Optimization of Remanufacturing Disassembly Line Balance Considering Multiple Failures and Material Hazards
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 disa...
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doaj-6e89295ec8e24ef6a0c690b9ee77e28f2020-11-25T03:18:59ZengMDPI AGSustainability2071-10502020-09-01127318731810.3390/su12187318Optimization of Remanufacturing Disassembly Line Balance Considering Multiple Failures and Material HazardsWei Meng0Xiufen Zhang1College of Mechanical Engineering, Inner Mongolia University of Technology, Hohhot 010051, ChinaCollege of Mechanical Engineering, Inner Mongolia University of Technology, Hohhot 010051, ChinaEnd-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.https://www.mdpi.com/2071-1050/12/18/7318remanufacturing disassembly line balance (RDLB)multiple failuresmaterial hazardsNSGA-II algorithmmulti-objective optimization |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Wei Meng Xiufen Zhang |
spellingShingle |
Wei Meng Xiufen Zhang Optimization of Remanufacturing Disassembly Line Balance Considering Multiple Failures and Material Hazards Sustainability remanufacturing disassembly line balance (RDLB) multiple failures material hazards NSGA-II algorithm multi-objective optimization |
author_facet |
Wei Meng Xiufen Zhang |
author_sort |
Wei Meng |
title |
Optimization of Remanufacturing Disassembly Line Balance Considering Multiple Failures and Material Hazards |
title_short |
Optimization of Remanufacturing Disassembly Line Balance Considering Multiple Failures and Material Hazards |
title_full |
Optimization of Remanufacturing Disassembly Line Balance Considering Multiple Failures and Material Hazards |
title_fullStr |
Optimization of Remanufacturing Disassembly Line Balance Considering Multiple Failures and Material Hazards |
title_full_unstemmed |
Optimization of Remanufacturing Disassembly Line Balance Considering Multiple Failures and Material Hazards |
title_sort |
optimization of remanufacturing disassembly line balance considering multiple failures and material hazards |
publisher |
MDPI AG |
series |
Sustainability |
issn |
2071-1050 |
publishDate |
2020-09-01 |
description |
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. |
topic |
remanufacturing disassembly line balance (RDLB) multiple failures material hazards NSGA-II algorithm multi-objective optimization |
url |
https://www.mdpi.com/2071-1050/12/18/7318 |
work_keys_str_mv |
AT weimeng optimizationofremanufacturingdisassemblylinebalanceconsideringmultiplefailuresandmaterialhazards AT xiufenzhang optimizationofremanufacturingdisassemblylinebalanceconsideringmultiplefailuresandmaterialhazards |
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1724624599167008768 |