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一种基于D-GRA和数据包裹分析的CNC机床新型FMECA方法.

Hailong Tian1, Yuzhi Sun2, Chuanhai Chen1

  • 1School of Mechanical and Aerospace Engineering, Jilin University, Key Laboratory of CNC Equipment Reliability, Ministry of Education, Changchun, 130022, Jilin Province, People's Republic of China.

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概括

这项研究通过完善风险因素和整合新方法来增强CNC机床的故障模式,效应和关键性分析 (FMECA). 改进的方法为提高系统可靠性和减少故障提供了更明确的方向.

关键词:
BCC模型模型的 BCC 模型.在CNC机床上,我们可以使用CNC机床.距离灰色关系分析FMECA FMECA 是一个很好的方法.改进方向 改进方向

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科学领域:

  • 机械工程 机械工程
  • 可靠性工程可靠性工程
  • 制造系统制造系统的制造

背景情况:

  • 传统的故障模式,效应和关键性分析 (FMECA) 在分析CNC机床可靠性方面面临局限性,包括模糊的风险因素和不清楚的改进策略.
  • 现有的方法难以平等对待风险因素,缺乏加强弱点的具体指导.

研究的目的:

  • 为CNC机床提出一个增强的FMECA方法,解决传统方法的局限性.
  • 完善风险因素评估,并引入一种新的方法来优先考虑故障模式.
  • 为提高数控机床的可靠性提供明确,可操作的指导方针.

主要方法:

  • 扩大严重程度 (S) 分为机器危险 (M) 和个人危险 (P);分为功能结构复杂性 (D1) 和检测成本 (D2) 的可检测性 (D).
  • 综合距离分析方法 (DAM) 和灰色关系分析 (GRA) 提出距离-灰色关系分析 (D-GRA) 用于确定风险因子权重.
  • 引入了BCC模型,以评估故障模式作为决策单位,并确定针对目标改进的效率值.

主要成果:

  • 开发了一种修改后的风险优先数 (RPN) 计算方法,将风险因子权重和故障模式效率值集成在一起.
  • 拟议的方法应用于电系统,证明了其在排名故障模式方面的有效性,并与传统的RPN方法相比较有利.
  • 确定了提高数控机床可靠性的具体改进方向.

结论:

  • 增强的FMECA方法提供了一个更精确和可操作的方法,用于CNC机床的可靠性分析.
  • 整合D-GRA和BCC模型为识别和解决关键故障模式提供了一个强大的框架.
  • 该研究证实了拟议的方法在指导复杂机械的可靠性提升工作方面,优于传统方法的优势.