Optimization of Remanufacturing Disassembly Line Balance Considering Multiple Failures and Material Hazards

Wei Meng and Xiufen Zhang
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Wei Meng: College of Mechanical Engineering, Inner Mongolia University of Technology, Hohhot 010051, China
Xiufen Zhang: College of Mechanical Engineering, Inner Mongolia University of Technology, Hohhot 010051, China

Sustainability, 2020, vol. 12, issue 18, 1-16

Abstract: End-of-life (EOL) electromechanical products often have multiple failure characteristics and material hazard attributes. These factors create uncertain disassembly task sequences and affect the remanufacturing cost, environmental sustainability, and disassembly efficiency of the remanufacturing disassembly line system. To address this problem, a novel multi-constraint remanufacturing disassembly line balancing model (MC-RDLBM) is constructed in this article, which accounts for the failure characteristics of the parts and material hazard constraints. To assign the disassembly task reasonably, a disassembly priority decision-making model was presented to describe the relationship between the failure layer, the material hazards layer, and the economic feasibility layer. Furthermore, the multi-objective non-dominated sorting genetic algorithm II (NSGA-II) optimization for the MC-RDLBM is improved. To increase the convergence speed of the algorithm, an initial population construction method is designed, which includes the component failure and material hazards. Moreover, a novel genetic algorithm evolution rule with a Pareto non-dominant relation and crowded distance constraint is established, which expands the search scope of the chromosome’s autonomous evolution and avoids local convergence. Furthermore, a Pareto grade-based evaluation strategy for non-dominant solutions is proposed to eliminate the invalid remanufacturing disassembly task sequences. Finally, a case study verified the effectiveness and feasibility of the proposed method.

Keywords: remanufacturing disassembly line balance (RDLB); multiple failures; material hazards; NSGA-II algorithm; multi-objective optimization (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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