用模糊逻辑方法分析故障模式和影响

José Jovani Cardiel-Ortega, R. Serrato
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引用次数: 4

摘要

失效模式和影响分析(FMEA)是风险管理中最常用的技术之一,因为它具有解决多学科工程问题的潜力。在制定FMEA时,专家的作用至关重要;他们根据自己的经验,通过表达自己的意见来识别故障模式。一个相关的方面是专家评估以获得风险优先级数(RPN)指标的方法,该指标基于定性分析和标准表,其中他们主观和直观地确定每个故障的因素级别(严重性,发生和检测)。在这种情况下,由于每个人对失败的解释,存在不精确性。因此,本研究提出了一个具有坚实数学基础的模糊逻辑评价系统,将这些不精确和不确定条件整合在一起,从而提供一个能够模拟专家评价形式的鲁棒系统,以支持和改进决策。本研究的主要贡献之一是在去模糊化阶段,调整质心方法并单独处理每个集合。利用此方法,得到了近似于传统方法的RPN值。通过仿真测试,确定了系统的最佳结构。该系统在瓜纳华托南部的一家纺织公司进行了验证。结果表明,该系统可靠地反映了专家如何进行风险评估。
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Failure Mode and Effect Analysis with a Fuzzy Logic Approach
Failure mode and effect analysis (FMEA) is one of the most used techniques in risk management due to its potential to solve multidisciplinary engineering problems. The role of experts is fundamental when developing the FMEA; they identify the failure modes by expressing their opinion based on their experience. A relevant aspect is a way in which the experts evaluate to obtain the indicator of the risk priority number (RPN), which is based on qualitative analysis and a table of criteria where they subjectively and intuitively determine the factor level (severity, occurrence, and detection) for each of the failures. With this, imprecision is present due to the interpretation that each one has regarding the failures. Therefore, this research proposes a fuzzy logic evaluation system with a solid mathematical basis that integrates these conditions of imprecision and uncertainty, thus offering a robust system capable of emulating the evaluation form of experts to support and improve decision making. One of the main contributions of this research is in the defuzzification stage, adjusting the centroid method and treating each set individually. With this, the RPN values approximate to the conventional technique were obtained. Simulations were carried out to test and determine the system’s best structure. The system was validated in a textile company in southern Guanajuato. The results demonstrate that the system reliably represents how experts perform risk assessment.
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