基于模糊topsis方法的失效模式及影响分析——以海底控制模块为例

Q4 Business, Management and Accounting
A. Kolios, A. Umofia, M. Shafiee
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引用次数: 17

摘要

失效模式与影响分析(FMEA)是一种最常用的可靠性工程技术,用于识别、评估和降低工程风险。本文根据业内专家的意见和经验,对水下控制模块(SCM)的潜在失效模式进行了识别。接下来是一个全面的基于组件的FMEA研究,使用风险优先级数(RPN),其中揭示了SCM中最关键的失效模式。然后,提出了一种基于模糊topsis的多准则决策方法,对FMEA研究确定的最关键失效模式进行分析和优先排序。为此,开发了一个独特的十参数临界模型,并首次应用于评估与SCM故障相关的风险。结果表明,所提出的模糊TOPSIS模型能显著提高传统FMEA技术在海上油气行业中的性能和适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Failure mode and effects analysis using a fuzzy-TOPSIS method: a case study of subsea control module
Failure mode and effects analysis (FMEA) is one of the most common reliability engineering techniques used for identifying, evaluating and mitigating the engineering risks. In this paper, the potential failure modes of a subsea control module (SCM) are identified based on industry experts' opinions and experiences. This is followed by a comprehensive component based FMEA study using the risk-priority-number (RPN) where the most critical failure modes in the SCM are revealed. A fuzzy TOPSIS-based multiple criteria decision making methodology is then proposed to analyse and prioritise the most critical failure modes identified by the FMEA study. To this aim, a distinct ten-parameter criticality model is developed and, for the first time, is applied to evaluate the risks associated with SCM failures. The results indicate that the proposed fuzzy TOPSIS model can significantly improve the performance and applicability of the conventional FMEA technique in offshore oil and gas industry.
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来源期刊
International Journal of Multicriteria Decision Making
International Journal of Multicriteria Decision Making Business, Management and Accounting-Strategy and Management
CiteScore
0.70
自引率
0.00%
发文量
9
期刊介绍: IJMCDM is a scholarly journal that publishes high quality research contributing to the theory and practice of decision making in ill-structured problems involving multiple criteria, goals and objectives. The journal publishes papers concerning all aspects of multicriteria decision making (MCDM), including theoretical studies, empirical investigations, comparisons and real-world applications. Papers exploring the connections with other disciplines in operations research and management science are particularly welcome. Topics covered include: -Artificial intelligence, evolutionary computation, soft computing in MCDM -Conjoint/performance measurement -Decision making under uncertainty -Disaggregation analysis, preference learning/elicitation -Group decision making, multicriteria games -Multi-attribute utility/value theory -Multi-criteria decision support systems and knowledge-based systems -Multi-objective mathematical programming -Outranking relations theory -Preference modelling -Problem structuring with multiple criteria -Risk analysis/modelling, sensitivity/robustness analysis -Social choice models -Theoretical foundations of MCDM, rough set theory -Innovative applied research in relevant fields
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