Disassembly Sequence Planning for End-of-Life Products
Nowadays, manufactures are under tremendous pressure to dispose product in an environmentally responsible way to pursue a sustainable development. Disassembly operations are required in the product recycling and maintenance period. An optimal disassembly sequence can reduce the disassembly cost and time. This thesis proposes an efficient method for selective disassembly sequence planning (DSP). The proposed method includes two main aspects: product representation and sequence searching. Multi-level constraint matrices based on product’s bill of material (BOM) are constructed. This representation approach can identify the product’s hierarchical structure to reduce the searching size of the sequence plans. Traversal algorithm and genetic algorithm are used to search the desired disassembly sequence. A disassembly feasibility check is integrated in the genetic algorithm to generate a better disassembly sequence with a less searching time. Several case studies are used to verify the proposed algorithms. In addition, destructive disassembly operations are considered to remove those constraints that cannot be removed by the non-destructive disassembly.