Green Scheduling Optimization Method of Special Vehicle Body-in-White Prototype Shops Considering Equipment Preventive Maintenance

被引：0
|
作者：
Li X. [1 ,2 ]
Zhou W. [1 ,2 ]
Tang H. [3 ]
Wu R. [1 ,2 ]
机构：
[1] School of Mechanical Engineering, Hubei University of Technology, Wuhan
[2] Hubei Key Laboratory of Modern Manufacturing and Quality Engineering, Hubei University of Technology, Wuhan
[3] School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan
来源：
Zhongguo Jixie Gongcheng/China Mechanical Engineering | 2023年 / 34卷 / 15期
关键词：
equipment preventive maintenance; flexible job shop; green scheduling; laser processing;
D O I：
10.3969/j.issn.1004-132X.2023.15.008
中图分类号：
学科分类号：
摘要：
A typical multi-objective flexible job-shop green scheduling model was established, and the makespan, total energy consumption of equipment and total smoke emission were taken into consideration. And an improved artificial bee colony algorithm was designed to solve this model. Firstly, according to the characteristics of periodic power attenuation of laser equipment, a preventive maintenance strategy that could distinguish laser equipment from ordinary mechanical equipment was proposed to reduce the makespan and the frequency of equipment failure. Then, a mutation method was designed based on equipment allocation and power selection, which could improve the local search a-bility of the algorithm. A selection method was introduced based on crowded distance in the follow bee search stage for population regeneration to obtain high-quality individuals. Finally, the comparison experiments were carried out based on the expanded common benchmark. Meanwhile, the effectiveness and feasibility of the model and algorithm were verified through the production case of a special vehicle body-in-white prototype workshop in an automotive equipment manufacturing enterprise. © 2023 China Mechanical Engineering Magazine Office. All rights reserved.
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页码：1832 / 1847
页数：15
相关论文
共 31 条
  • [1] GAHM C, DENZ F, DIRR M, Et al., Energy-efficient Scheduling in Manufacturing Companies:a Review and Research Framework, European Journal of Operational Research, 248, 3, pp. 744-757, (2016)
  • [2] LI X, QUO X, TANG H, Et al., Survey of Integrated Flexible Job Shop Scheduling Problems, Computers & Industrial Engineering, 174, (2022)
  • [3] ZHAO Shikui, Improved Hybrid Algorithm Based on Improved Neighborhood Structure for Flexible Job Shop Scheduling[J], Computer Integrated Manufacturing System, 24, 12, pp. 3060-3072, (2018)
  • [4] YANG Yanhua, YAO Ligang, Time Recursive Modeling and Cross Entropy Algorithm for Flexible Job Shop Scheduling Problem [J], Computer Integrated Manufacturing Systems, 27, 6, pp. 1703-1713, (2021)
  • [5] JANG Tianhua, Flexible Job Shop Scheduling Problem with Hybrid Grey Wolf Optimization Algorithm [J], Control and Decision, 33, 3, pp. 503-508, (2018)
  • [6] WANG Ling, WANG Jingjing, WU Chuge, Advances in Green Shop Scheduling and Optimization [J], Control & Decision, 33, 3, pp. 385-391, (2018)
  • [7] CALDEIRA R H, GNANAVELBABU A, VAIDYANATHAN T., An Effective Backtracking Search Algorithm for Multi-objective Flexible Job Shop Scheduling Considering New Job Arrivals and Energy Consumption[J], Computers & Industrial Engineering, 149, (2020)
  • [8] LI J Q, DENG J W, LI C Y, Et al., An Improved Jaya Algorithm for Solving the Flexible Job Shop Scheduling Problem with Transportation and Setup Times, Knowledge-Based Systems, 200, 3, (2020)
  • [9] MAO J, PAN Q, MIAO Z, Et al., An Effective Multi-start Iterated Greedy Algorithm to Minimize Makespan for the Distributed Permutation Flow-shop Scheduling Problem with Preventive Maintenance [J], Expert Systems with Applications, 169, (2021)
  • [10] SHEIKHALISHAHI M, ESKANDARI N, MASHAYEKHI A, Et al., Multi-objective Open Shop Scheduling by Considering Human Error and Preventive Maintenance, Applied Mathematical Modelling, 67, pp. 573-587, (2019)
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