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带失效的拉式生产系统预防性维护建模

周炳海 刘子龙

周炳海, 刘子龙. 带失效的拉式生产系统预防性维护建模. 自动化学报, 2018, 44(6): 1045-1052. doi: 10.16383/j.aas.2017.c160767
引用本文: 周炳海, 刘子龙. 带失效的拉式生产系统预防性维护建模. 自动化学报, 2018, 44(6): 1045-1052. doi: 10.16383/j.aas.2017.c160767
ZHOU Bing-Hai, LIU Zi-Long. Preventive Maintenance Modeling of Pull System With Failures. ACTA AUTOMATICA SINICA, 2018, 44(6): 1045-1052. doi: 10.16383/j.aas.2017.c160767
Citation: ZHOU Bing-Hai, LIU Zi-Long. Preventive Maintenance Modeling of Pull System With Failures. ACTA AUTOMATICA SINICA, 2018, 44(6): 1045-1052. doi: 10.16383/j.aas.2017.c160767

带失效的拉式生产系统预防性维护建模

doi: 10.16383/j.aas.2017.c160767
基金项目: 

国家自然科学基金 71471135

详细信息
    作者简介:

    刘子龙  同济大学机械与能源工程学院工业工程研究所硕士研究生.主要研究方向为集成制造系统调度与控制, 离散系统的建模、调度仿真和控制技术.E-mail:liuzilongcumt@163.com

    通讯作者:

    周炳海  同济大学机械与能源工程学院教授.主要研究方向为制造系统/物流系统的建模、调度、仿真和控制技术, 生产系统预防性维护建模.本文通信作者.E-mail:bhzhou@tongji.edu.cn

Preventive Maintenance Modeling of Pull System With Failures

Funds: 

National Natural Science Foundation of China 71471135

More Information
    Author Bio:

     student at the Institute of Industrial Engineering, School of Mechanical Engineering, Tongji University. His research interest covers scheduling and control of integrated manufacturing systems, discrete system modeling, scheduling, simulation and control

    Corresponding author: ZHOU Bing-Hai  Professor at the School of Mechanical Engineering, Tongji University. His research interest covers modeling, scheduling, simulation, and control in integration of manufacturing systems, reliability and preventive maintenance model for systems. Corresponding author of this paper
  • 摘要: 为了有效解决同时具有随机失效与退化失效的拉式生产系统的维护问题,提出了基于状态的双阶段预防性维护(Preventive maintenance,PM)策略.首先,根据设备的退化状态、生产端状态以及库存容量构建了系统的状态空间,并利用马尔科夫链描述系统的状态转移.之后,分别以最小化失效率和最大化产出速率为目标,建立了考虑检测周期、看板数量以及预防性维护阈值的综合预防性维护模型.针对设备随役龄增加而故障频发的特点,引入失效率递增因子.最后,给出了最小化失效率和最大化产出速率两种目标下的求解算法,并对决策变量做了敏感性分析.数值实例与现有方案的对比表明了所建模型和算法的有效性.
    1)  本文责任编委 胡昌华
  • 图  1  拉式生产系统

    Fig.  1  Pull production system

    图  2  系统状态转移图

    Fig.  2  System state transition diagram

    图  3  决策变量对系统的影响

    Fig.  3  Effects of decision variables on system

    图  4  失效率递增因子对可用度的影响

    Fig.  4  Effect of increase factor on availability

    图  5  看板数量与检测频率对失效率的作用

    Fig.  5  Effect of Kanban$'$s quantity and inspection frequency on ROF

    图  6  看板数量与检测频率对可用度的作用

    Fig.  6  Effect of Kanban$'$s quantity and inspection frequency on availability

    表  1  符号及含义

    Table  1  Symbols and definitions

    符号 定义
    $i$ 退化阶段序号
    $j$ 生产端状态
    $d$ 退化总阶段
    $k$ 库存区产品数量
    $K$ 看板最优量(决策量)
    $ins$ 最优检测速率(决策量)
    $b_1$ & $b_2$ 阈值(决策量)
    $\lambda_d$ 退化速率
    $\lambda_i$ 阶段$i$的失效速率
    $\lambda_a$ 订单到达速率
    $\lambda_p$ 订单完成速率
    $1/{\lambda _{\rm{ins}}}$ 检测平均间隔期
    $1/\mu_{ins}$ 检测平均用时
    $1/\mu_r$ 小修平均用时
    $1/\mu_{upm}$ UPM平均用时
    $1/\mu_{ppm}$ PPM平均用时
    $1/\mu_{up}$ 更换平均用时
    $UB$ & $LB$ 数值上(下)限
    下载: 导出CSV

    表  2  实验参数

    Table  2  Experiment parameters

    变量 实际值
    $\lambda_a$ 1.0 接单能力平均100单/天
    $\lambda_p$ 1.4 生产能力平均140单/天
    $\lambda_d$ 0.02 平均50天退化一个程度
    $\lambda_0$ 0.005 初始状态失效间隔期200天
    $d$ 8 退化分为8个阶段
    $\mu_{ins}$ 0.8 检测平均用时1.25 h
    $\mu_{r}$ 0.25 小修平均用时4 h
    $\mu_{upm}$ 1 非完美维护平均用时1 h
    $\mu_{ppm}$ 0.5 完美维护平均用时2 h
    $\mu_{up}$ 0.2 更换平均用时5 h
    下载: 导出CSV

    表  3  $\lambda_a=1.0 $时结果对比

    Table  3  Comparison of results when $\lambda_a=1.0$

    $\lambda_p$$ROF$$K, \lambda_{ins}, b_1, b_2$
    $K, \lambda_{ins}, b$
    $THR$$K, \lambda_{ins}, b_1, b_2$
    $K, \lambda_{ins}, b$
    ${\bf 1.0}$${\bf 0.0370} $${\bf 6, 0.074, 2, 4} $${\bf 0.87} $${\bf 10, 0.043, 2, 5}$
    $0.0393 $$7, 0.082, 3 $$0.82 $$11, 0.103, 5 $
    ${\bf 1.2}$${\bf 0.0395} $${\bf 10, 0.179, 2, 6} $${\bf 0.960 } $${\bf 11, 0.149, 3, 5} $
    $0.0402 $$10, 0.152, 4 $$0.94 $$11, 0.124, 2 $
    ${\bf 1.4}$${\bf 0.0339} $${\bf 6, 0.074, 2, 4} $${\bf 1.001} $${\bf 20, 0.035, 6, 7}$
    $0.0351 $$7, 0.081, 3 $$1.201 $$19, 0.042, 4 $
    ${\bf 1.6}$${\bf 0.0297} $${\bf 5, 0.151, 2, 6} $${\bf 1.202} $${\bf 20, 0.018, 5, 8} $
    $0.0321 $$6, 0.181, 1 $$1.187 $$21, 0.032, 3 $
    下载: 导出CSV
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出版历程
  • 收稿日期:  2016-11-14
  • 录用日期:  2017-02-06
  • 刊出日期:  2018-06-20

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