• Journal of Applied Reliability
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• v.17 no.1
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• pp.28-37
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• 2017

Purpose: This paper proposes a procedure that may infer and identify interaction failures in a module. Methods: In design FMEA, we defined an interaction model between components and proposed a method for selecting a single component by using the standard specification classification table and four methods for choosing the related components. We also introduced the function tree for function and requirement characteristic analysis and proposed utilization of standard stress lists and 1st and 2nd stress analysis tables to determine the effect the stress analysis has on interactions. Finally, the interaction mechanism diagram was proposed and used to infer the failure mechanism. Process FMEA also established procedures in a similar way. Results: We established a procedure for predicting the failure mode due to interaction between components based on Company A's multi-step FMEA procedure. Conclusion: By applying the proposed interaction FMEA procedure to the development model, we were able to confirm the effect of the new derivation on the failure mode of interaction, which was not predicted by the existing FMEA.

• Journal of Korean Society for Quality Management
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• v.42 no.1
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• pp.43-61
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• 2014

Purpose: This study identifies preventive measures for VOC management by analyzing the causes and effects of factors that contribute to high risk service failure using FMEA on KORAIL VOC data. Methods: Two research methods were used. First, a Risk Priority Number (RPN) was assigned to each KORAIL VOC based on Failure Mode and Effect Analysis (FMEA). Second, multiple regression analysis was run with RPN factors that include severity, occurrence, and detection as the independent variables and customer dissatisfaction as the dependent variable. Results: Multiple regression analysis showed that RPN factors including severity, occurrence, and detection had significantly positive relationship with customer dissatisfaction. Based on these results, an FMEA was performed on VOC categories with high RPN for railroad stations including platform, ticketing, ticket verification, parking, and escalator, and VOC categories with high RPN for trains including entrance doors, cafes, air quality, announcement, and ticket verification. Conclusion: This study has practical implications to service failure management. A priority order using FMEA was established for the list of customer dissatisfactions that should be addressed to actively manage service failure, and strategies for tackling this priority list are offered.

• Journal of IKEEE
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• v.23 no.1
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• pp.254-260
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• 2019

The failure rate of bidirectional dc-to-dc converter is predicted through the failure mode and effect analysis (FMEA) and the fault-tree analysis (FTA) considering the operational risk. In order to increase the driving voltage of the electric vehicle efficiently, the bidirectional converter is attached to the front of the inverter. It has a boost mode for discharging battery power to the dc-link capacitor and a buck mode for charging the regenerative power to the battery. Based on the results of the FMEA considering the operating characteristics of the bidirectional converter, the fault-tree is designed considering the risk of the converter. After setting the design parameters for the MCU for the electric vehicle, we analyze the failure rate of the capacitor due to the output voltage ripple and the inductor component failure rate due to the inductor current ripple. In addition, we obtain the failure rate of major parts according to operating temperature using MIL-HDBK-217F. Finally, the failure rate and the mean time between failures (MTBF) of the converter are predicted by reflecting the part failure rate to the basic event of the fault-tree.

• Proceedings of the KSR Conference
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• 2009.05a
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• pp.162-168
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• 2009

FMEA(Failure Mode and Effect Analysis) is a failure analysis method for the system to identify the potential failure modes, and their effects and causes to reduce or mitigate the critical effects of the system. FMEA for railway was introduced with reliability of railway system, and this was used for identifying and analysing the possible hazards qualitatively to meet the requirements in early stage of business. In general, the overall failure data of system could be managed from design stage by FMEA, and also the countermeasures to prevent many predicted failures could be established by identification of failure modes and assement of failure effects by FMEA. Using these advantages of FMEA, the effectiveness of reliability improvement could be expected if FMEA is applied continuously in operation stage. It is essential that railway vehicles are maintained with high level of safety and reliability not to happen any failures in operation. This paper is proposed the proper FMEA for maintenance of railway vehicles compared with existing FMEA.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.5
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• pp.1601-1607
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• 2010

