工业工程 ›› 2021, Vol. 24 ›› Issue (3): 104-114.doi: 10.3969/j.issn.1007-7375.2021.03.014

• 实践与应用 • 上一篇    下一篇

物料齐套时间不确定的多地总装作业前摄性调度

李思瀚, 莫超雄, 刘建军, 陈庆新, 毛宁   

  1. 广东工业大学 广东省计算机集成制造重点实验室,广东 广州 510006
  • 收稿日期:2019-01-28 发布日期:2021-06-26
  • 通讯作者: 刘建军(1982-),男,江西省人,副教授,主要研究方向为车间调度、智能优化等。E-mail:jianjun.liu@gdut.edu.cn E-mail:jianjun.liu@gdut.edu.cn
  • 作者简介:李思瀚(1994-),男,江西省人,硕士研究生,主要研究方向为生产计划与控制等
  • 基金资助:
    国家自然科学基金资助项目(51975129,71572049,61973089);广东省自然科学基金资助项目(2019A1515012158);广东省特支计划科技创新青年拔尖人才资助项目(2016TQ03X364);广州市珠江科技新星资助项目(201710010004)

Proactive Scheduling of Multi-location Final-assembly Operations with Uncertain Material Kitting Time

LI Sihan, MO Chaoxiong, LIU Jianjun, CHEN Qingxin, MAO Ning   

  1. Guangdong CIM Provincial Key Lab, Guangdong University of Technology, Guangzhou 510006, China
  • Received:2019-01-28 Published:2021-06-26

摘要: 定制型生产线的总装环节具有工程项目式运作、在客户地开展手工装配、所需物料众多等特点,装配组在各个客户地往来调配需要差旅时间,而装配物料又难以如期齐套,容易导致人员和物料的相互等待,从而延长了此类生产线的交付周期。本文通过对总装作业进行前摄性考虑以减少等待浪费、缩短交期。首先建立不确定环境下多地总装作业前摄性调度数学模型,然后以质量鲁棒性和解的鲁棒性为优化目标,构建了结合缓冲时间插入策略和抽样仿真技术的非支配排序遗传算法NSGA-II求解问题,最后通过实际样例验证了算法的有效性。

关键词: 总装作业, 前摄性调度, 不确定性, 鲁棒性, 抽样仿真

Abstract: The final assembly of the customized production line has the characteristics of project-style operation, manual assembly at the customer's site, and a large number of materials required. The assembly teams need travel time to deploy between each customer's site, and the assembly materials are difficult to be prepared as scheduled, which is easy to cause assembly teams and materials wait for each other, thereby extending the production lead time of such production lines. In order to reduce the waiting waste and shorten the delivery time, this paper makes a proactive consideration of the final assembly operation. First established under uncertainty environment more proactive sexual assembly operation scheduling mathematical model, then the robustness of reconciliation with quality robustness as the optimization goal, constructs the binding buffer insertion strategy and sampling time simulation technology of non dominated sorting genetic algorithm (NSGA II) to solve the problem, finally the effectiveness of the algorithm is validated by a practical sample.

Key words: final-assembly operations, proactive scheduling, uncertainty, robustness, sampling simulation

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