[논문]퍼지 기반 다양한 모델을 이용한 회전익 항공기 착륙장치의 위험 우선순위 평가

나성현; 이광은; 구정모

doi:10.14346/jkosos.2021.36.2.49

퍼지 기반 다양한 모델을 이용한 회전익 항공기 착륙장치의 위험 우선순위 평가
Risk Analysis for the Rotorcraft Landing System Using Comparative Models Based on Fuzzy 원문보기

한국안전학회지 = Journal of the Korean Society of Safety, v.36 no.2, 2021년, pp.49 - 57

나성현 (국방기술품질원) , 이광은 (국방기술품질원) , 구정모 (국방기술품질원)

Abstract ▼ AI-Helper

In the case of military supplies, any potential failure and causes of failures must be considered. This study is aimed at examining the failure modes of a rotorcraft landing system to identify the priority items. Failure mode and effects analysis (FMEA) is applied to the rotorcraft landing system. In general, the FMEA is used to evaluate the reliability in engineering fields. Three elements, specifically, the severity, occurrence, and detectability are used to evaluate the failure modes. The risk priority number (RPN) can be obtained by multiplying the scores or the risk levels pertaining to severity, occurrence, and detectability. In this study, different weights of the three elements are considered for the RPN assessment to implement the FMEA. Furthermore, the FMEA is implemented using a fuzzy rule base, similarity aggregation model (SAM), and grey theory model (GTM) to perform a comparative analysis. The same input data are used for all models to enable a fair comparison. The FMEA is applied to military supplies by considering methodological issues. In general, the fuzzy theory is based on a hypothesis regarding the likelihood of the conversion of the crisp value to the fuzzy input. Fuzzy FMEA is the basic method to obtain the fuzzy RPN. The three elements of the FMEA are used as five linguistic terms. The membership functions as triangular fuzzy sets are the simplest models defined by the three elements. In addition, a fuzzy set is described using a membership function mapping the elements to the intervals 0 and 1. The fuzzy rule base is designed to identify the failure modes according to the expert knowledge. The IF-THEN criterion of the fuzzy rule base is formulated to convert a fuzzy input into a fuzzy output. The total number of rules is 125 in the fuzzy rule base. The SAM expresses the judgment corresponding to the individual experiences of the experts performing FMEA as weights. Implementing the SAM is of significance when operating fuzzy sets regarding the expert opinion and can confirm the concurrence of expert opinion. The GTM can perform defuzzification to obtain a crisp value from a fuzzy membership function and determine the priorities by considering the degree of relation and the form of a matrix and weights for the severity, occurrence, and detectability. The proposed models prioritize the failure modes of the rotorcraft landing system. The conventional FMEA and fuzzy rule base can set the same priorities. SAM and GTM can set different priorities with objectivity through weight setting.

주제어

표/그림 (24)

그림 Fig. 1. Membership function.
그림 Fig. 2. Process of proposed fuzzy model.
그림 Fig. 3. Intersection of expert opinion on fuzzy sets.
표 Table 1. Traits for expert weighting score
표 Table 2. Expert weighting results
그림 Fig. 4. Defuzzifier of the linguistic term for GTM.
그림 Fig. 5. Membership functions for severity.
표 Table 3. Risk level and linguistic expressions for severity
표 Table 4. Risk level and linguistic expressions for occurrence
표 Table 5. Risk level and linguistic expressions for detectability
그림 Fig. 6. Membership functions for occurrence.
그림 Fig. 7. Membership functions for detectability.
그림 Fig. 8. Landing system of rotorcraft.
표 Table 6. FMEA for landing system
표 Table 7. Priorities using fuzzy rule base
그림 Fig. 9. Fuzzy Rule Base(125 cases).
표 Table 8. Each expert opinion for SAM
표 Table 9. Parameter of SAM for severity of FM1
그림 Fig. 10. Result according to beta coefficient.
표 Table 10. Priorities using SAM
표 Table 11. Defuzzified crisp numbers for GTM
표 Table 12. Calculation for Grey relation coefficient of GTM
표 Table 13. Priorities using GTM
표 Table 14. Priority of landing system for various model

참고문헌 (11)

B. C. Shin, W. Y. Hwang, N. S. Ahn, D. H. Kim, G. L. Lee, B. K. Jang and J. H. Byun, "Suggestions on Enhancing the Effectiveness of Government Quality Assurance Activities for Military Supplies in Production Stage", Journal of Society Quality Management, Vol. 44, No. 1, pp. 153-166, 2016.
W. C. Shin and J. M. Chae, "Risk Priority Number using FMEA by the Plastic Moulding Machine", J. Korean Soc. Saf., Vol. 30, No. 5, pp. 108-113, 2015.

원문보기 상세보기
H. M. Kwon, M. K. Lee and S. H. Hong, "Risk Evaluation of Failure Cause for FMEA under a Weibull Time Delay Model", J. Korean Soc. Saf., Vol. 33, No. 3, pp. 83-91, 2018.

원문보기 상세보기
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상세보기
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상세보기
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상세보기
M. Yazdi. S. Daneshvar and H. Setareh, "An Extension to Fuzzy Developed Failure Mode and Effects Analysis (FDFMEA) Application for Aircraft Landing System", Safety Science, Vol. 98, pp. 113-123, 2017.

상세보기
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상세보기
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