This paper presents FMEA (Failure Mode Effect Analysis) for maintenance of mail sorting machine which is for automatic sorting of mail. We suggest the update method of regular diagnosis item and period for maintenance of mail sorting machine using the risk priority number which is calculated by severity, occurrence, and detection of failure mode of mail sorting machine, and shows FMEA adoption example of letter sorting machine. This paper also describes the current maintenance system and status of mail sorting machine in the domestic postal logistics environment, and FMEA adoption step. The proposed maintenance using FMEA will be adapted for more easy and efficiency maintenance of mail sorting machine.

• Journal of Ocean Engineering and Technology
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• v.23 no.6
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• pp.32-38
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• 2009

An FMEA for the waterjet-lifter of a DSNM is performed to prevent the occurrence of device failure. A waterjet-lifter raises and transports manganese nodules from the deep-sea floor up to a somewhat elevated place, from which a pin-scraper transports the lifted nodules to the inner space of the DSNM. A concept design for a device using the axiomatic design methodology is shown as the mapping between the functional domain and physical domain. The FMEA for a DSNM is introduced briefly and the rating criteria of severity, occurrence, and detection for the DSNM are defined. The FMEA of the functional requirements of a DSNM device is accomplished. Three kinds of failure modes, as well as their effects and causes, are predicted. Current design control methods for detecting potential failures, such as physical or computational experiments, design confirmation, and mathematical calculation, are described and the recommended actions for several significant causes are suggested.

• Journal of Applied Reliability
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• v.10 no.2
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• pp.123-135
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• 2010

Failure mode and effects analysis (FMEA) is a widely used technique to assess or to improve reliability of products or processes at early stage of development. Traditionally, the prioritization of failures for corrective actions is performed by evaluating risk priority numbers (RPN). In practice, due to insufficient evaluation criteria specific to related products and processes, RPN is not always evaluated properly. This paper reestablishes an effective methodology for prioritization of failure modes in FMEA procedure. Revised evaluation criteria of RPN are devised and a refined FMEA sheet is introduced. To verify the proposed methodology, it is applied to inspection processes of PCB products.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.6
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• pp.631-638
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• 2015

In this study, semiquantitative failure mode, effects, and criticality analysis (FMECA) for the reliability analysis of a solid rocket propulsion system is performed. The semiquantitative FMECA is composed of failure mode and effects analysis (FMEA) and criticality analysis (CA). To perform FMECA, the structure of the solid rocket propulsion system is divided into 43 parts down to the component level, and FMEA is conducted at the design stage considering 137 potential failure modes. CA is then conducted for each failure mode, during which the criticality number is estimated using the failure rate databases. The results demonstrate the relationship between potential failure modes, causes, and effects, and their risk priorities are evaluated qualitatively. Additionally, several failure modes with higher criticality and severity values are selected for high-priority improvement.

• Journal of Korean Academy of Nursing Administration
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• v.22 no.5
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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.

• Industrial Engineering and Management Systems
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• v.14 no.4
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• pp.379-391
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• 2015

Several risk assessment techniques have been presented and investigated in previous research, focusing mainly on the failure mode and effect analysis (FMEA). FMEA can be employed to determine where failures can occur within industrial systems and to assess the impact of such failures. This research proposes a novel methodology for hazard analysis and risk assessments that integrates FMEA with the bow-tie model. The proposed method has been applied and evaluated in a real industrial process, illustrating the effectiveness of the proposed method. Specifically, the bowtie diagram of the critical equipment in the adopted plant in the case study was built. Safety critical barriers are identified and each of these is assigned to industrial process with an individual responsible. The detection rating to the failure mode and the values of risk priority number (RPN) are calculated. The analysis shows the high values of RPN are 500 and 490 in this process. A global corrective actions are suggested to improve the RPN measure. Further managerial insights have been provided.