A meta-heuristic approach for supporting adaptive disassembly sequencing using a multi-objective concept

One of the key features of environmentally conscious manufacturing has been the efforts to promote product recycling and remanufacturing. Efficient material re-utilisation through product disassembly to retrieve the desired parts and/or subassemblies is one rational approach. This is because it can promote the conservation of both material and energy resources whilst concurrently reducing environmental impact. However, because manufactured products may be made from many components, disassembly load becomes a critical factor that may obstruct the recovery of materials. Accordingly, it is essential to develop a practical method for deriving a disassembly plan to decrease such load, and to endow a certain value to the product at the end of its life cycle. With this understanding, the authors have developed a practical procedure to produce an adaptive disassembly strategy. The authors have applied a meta-heuristic method known as genetic programming ( GP) as a search engine to derive the adaptive disassembly sequence together with a multi-objective optimisation method termed MOON 2R. The authors have also proposed a hierarchical sequencing method to cope with large/complex products and added several ideas to increase the applicability associated with the interests in disassembly of hazardous and/or valuable parts, and alternative disassembly actions. Through numerical experiments, the authors examined the effectiveness of the proposed approach by showing its support for relevant planning and design decisions for product recycling and remanufacturing from various viewpoints.