• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2024, Vol. 60 ›› Issue (4): 438-448.doi: 10.3901/JME.2024.04.438

• 交叉与前沿 • 上一篇    下一篇

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多目标混合流水车间机器故障重调度问题研究

苏建涛, 董绍华, 朱诗敏   

  1. 北京科技大学机械工程学院 北京 100083
  • 收稿日期:2023-04-04 修回日期:2023-11-16 出版日期:2024-02-20 发布日期:2024-05-25
  • 作者简介:苏建涛,男,1972年出生,博士研究生。主要研究方向为智能制造、智能工厂及智能物流。E-mail:cssjt@163.com;董绍华,男,1960年出生,教授,博士研究生导师。主要研究方向为物流系统仿真、制造执行系统等。E-mail:dshdle@me.ustb.edu.cn;朱诗敏,女,1994年出生。主要研究方向为智能调度及智能算法等。E-mail:1017916438@qq.com
  • 基金资助:
    国家自然科学基金资助项目(51305024)

Research on Machine Fault Rescheduling Problem of Multi Objective Hybrid Flow Shop Based on Intelligent Manufacturing

SU Jiantao, DONG Shaohua, ZHU Shimin   

  1. School of Mechanical Engineering, University of Science and Technology Beijing, Beijing 100083
  • Received:2023-04-04 Revised:2023-11-16 Online:2024-02-20 Published:2024-05-25

摘要: 在数字化转型过程中,如何解决好生产调度问题是研究者关注的问题。混合流水车间机器故障是在生产调度过程中常遇到的问题。为此,需要为快速解决机器故障的重调度问题找到方法。在解决机器故障重调度过程中,主要考虑的因素为加工时间不能确定、物流装卸时间以及生产设备布局限制,从而提出这种多种重调度组合的重调度方法。首先建立双目标数学模型,系统中植入NSGA-II算法求解初始调度方案,算法采用启发式规则和随机化的方式生成初始解,利用仿真的方法对调度方案进行评价。其次,将多种重调度方式融合在一起,通过设备故障仿真验证重调度方法,试验验证启发式规则作为初始解的一部分,可以非常好地提高算法的搜索效率,所研究的重调度方法能够有效解决混合流水车间机器故障问题,具有重要的意义。

关键词: 智能制造, 机器故障, 多目标优化, 重调度, 混合流水车间

Abstract: In the process of digital transformation, How to solve production scheduling problem,Researchers very attention. Machine failure is mixed flow shop to happen problem in production scheduling. Therefore,it is necessary to find a way to quickly solve the rescheduling of faulty machines. To this end, several main factors are needed to be considered, which are processing time the logistics loading and unloading time and the limitation of the layout of production equipment. Based on these considerations, a rescheduling method combining multiple rescheduling is proposed. Firstly, a dual-objective mathematical model is established, with the NSGA-II algorithm implanted into the system to solve the initial scheduling scheme. The algorithm uses heuristic rules and randomization to generate the initial solution and uses the simulation method to evaluate the scheduling scheme. Secondly, a variety of rescheduling methods are integrated, and the rescheduling method verified by equipment failure simulation and experimental verification heuristic rules can be used as part of the initial solution, which can greatly improve the search efficiency of the algorithm. The rescheduling method studied can effectively deal with machine failures in hybrid flow workshops and is of great significance.

Key words: intelligent manufacturing, machine breakdowns, multi-objective optimization, rescheduling, hybrid flow shop

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