LAPSE:2018.0628
Published Article
LAPSE:2018.0628
Sequence Planning for Selective Disassembly Aiming at Reducing Energy Consumption Using a Constraints Relation Graph and Improved Ant Colony Optimization Algorithm
Bingtao Hu, Yixiong Feng, Hao Zheng, Jianrong Tan
September 21, 2018
With environmental pollution and the shortage of resources becoming increasingly serious, the disassembly of certain component in mechanical products for reuse and recycling has received more attention. However, how to model a complex mechanical product accurately and simply, and minimize the number of components involved in the disassembly process remain unsolved problems. The identification of subassembly can reduce energy consumption, but the process is recursive and may change the number of components to be disassembled. In this paper, a method aiming at reducing the energy consumption based on the constraints relation graph (CRG) and the improved ant colony optimization algorithm (IACO) is proposed to find the optimal disassembly sequence. Using the CRG, the subassembly is identified and the number of components that need to be disassembled is minimized. Subsequently, the optimal disassembly sequence can be planned using IACO where a new pheromone factor is proposed to improve the convergence performance of the ant colony algorithm. Furthermore, a case study is presented to illustrate the effectiveness of the proposed method.
Keywords
constraints relation graph, disassembly sequence planning, energy consumption, improved ant colony optimization algorithm, selective disassembly
Suggested Citation
Hu B, Feng Y, Zheng H, Tan J. Sequence Planning for Selective Disassembly Aiming at Reducing Energy Consumption Using a Constraints Relation Graph and Improved Ant Colony Optimization Algorithm. (2018). LAPSE:2018.0628
Author Affiliations
Hu B: State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China [ORCID]
Feng Y: State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China [ORCID]
Zheng H: State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China
Tan J: State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China
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Journal Name
Energies
Volume
11
Issue
8
Article Number
E2106
Year
2018
Publication Date
2018-08-13
Published Version
ISSN
1996-1073
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PII: en11082106, Publication Type: Journal Article
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LAPSE:2018.0628
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doi:10.3390/en11082106
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Sep 21, 2018
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Calvin Tsay
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