퍼지 베이지안 네트워크와 증거 이론을 이용한 FTA-FMEA 통합시스템에 의한 오류진단Fault Diagnosis of Combined FTA and FMEA Using Fuzzy Bayesian Network and Evidence Theory
- Other Titles
- Fault Diagnosis of Combined FTA and FMEA Using Fuzzy Bayesian Network and Evidence Theory
- Authors
- 최성운
- Issue Date
- Dec-2020
- Publisher
- 한국경영공학회
- Keywords
- FTA; FMEA; FBN; TrDTBBA; Fault Diagnosis; Uncertain Circumstances; Fusion Strategy
- Citation
- 한국경영공학회지, v.25, no.4, pp.101 - 128
- Journal Title
- 한국경영공학회지
- Volume
- 25
- Number
- 4
- Start Page
- 101
- End Page
- 128
- URI
- https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/79562
- ISSN
- 2005-7776
- Abstract
- Purpose This study presents a combined model of Fault Tree Analysis (FTA) and Failure Mode and Effects Analysis (FMEA) using evidence theory and Fuzzy Bayesian Network (FBN) under uncertain circumstances which are caused by the presence of incompleteness, randomness and ambiguity of failure modes.
Methods In order to identify the critical failure modes according to the multi-level FTA-FMEA, the Trapezoidal Distribution-Type Basic Belief Assignment (TrDTBBA) is used to consider the viewpoints of experts and to resolve the conflicts of evidence The proposed FTA-FMEA-FBN model derives fuzzy posterior probabilities to implement fault diagnosis approach which is more suitable than fuzzy prior probabilities when conducting qualitative reasoning of vague probability.
Results A novel method for identifying the critical failure modes according to the level of hierarchical Bill of Material (BOM) is based on the proposed FTA-FMEA-FBN integrated model that illustrates chassis system consisting of 6 components, 4 modules and 6 parts.
Conclusion This suggested FTA-FMEA-FBN model is convenient for a risk evaluation in the following uncertain circumstances: 1) The information of failure modes are incomplete, 2) The numbers of failure modes comprised of three levels are too abundant, 3) The probabilities of failure modes have a lack of quantification data. The fusion strategy of those three risk techniques implements computational efficiency and provides a synergistic effect to accurately identify the critical failure modes under uncertain circumstances.
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Collections - 공과대학 > 산업경영공학과 > 1. Journal Articles
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