计算机集成制造系统 ›› 2015, Vol. 21 ›› Issue (第9期): 2504-2514.DOI: 10.13196/j.cims.2015.09.027

• 产品创新开发技术 • 上一篇    下一篇

基于多故障模式的复杂机械设备预防性维修决策

王远航1,2,邓超3,胡湘洪4,高军5,黄创绵1,2+   

  1. 1.工业和信息化部电子第五研究所
    2.广州市电子信息产品可靠性与环境工程重点实验室
    3.华中科技大学机械学院制造装备数字化国家工程中心
    4.广东省电子信息产品可靠性技术重点实验室
    5.广东韵脉质量技术服务有限公司
  • 出版日期:2015-09-30 发布日期:2015-09-30
  • 基金资助:
    高端装备关键产品质量与可靠性公共技术服务平台建设资助项目(粤经信创新[2014]60号);国家973计划资助项目(2011CB706803);国家自然科学基金资助项目(5137518151475189)。

Preventive maintenance scheduling for complex mechanical device based on multiple failure modes

  • Online:2015-09-30 Published:2015-09-30
  • Supported by:
    Project supported by the Common Technical Platform Construction for High-end Equipment Key Product Quality and Reliability(Guangdong Economic and Information Commission,No.[2014]60),the National Basic Research Program,China(No.2011CB706803),and the National Natural Science Foundation,China(No.5137518151475189).

摘要: 目前,复杂设备的维修维护往往是基于多部件的,然而单个部件往往具有多故障模式,且故障之间具有复杂的关联关系,导致基于多部件的维修决策方案并不一定合理。针对这一难题,提出一种复杂机械装备预防性维修决策方法,与传统的基于多部件的预防性维修决策不同,从故障模式的角度切入分析。根据系统结构和功能特征进行关键故障模式辨识,并将其分为突发类和退化类两类。讨论了复杂机械设备故障模式之间的依赖性、维修级别和维修效果等,进一步利用故障时间分布即寿命分布构建预防性维修决策的目标成本函数,并通过遗传算法实现含整型约束的非线性优化问题求解。所提出的方法在某镗床滑枕进给传统子系统中得到验证,并表现出良好性能。

关键词: 复杂机械设备, 预防性维修, 多故障模式, 维修成本, 遗传算法

Abstract: Based on the analysis of multiple failure modes,a Preventive Maintenance (PM) scheduling for complex mechanical device was proposed.According to system structure and function features,the key failure modes were identified.The dependences between failure modes,the maintenance level and the maintenance effects of complex mechanical device were discussed.The objective cost function of PM was constructed further by using failure time distribution,and the integer-constrained nonlinear optimization problem achieved by genetic algorithm was adopted to solve this function.The proposed approach was illustrated in a ram feed subsystem of a boring machine,and the effectiveness was proved.

Key words: complex mechanical device, preventive maintenance, multiple failure modes, maintenance cost, genetic algorithms

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