• 제목/요약/키워드: Failure Mode Effect & Analysis

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수소충전소용 수소 충전 노즐의 고장 유형 및 영향분석 (A Study on Failure Mode and Effect Analysis of Hydrogen Fueling Nozzle Used in Hydrogen Station )

  • 김주현;조계용;지상원
    • 한국수소및신에너지학회논문집
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    • 제34권6호
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    • pp.682-688
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    • 2023
  • In this paper, analyzes the type of failure and its effect on the hydrogen fueling nozzle used in hydrogen station. Failure of hydrogen fueling nozzle was analyzed using a qualitative risk assessment method, failure mode and effect analysis. The failure data of hydrogen fueling nozzles installed in domestic hydrogen stations are collected, and the failure types are classified, checked the main components causing the failure. Criticality analysis was derived based on frequency and severity depending on the failure mode performed. A quality function is developed by a performance test evaluation item of the hydrogen fueling nozzle, and the priority order of design characteristics is selected. Through the analysis results, the elements to improve the main components for enhancing the quality and maintenance of the hydrogen fueling nozzle were confirmed.

오류유형 영향분석(FMEA)을 적용한 수술준비 위험예방활동의 효과 (A Study on Failure Mode and Effect Analysis (FMEA) for Preoperative Risk Prevention)

  • 김창희;이미향
    • 간호행정학회지
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    • 제22권5호
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    • pp.415-423
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    • 2016
  • Purpose: The purpose of this research was to provide patients with safe preoperative preparatory procedures by removing any risk factors from the preparatory procedures by using failure mode and effects analysis, which is a prospective risk-managing tool. Methods: This was a research design in which before and after conditions of a single group were studied, Failure mode and effects analysis were applied for the preparatory procedures done before operations. Results: The preparation omission rate before the operation decreased from 2.70% to 0.04%, and operation cancellation rate decreased from 0.48% to 0.08%. Conclusion: Failure mode and effects analysis which remove any risk factors for patients in advance of the operation is effective in preventing any negligent accidents.

고장나무를 이용한 양방향 컨버터의 신뢰성 분석 (Fault-tree based reliability analysis for bidirectional converter)

  • 허대호;강필순
    • 전기전자학회논문지
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    • 제23권1호
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    • pp.254-260
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    • 2019
  • 본 논문에서는 양방향 dc-to-dc 컨버터의 고장원인, 고장영향, 고장 결과를 파악하기 위한 failure mode and effect analysis(FMEA)와 양방향 컨버터의 위험도를 고려한 fault-tree analysis(FTA)를 통해 고장률을 예측한다. 전기차의 구동전압을 효율적으로 상승시키기 위해 인버터 앞단에 부착되는 양방향 컨버터는 배터리 전력을 dc-link 커패시터로 방전시키는 승압모드와 회생전력을 배터리로 충전시키는 강압모드를 가진다. 양방향 컨버터의 동작 특성을 고려한 FMEA 결과를 바탕으로 컨버터의 위험도를 고려한 고장나무를 설계한다. 전기차 MCU용에 맞는 설계 파라메타를 설정하고 출력전압 리플과 인덕터 전류 리플에 따른 커패시터와 인덕터의 부품 고장률을 분석한다. 또한 동작 온도에 따른 주요부품의 고장률을 MIL-HDBK-217F를 이용하여 구한다. 마지막으로 부품 고장률을 고장나무의 기본 사상의 고장률로 반영하여 컨버터 고장률과 평균고장시간을 예측한다.

자기검사회로를 이용한 대기이중계구조 결함허용제어기의 설계 및 신뢰도평가에 관한 연구 (A Study on Design and Reliability Assessment for Embedded Hot-Standby Sparing FT System Using Self-Checking Logic)

  • 이재호;이강미;김용규;신덕호
    • 한국철도학회논문집
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    • 제9권6호
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    • pp.725-731
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    • 2006
  • Hot Standby sparing system detecting faults by using software, and being tolerant any faults by using Hardware Redundancy is difficult to perform quantitative reliability prediction and to detect real time faults. Therefore, this paper designs Hot Standby sparing system using hardware basis self checking logic in order to overcome this problem. It also performs failure mode analysis of Hot Standby sparing system with designed self checking logic by using FMEA (Failure Mode Effect Analysis), and identifies reliability assessment of the controller designed by quantifying the numbers of failure development by using FTA (Fault Tree Analysis)

고압산소 치료기에 대한 고장모드 분석 (Failure Mode Analysis for a Hyperbaric Oxygen Chamber)

  • 전태보;박성빈
    • 산업기술연구
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    • 제33권A호
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    • pp.9-14
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    • 2013
  • Reliability plays a pivotal role in the development of medical instruments. A hyperbaric oxygen chamber, as a medical/health device, is known to help medical therapy for diversity of diseases through provision of high purity oxygen. The use of hyperbaric oxygen chamber is expected to increase in the future and study to examine reliability and safety is needed. We have performed reliability assessment for a newly developed hyperbaric oxygen chamber in this study. We first briefly discussed the system structure and mechanism. We then performed FMEA (Failure Mode and Effect Analysis) for the chamber. We drew major failure modes affecting the system performance and performed in depth analysis for measuring the expected effects.

