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Energy-Saving Oriented Manufacturing Workshop Facility Layout: A Solution Approach Using Multi-Objective Particle Swarm Optimization

delete2022-02-27
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OA
AI
张中伟 封面图
张中伟 (Zhongwei Zhang)
吴立辉 封面图
吴立辉 (Lihui Wu) *
Z
Zhaoyun Wu
W
Wenqiang Zhang
S
Shun Jia
T
Tao Peng *
DOI:10.3390/su14052788delete
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摘要

摘要

En 中文
Low-carbon sustainable development has become the consensus of manufacturing enterprises to fulfill their social responsibilities. Facility layout is an essential part of manufacturing system planning. Current research has demonstrated the advantages of energy saving on the manufacturing system level where operational methods (e.g., energy-efficient production scheduling and path planning) can be utilized and do not require massive investment in the existing legacy system. However, these efforts are mostly based on the existing fixed facility layout. Meanwhile, although facility layout problems have been extensively studied so far, the related work seldom involves the optimization of energy consumption (EC) or other EC-related environmental impact indicators, and does not clearly reveal if EC can be an independent optimization objective in facility layout. Accordingly, whether the energy-saving potential of a manufacturing system can be further tapped through rational facility layout is the gap of the current study. To address this, an investigation into energy-saving oriented manufacturing workshop facility layout is conducted. Correspondingly, an energy-efficient facility layout (EFL) model for the multi-objective optimization problem that minimizes total load transport distance and EC is formulated, and a multi-objective particle swarm optimization-based method is proposed as the solution. Furthermore, experimental studies verify the effectiveness of the presented model and its solution, indicating that EC can be regarded as an independent optimization objective during facility layout, and EFL is a feasible energy-saving approach for a manufacturing system.
Keyword:
energy consumption
energy-efficient facility layout
multi-objective optimization
multi-objective particle swarm optimization

期刊

Sustainability 封面图
Sustainability
IF:
3.3
论文数:
10.7W
被引数:
28.4W

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H
Henan University of Technology
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8.8K
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被引数: 7.1K
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shanghai institute of technology
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5.8K
论文数: 3.7K
被引数: 1
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zhejiang university
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17.7W
论文数: 12.1W
被引数: 152
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