2.765

2022影响因子

(CJCR)

  • 中文核心
  • EI
  • 中国科技核心
  • Scopus
  • CSCD
  • 英国科学文摘

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

串行生产线中机器维修工人的任务分配问题研究

鄢超波 张雷

鄢超波, 张雷. 串行生产线中机器维修工人的任务分配问题研究. 自动化学报, 2021, 47(11): 2578-2584 doi: 10.16383/j.aas.c180781
引用本文: 鄢超波, 张雷. 串行生产线中机器维修工人的任务分配问题研究. 自动化学报, 2021, 47(11): 2578-2584 doi: 10.16383/j.aas.c180781
Yan Chao-Bo, Zhang Lei. Formulation and solution methodology for repairman allocation problem in serial production lines. Acta Automatica Sinica, 2021, 47(11): 2578-2584 doi: 10.16383/j.aas.c180781
Citation: Yan Chao-Bo, Zhang Lei. Formulation and solution methodology for repairman allocation problem in serial production lines. Acta Automatica Sinica, 2021, 47(11): 2578-2584 doi: 10.16383/j.aas.c180781

串行生产线中机器维修工人的任务分配问题研究

doi: 10.16383/j.aas.c180781
基金项目: 

国家自然科学基金 61603294

陕西省重点研发计划 2017GY-040

详细信息
    作者简介:

    张雷  西安交通大学系统工程研究所硕士研究生. 主要研究方向为生产系统性能分析和优化. E-mail: zhanglei6549@163.com

    通讯作者:

    鄢超波  博士, 西安交通大学电信学部自动化学院教授. 主要研究方向为生产系统的建模、分析和优化, 以及信息物理融合系统理论及其在制造、物流和仓储系统中的应用. 本文通信作者. E-mail: chaoboyan@mail.xjtu.edu.cn

Formulation and Solution Methodology for Repairman Allocation Problem in Serial Production Lines

Funds: 

National Natural Science Foundation of China 61603294

Key Research and Development Program of Shaanxi Province 2017GY-040

More Information
    Author Bio:

    ZHANG Lei   Master student at the Institute of Systems Engineering, Xi0an Jiaotong University. His research interest covers performance analysis and optimization of production systems

    Corresponding author: YAN Chao-Bo   Ph. D., professor at the School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi0an Jiaotong University. His research interest covers modeling, analysis, and optimization of production systems, and cyber-physical systems (CPS) theory and its applications to manufacturing, logistics, and inventory systems. Corresponding author of this paper
  • 摘要: 在串行生产线中, 机器会发生故障而且故障间隔时间随机, 因此需要维修工人及时维修, 使得故障的机器恢复加工能力, 否则就可能导致系统吞吐率降低. 如何在满足系统吞吐率的前提下, 使用尽可能少的维修工人来完成机器的维修任务, 本文称这样一个全新的问题为串行生产线中机器维修工人的任务分配问题. 针对该问题, 本文首先建立了问题的优化模型, 并将该优化问题转换为多个判定问题进行求解; 然后, 通过合理地定义机器的维修工作量, 使得判定问题可以类比为并行机调度问题; 最后, 采用了一种基于最长处理时间优先算法(Longest processing time, LPT)和回溯策略的启发式算法, 搜索最优的维修工人任务分配方式. 实验结果表明, 该方法能有效求解维修工人的任务分配问题.
    Recommended by Associate Editor LIU Yan-Jun
    1)  本文责任编委 刘艳军
  • 图  1  串行生产线

    Fig.  1  A serial production line

    图  2  串行生产线中维修工人任务分配

    Fig.  2  Repairman allocation in a serial production line

    表  1  机器参数

    Table  1  Machine parameters

    机器编号 故障率(次/分钟) 维修率(次/分钟) 维修工作量(分钟)
    1 0.2 5 0.04
    2 0.2 5 0.04
    3 0.6 5 0.12
    4 0.6 5 0.12
    5 0.4 5 0.08
    6 0.4 5 0.08
    7 0.2 5 0.04
    8 0.2 5 0.04
    下载: 导出CSV

    表  2  实验结果

    Table  2  Experimental results

    回溯次数 吞吐率(个/分钟) 工人数(人)
    0 0.8867 5
    10 0.8428 4
    50 0.8589 4
    100 0.8589 4
    下载: 导出CSV

    表  3  维修工人任务分配

    Table  3  Repairman task allocation

    回溯次数 分配方案
    0 $ D_1 = \{m_{3}\} $, $ D_2 = \{m_{4}\} $, $ D_3 = \{m_{5}, m_{7}\} $, $ D_4 = \{m_{6}, m_{8}\} $, $ D_5 = \{m_{1}, m_{2}\} $
    10 $ D_1 = \{m_{3}\} $, $ D_2 = \{m_{4}, m_{7}\} $, $ D_3 = \{m_{1}, m_{5}\} $, $ D_4 = \{m_{2}, m_{6}, m_{8}\} $
    50 $ D_1 = \{m_{2}, m_{3}\} $, $ D_2 = \{m_{4}\} $, $ D_3 = \{m_{1}, m_{5}\} $, $ D_4 = \{m_{6}, m_{7}, m_{8}\} $
    100 $ D_1 = \{m_{2}, m_{3}\} $, $ D_2 = \{m_{4}\} $, $ D_3 = \{m_{1}, m_{5}\} $, $ D_4 = \{m_{6}, m_{7}, m_{8}\} $
    下载: 导出CSV