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In-plane 모드 반복굽힘 조건에서 90° 엘보우의 손상 위치와 방향에 미치는 직경과 두께 영향 (Effect of Diameter and Thickness on the Failure Location and Orientation of 90° Elbows Under In-plane Mode Cyclic Bending)

  • 홍진의;김진원
    • 한국압력기기공학회 논문집
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    • 제18권2호
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    • pp.77-86
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    • 2022
  • This study investigates the effect of the diameter and thickness on crack initiation location and orientation of 90° elbows under in-plane mode displacement-controlled cyclic bending loads. Finite element (FE) analysis of cyclic failure test is conducted for elbow specimens under in-plane mode displacement-controlled cyclic bending to identify the parameters affecting crack location and orientation. Furthermore, parametric FE analysis of the pipe elbows with various pipe nominal sizes and Schedules is performed, and the crack location and orientation from the results of FE analysis are determined. It is found that the crack location and orientation in the pipe elbows are determined mianly by the radius to thickness ratio of pipe elbows (Rm/t). It is also found that the presence of internal pressure slightly increases the value of Rm/t at which the failure mode changes.

전단파괴모드를 고려한 철근콘크리트 보통전단벽-골조 건물의 붕괴메커니즘 (Collapse Mechanism of Ordinary RC Shear Wall-Frame Buildings Considering Shear Failure Mode)

  • 추유림;김태완
    • 한국지진공학회논문집
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    • 제25권1호
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    • pp.1-9
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    • 2021
  • Most commercial buildings among existing RC buildings in Korea have a multi-story wall-frame structure where RC shear wall is commonly used as its core at stairways or elevators. The members of the existing middle and low-rise wall-frame buildings are likely arranged in ordinary details considering building occupancy, and the importance and difficulty of member design. This is because there are few limitations, considerations, and financial burdens on the code for designing members with ordinary details. Compared with the intermediate or unique details, the ductility and overstrength are insufficient. Furthermore, the behavior of the member can be shear-dominated. Since shear failure in vertical members can cause a collapse of the entire structure, nonlinear characteristics such as shear strength and stiffness deterioration should be adequately reflected in the analysis model. With this background, an 8-story RC wall-frame building was designed as a building frame system with ordinary shear walls, and the effect of reflecting the shear failure mode of columns and walls on the collapse mechanism was investigated. As a result, the shear failure mode effect on the collapse mechanism was evident in walls, not columns. Consequently, it is recommended that the shear behavior characteristics of walls are explicitly considered in the analysis of wall-frame buildings with ordinary details.

머신러닝을 이용한 알루미늄 전해 커패시터 고장예지 (Machine Learning Based Failure Prognostics of Aluminum Electrolytic Capacitors)

  • 박정현;석종훈;천강민;허장욱
    • 한국기계가공학회지
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    • 제19권11호
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    • pp.94-101
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    • 2020
  • In the age of industry 4.0, artificial intelligence is being widely used to realize machinery condition monitoring. Due to their excellent performance and the ability to handle large volumes of data, machine learning techniques have been applied to realize the fault diagnosis of different equipment. In this study, we performed the failure mode effect analysis (FMEA) of an aluminum electrolytic capacitor by using deep learning and big data. Several tests were performed to identify the main failure mode of the aluminum electrolytic capacitor, and it was noted that the capacitance reduced significantly over time due to overheating. To reflect the capacitance degradation behavior over time, we employed the Vanilla long short-term memory (LSTM) neural network architecture. The LSTM neural network has been demonstrated to achieve excellent long-term predictions. The prediction results and metrics of the LSTM and Vanilla LSTM models were examined and compared. The Vanilla LSTM outperformed the conventional LSTM in terms of the computational resources and time required to predict the capacitance degradation.

Design Optimization of Double-array Bolted Joints in Cylindrical Composite Structures

  • Kim, Myungjun;Kim, Yongha;Kim, Pyeunghwa;Park, Jungsun
    • International Journal of Aeronautical and Space Sciences
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    • 제17권3호
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    • pp.332-340
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    • 2016
  • A design optimization is performed for the double-bolted joint in cylindrical composite structures by using a simplified analytical method. This method uses failure criteria for the major failure modes of the bolted composite joint. For the double-bolted joint with a zigzag arrangement, it is necessary to consider an interaction effect between the bolt arrays. This paper proposes another failure mode which is determined by angle and distance between two bolts in different arrays and define a failure criterion for the failure mode. The optimal design for the double-bolted joint is carried out by considering the interactive net-tension failure mode. The genetic algorithm (GA) is adopted to determine the optimized parameters; bolt spacing, edge distance, and stacking sequence of the composite laminate. A purpose of the design optimization is to maximize the burst pressure of the cylindrical structures by ensuring structural integrity. Also, a progressive failure analysis (PFA) is performed to verify the results of the optimal design for the double-bolted joint. In PFA, Hashin 3D failure criterion is used to determine the ply that would fail. A stiffness reduction model is then used to reduce the stiffness of the failed ply for the corresponding failure mode.

RCM에서 상관관계 계수를 이용한 치명도 분석에 관한 연구 (A Study on the Criticality Analysis using Correlation Coefficient in Reliability Centered Maintenance)

  • 윤덕수;정광우
    • 한국신뢰성학회지:신뢰성응용연구
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    • 제17권1호
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    • pp.11-21
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    • 2017
  • Purpose: The occurrence ranks of failure modes can come from the real failure but the severity ranks of failure modes require a highly subjective point of view of users. The severity ranks have to find more objective and scientific values. Methods: We found the optimal values by using the correlation analysis between failure mode effects and the criticality number like RPN (Risk Priority Number) in RCM. Result: This paper shows the result that verified whether the weighted values on each failure effect in criticality number calculation is suitable to the actual failures or not. To get the verification, it used the 5 year data and correlation analysis. Based on the analyzed result, We proposed the more suitable values. Conclusion: This correlation analysis approach can provide guidance of RCM analysis across many industries and situations.