主办:陕西省汽车工程学会
ISSN 1671-7988  CN 61-1394/TH
创刊:1976年

汽车实用技术 ›› 2023, Vol. 48 ›› Issue (16): 113-118.DOI: 10.16638/j.cnki.1671-7988.2023.016.023

• 工艺·材料 • 上一篇    

基于遗传算法在生产线平衡的应用

张国欣,商福永,梁封罡,高健章,刘 念*,徐华南   

  1. 长城汽车股份有限公司重庆分公司
  • 出版日期:2023-08-30 发布日期:2023-08-30
  • 通讯作者: 刘 念
  • 作者简介:张国欣(1976-),男,硕士,副高级工程师,研究方向为整车生产战略决策、整车生产成本管理、整车精 益生产,E-mail:BDZGX@163.com。 通信作者:刘念(1997-),女,研究方向为精益生产,E-mail:cqccjy@gwm.cn。

Application of Genetic Algorithm in Production Line Balance

ZHANG Guoxin, SHANG Fuyong, LIANG Fenggang, GAO Jianzhang, LIU Nian* , XU Huanan   

  1. Great Wall Motor Company Limited Chongqing Branch
  • Online:2023-08-30 Published:2023-08-30
  • Contact: LIU Nian

摘要: 为解决组装线右侧生产线作业间不平衡产生的时间损失问题,建立以线体工艺为前提, 满足工艺约束条件,提高生产线整体效率为目标的生产线平衡优化模型。作业组合的 6 个核 心要素分别为作业内容、作业工时、固定工位、作业部位、紧前作业及作业工具,只要对以 上内容增加约束条件,采用遗传算法,并借助 Python 编程语言算出满足约束条件的目标解, 即可得到线体优化的作业组合结果。以组装线右侧生产线为实例进行应用分析,经过程序优 化后,线体平衡率由 81.3%提升至 95.1%;根据程序输出的组合优化方案,进行线体试验,发 现线体平衡率为 93.8%,比优化前有显著提升,同时验证了本优化模型的合理性和有效性。

关键词: 生产线平衡;作业组合;遗传算法;计算模型

Abstract: In order to solve the problem of time loss caused by the imbalance between the production lines on the right side of the assembly line, a production line balance optimization model is established to meet the process constraints and improve the overall efficiency of the production line. The six core elements of the job combination are job content, job hours, fixed station, job site, immediate job and job tool. As long as the constraints are added to the above content, the genetic algorithm is used, and the Python programming language is used to calculate the target solution that meets the constraints, the job combination result of the line body optimization can be obtained. Taking the assembly line on the right side of the production line as an example for application analysis, after program optimization, the line balance rate increased from 81.3% to 95.1%; according to the combined optimization scheme of the program output, the line body test is carried out, and it is found that the line body balance rate is 93.8%, which is significantly improved compared with that before optimization, and the rationality and effectiveness of the optimization model are verified.

Key words: Line balance; Job mix; Genetic algorithm; Calculate model