基于失效模式、影响分析和Z数的风险评估优先级模糊模型建议:一个汽车工厂的真实案例研究。

IF 1.6 4区 医学 Q3 ERGONOMICS
Emine Bozkus, İhsan Kaya
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引用次数: 0

摘要

综合失效模式和影响分析(FMEA)方法结合了德尔菲技术、决策试验和评估实验室(DEMATEL)和vlsekreriijumska Optimizacija I Kompromisno Resenje (VIKOR)方法,并辅以Z数。将该方法应用于土耳其客车生产线的实际案例,以改进人机协作中的风险评估。DEMATEL可识别故障模式之间的相互依赖关系,而VIKOR可实现有效的风险优先级排序。在评估发生、严重程度和检测的不确定性下,Z数包含了专家的判断。严重性和发生的权重最高(0.4062和0.2589)。硬件、过程可靠性和机器人技术水平成为前三大故障模式。Fuzzy Cohen's κ确保专家共识和统计可靠性。比较分析支持了复杂工业环境中决策方法的精确性、适应性和鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A fuzzy-based model proposal for risk assessment prioritization using failure mode and effect analysis and Z numbers: a real case study in an automotive factory.

An integrated Failure Mode and Effect Analysis (FMEA) methodology combines the Delphi technique, Decision-Making Trial and Evaluation Laboratory (DEMATEL), and Vlsekrerijumska Optimizacija I Kompromisno Resenje (VIKOR) methods, enhanced with Z numbers. The approach applies to a real case in a bus production line in Turkey to improve risk assessment in human-robot collaboration. DEMATEL identifies interdependencies among failure modes, while VIKOR enables effective risk prioritization. Z numbers incorporate expert judgment under uncertainty in evaluating occurrence, severity, and detection. Severity and occurrence receive the highest weights (0.4062 and 0.2589). Hardware, process reliability, and robot technology level emerge as the top three failure modes. Fuzzy Cohen's κ ensures expert consensus and statistical reliability. A comparative analysis supports the precision, adaptability, and robustness of the methodology for decision-making in complex industrial environments.

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来源期刊
CiteScore
4.80
自引率
8.30%
发文量
152
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