious. Product refurbishing and component re-use are being applied on a wider scale worldwide. Disassembly, hence, has attracted more attention both in academia and the industry. Concepts and methods for disassembly planning should be further developed to support this new manufacturing environment. A semi-generative macro disassembly process planning approach based on the Traveling Salesperson formulation has been developed and is reported in this paper. Precedence graphs, which depict the precedence relationships between disassembly operations, are being utilized. The problem of generating optimal macro-level process plans is combinatorial in nature and proven NP-hard. Hence, a random-based hill-climbing heuristic based on Simulated Annealing is tailored for this problem. Finally, a realistic case study is presented to illustrate the working of the proposed methodology. The presented method produced good quality suboptimal solutions and is proven efficient in terms of computation time as demonstrated by the obtained results.