一个基于模糊的模型建议,使用故障模式和效果分析和Z数字来确定风险评估优先级:汽车工厂的真实案例研究
Emine Bozkus1,2, İhsan Kaya2,3
1Wolfson School of Mechanical, Electrical & Manufacturing Engineering, Loughborough University, Loughborough, UK.
概括
本研究引入了一种使用 Delphi,DEMATEL 和 VIKOR 与 Z 数的综合故障模式和效应分析 (FMEA) 方法,用于在人机协作中加强风险评估,提高工业安全.
科学领域:
- 工业工程 工业工程 工业工程
- 风险管理 风险管理
- 运营研究 运营研究
背景情况:
- 在制造业中,人机协作带来了复杂的风险.
- 准确的风险评估对于运营安全和效率至关重要.
- 现有的方法可能无法充分处理专家判断中的不确定性.
研究的目的:
- 开发和验证一个集成的故障模式和效应分析 (FMEA) 方法.
- 改进公共汽车生产线内人机器人协作中的风险评估.
- 在不确定性下使用Z数字将专家判断纳入.
主要方法:
- 整合了Delphi技术,DEMATEL和VIKOR方法的使用.
- 应用Z数来量化风险因素的不确定性 (发生,严重程度,检测).
- 使用Fuzzy Cohen的kappa进行专家共识和可靠性分析.
主要成果:
- 德马特尔有效地发现了故障模式之间的相互依赖.
- 维科尔使得风险有了强有力的优先级,强调严重程度和发生率作为关键因素.
- 硬件,过程可靠性和机器人技术水平被确定为关键故障模式.
结论:
- 建议的FMEA综合方法为风险评估提供了一个精确,可适应和可靠的方法.
- 该方法可以在复杂的工业环境中加强决策,使专家评估不确定.
- 这一框架对于在人机协作环境中提高安全性和可靠性是有价值的.
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