两部件系统视情维修与生产调度的联合优化模型
作者:
作者单位:

1.太原科技大学 工业与系统工程研究所;2.山西人文社科重点研究基地: 装备制造业创新发展研究中心

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中图分类号:

TH163.5

基金项目:

山西省自然科学基金项目(No. 201801D121166), 山西省高校科技创新项目(No. 201802091), 国家青年科学基金项目(No. 71701140 and 61703297), 太原科技大学校博士启动基金项目(No. 20162021), 山西省高等学校人文社会科学重点研究基地项目(201801032), and山西省重点研发计划项目(201703D111011).


Joint Optimization Model for Condition-based maintenance and Production Scheduling of Two-component System
Author:
Affiliation:

1.Division of Industrial and System Engineering, Taiyuan University of Science & Technology;2.Key Research Bases for Humanities and Social Sciences in Shanxi, Research Center for Innovation and Development of Equipment Manufacturing Industry

Fund Project:

The Natural Science Foundation of Shanxi Province, China(No. 201801D121166), the Scientific and Technological Innovation Programs of Higher Education Institutions in Shanxi (No. 201802091), the National Natural Science Foundation of China (No. 71701140 and 61703297), the PhD Research Startup Foundation of Taiyuan University of Science & Technology (No. 20162021), Program for the Philosophy and Social Sciences Research of Higher Learning Institutions of Shanxi (Grant No. 201801032) and Key Research and Development Program Projects in Shanxi Province (Grant No. 201703D111011).

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    摘要:

    为了解决生产调度过程中由于系统维护维修产生的资源闲置和时间成本增加问题, 将系统维修与生产调度联合建模. 在众多学者将系统作为整体进行生产调度与维修研究的基础上, 本文考虑了系统内各组成部件之间的复杂关系. 针对具有经济相关性的两部件系统, 以调度作业加工顺序、预防性维修阈值、机会维修阈值作为决策变量, 考虑到两部件同时维修比单部件独立维修更为经济, 故将机会维修引入到建模之中, 制订了机会维修、预防性维修、故障后更换的视情维修与生产调度结合的联合策略, 通过劣化状态空间划分法给出了生产调度过程中所有维修组合及其对应维修概率, 推导出联合概率密度函数, 建立了以最小化总加权期望完成时间为目标的 联合优化模型. 通过数值实验和灵敏度分析, 验证了提出的策略及模型的有效性.

    Abstract:

    In order to solve the problem of resource idleness and time cost increase caused by system maintenance and repair in production scheduling process, the system maintenance and production scheduling are modeled jointly. For two- component system with economic relevance, opportunity maintenance, preventive maintenance and after failure are established. Through the degraded state space division method, all maintenance combinations and probability calculation formulas of the scheduling operation are given, and the probability density function is derived. The joint optimization model aiming at minimizing the total weighted expected completion time is established. The experimental results show that the proposed model can effectively shorten the total completion time of the scheduling operation and has good sensitivity.

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历史
  • 收稿日期:2019-09-26
  • 最后修改日期:2021-02-20
  • 录用日期:2020-01-18
  • 在线发布日期: 2020-02-19
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