Disassembly Sequence Planning for Intelligent Manufacturing Using Social Engineering Optimizer

Abstract

Product disassembly and recycling are important issues in green design. Disassembly sequence planning (DSP) is an important problem in the product disassembly process. The core idea is to generate the best or approximately optimal disassembly sequence to reduce disassembly costs and time. According to the characteristics of the DSP problem, a new algorithm to solve the DSP problem is proposed. Firstly, a disassembly hybrid graph is introduced, and a disassembly constraint matrix is established. Secondly, the disassembling time, replacement frequency of disassembly tool and replacement frequency of disassembly direction are taken as evaluation criteria to establish the product fitness function. Then, an improved social engineering optimizer (SEO) method is proposed. In order to enable the algorithm to solve the problem of disassembly sequence planning, a swap operator and swap sequence are introduced, and steps of the social engineering optimizer are redefined. Finally, taking a worm reducer as an example, the proposed algorithm is used to generate the disassembly sequence, and the influence of the parameters on the optimization results is analyzed. Compared with several heuristic intelligent optimization methods, the effectiveness of the proposed method is verified.