    表  4  50台机器实验结果

    Table  4  Experimental results of 50 machines

    回溯次数 吞吐率(个/分钟) 工人数(人)
    0 0.6600 17
    100 0.6586 15
    下载: 导出CSV
  • [1] 张于贤, 李娜, 肖吉军. 基于排队论的生产线量化分析及优化. 制造业自动化, 2014, 7: 59-61 https://www.cnki.com.cn/Article/CJFDTOTAL-JXGY201407018.htm

    Zhang Yu-Xian, Li Na, Xiao Ji-Jun. Quantitative analysisand optimizationofthe production line based on the queuing theory. Manufacturing Automation, 2014, 7: 59-61 https://www.cnki.com.cn/Article/CJFDTOTAL-JXGY201407018.htm
    [2] Yang F J, Gao K Z, Simon I W, Zhu Y T, Zhu R. Decomposition methods for manufacturing system scheduling: a survey. IEEE/CAA Journal of Automatica Sinica, 2018, 5(2): 389-400 doi: 10.1109/JAS.2017.7510805
    [3] Zhao Y J, Yan C B, Zhao Q C, et al. Efficient simulation method for general assembly systems with material handling based on aggregated event-scheduling. IEEE Transactions on Automation Science and Engineering, 2010, 7(4): 762-775 doi: 10.1109/TASE.2009.2034135
    [4] Li J S, Meerkov S M. Production Systems Engineering, New York: Springer, 2009. 17-37
    [5] Xiao F L, Shao L P. Optimizing production line balance based on witness simulation. In: Proceedings of the 8th International Conference on Logistic, Informatics and Service Sciences. Toronto, ON, Canada: IEEE, 2018. 1-5
    [6] Borba L, Ritt M, Miralles C. Exact and heuristic methods for solving the robotic assembly line balancing problem. European Journal of Operational Research, 2018, 270(1): 146-156 doi: 10.1016/j.ejor.2018.03.011
    [7] Horng S L, Lin S S. Merging artificial immune system and ordinal optimization for solving the optimal buffer resource allocation of production line. In: Proceedings of the 9th International Conference on Knowledge and Smart Technology. Chonburi, Thailand: IEEE, 2017. 6-11
    [8] Sophie W, Andrea M, Raik S. Optimization of buffer allocations in flow lines with limited supply. ⅡSE Transactions, 2018, 50(3): 191-202 doi: 10.1080/24725854.2017.1328751?src=recsys
    [9] Zou D X, Gao L Q, Li S. A novel global harmony search algorithm for task assignment problem. Journal of Systems and Software, 2010, 83(10): 1678-1688 doi: 10.1016/j.jss.2010.04.070
    [10] Camacho G A, Cuellar D, Álvarez D. Heuristic approach for the multiple bin-size bin packing problem. IEEE Latin America Transactions, 2018, 16(2): 620-626 doi: 10.1109/TLA.2018.8327421
    [11] 李孙寸, 施心陵, 张松海, 董易, 高莲, 基于多元优化的三维装箱问题的研究. 自动化学报, 2018, 44(1): 106-115 doi: 10.16383/j.aas.2018.c160381

    Li Sun-Cun, Shi Xin-Ling, Zhang Song-Hai, Dong Yi, Gao Lian. Multi-variant optimization algorithm for three dimensional container loading problem. Acta Automatica Sinica, 2018, 44(1): 106-115 doi: 10.16383/j.aas.2018.c160381
    [12] Yan C B, Zhao Q C, Huang N J, Xiao G X, Li J S. Formulation and a simulation based algorithm for line-side buffer assignment problem in systems of general assembly line with material handling. IEEE Transactions on Automation Science and Engineering, 2010, 7(4): 902-920 doi: 10.1109/TASE.2010.2046892
    [13] Sels V, Coelho J, Dias A M, Vanhoucke M. Hybrid tabu search and a truncated branch-and-bound for the unrelated parallel machine scheduling problem. Computers and Operations Research, 2015, 53: 107-117 doi: 10.1016/j.cor.2014.08.002
    [14] Massabò I, Paletta G, Ruiz-Torres A J. A note on longest processing time algorithms for the two uniform parallel machine makespan minimization problem. Journal of Scheduling, 2016, 19(2): 207-211 doi: 10.1007/s10951-015-0453-x
    [15] Braun O, Chung F, Graham R. Worst-case analysis of the LPT algorithm for single processor scheduling with time restrictions. OR Spectrum, 2016, 38(2): 531-540 doi: 10.1007/s00291-016-0431-5
  • 加载中
图(2) / 表(4)
计量
  • 文章访问数:  581
  • HTML全文浏览量:  190
  • PDF下载量:  140
  • 被引次数: 0
出版历程
  • 收稿日期:  2018-11-23
  • 录用日期:  2019-03-25
  • 刊出日期:  2021-11-18

目录

    /

    返回文章
    返回