• Journal of Korean Society for Quality Management
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• v.47 no.3
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• pp.571-582
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• 2019

Purpose: To develop a risk metric for failure cause that can help determine the action priority of each failure cause in FMEA considering time sequence of cause- failure- detection. Methods: Assuming a quadratic loss function the unfulfilled mission period, a risk metric is obtained by deriving the failure time distribution. Results: The proposed risk metric has some reasonable properties for evaluating risk accompanied with a failure cause. Conclusion: The study may be applied to determining action priorities among all the failure causes in the FMEA sheet, requiring further studies for general situation of failure process.

• Journal of the Korean Society of Safety
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• v.31 no.4
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• pp.136-142
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• 2016

The FMEA is a widely used technique to pre-evaluate and avoid risks due to potential failures for developing an improved design. The conventional FMEA does not consider the possible time gap between occurrence and detection of failure cause. When a failure cause is detected and corrected before the failure itself occurs, there will be no other effect except the correction cost. But, if its cause is detected after the failure actually occurs, its effects will become more severe depending on the duration of the uncorrected failure. Taking this situation into account, a risk metric is developed as an alternative to the RPN of the conventional FMEA. The severity of a failure effect is first modeled as linear and quadratic severity functions of undetected failure time duration. Assuming exponential probability distribution for occurrence and detection time of failures and causes, the expected severity is derived for each failure cause. A new risk metric REM is defined as the product of a failure cause occurrence rate and the expected severity of its corresponding failure. A numerical example and some discussions are provided for illustration.

• Proceedings of the Korea Concrete Institute Conference
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• 2003.05a
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• pp.181-186
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• 2003

There are many uncertainties in structural failures or structures, so probabilistic failure cause assessment should be performed in order to consider the uncertainties. However, in many cases of forensic engineering, the failure cause assessments are performed by deterministic approach though number of uncertainties are existed in the failures or structures. Thus, deterministic approach may have possibility for leading to unreasonable and unrealistic failure cause assessment due to ignorance of the uncertainties. Therefore, probabilistic approach is needed to complement the shortcoming of deterministic approach and to perform the more reasonable and realistic failure cause assessment. In this study, reliability-based failure cause assessment (reliability based forensic engineering) is performed, which can incorporate uncertainties in failures and structures. For more practical application, the modified ETA technique is proposed, which automatically generates the defected structural model, performs structural analysis and reliability analysis, and calculates the failure probabilities of the failure events and the occurrence probabilities of the failure scenarios. Also, for more precise reliability analysis, uncertainties are estimated more reasonably by using bayesian approach based on the experimental laboratory testing data in forensic report.

• Journal of Korean Society for Quality Management
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• v.46 no.2
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• pp.327-338
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• 2018

Purpose: A risk evaluation procedure is proposed for common failure causes in FMEA(Failure Mode and Effects Analysis). The conventional FMEA does not provide a proper means to compare common failure causes with other failure causes. This research aims to develop a risk evaluation procedure in FMEA where common failure causes and other failure causes exist together. Methods: For each common failure cause, the effect of each combination of its resulting failures is recommended to be reevaluated considering their interactive worsening effect. And the probability that each combination of failures is incurred by the same common cause is also considered. Based on these two factors, the severity of each common cause is determined. Other procedures are similar to the conventional method. Results: The proposed procedure enables to compare and prioritize every failure cause. Thus, the common causes, each of which incurring two or more failures, and other causes, each of which is corresponding to one failure, can be fairly compared. Conclusion: A fair and proper way of comparing the common failure causes and other causes is provided. The procedure is somewhat complicated and requires more works to do. But it is worth to do.

• Journal of Korean Society of Water and Wastewater
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• v.10 no.1
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• pp.96-111
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• 1996

The failure of water pipelines is progressed by several compound factors and the collection and analysis of data about pipeline failure are inevitable for effective pipeline rehabilitation. Data analysis of pipeline failure was already performed in USA and Europe. Based on such phenomena, failure characteristics about metropolitan pipelines in Korea were analyzed: The conclusions of this study are as followings. 1. The failure cause of pipelines can be classified into natural cause and artificial cause. Artificial cause is 32% of total causes, so artificial failure as several constructions happens frequently in Korea. Although the failure by old pipe is greatest of any other causes m classtfied cause, failure cause is not classified in detail now. 2. The damaged part of pipelines is affected by cities, distribution system inventory, bedding conditions, and so on. In this study, the failure of pipeline body(67%) is greater than the failure of pipeline joint(33%) in natural failure. 3. In regard to pipe materials, failure rate of DCIP(0.8456), PEP(0.7288), and GSP(0.6643) is greater than that of CIP(0.3985) and CWSP(0.2348). 4. Usually, faIlure rate is increased in proportion to diameter of pipeline. In this study, CIP, DCIP, and CWSP have clear trends. But the trends of PEP is reverse, the case of GSP, HP is obscure due to data shortage. 5. There are no direct relationships between burial age and failure rate of pipelines. 6. Annual breaks and winter(Nov.~Feb.) breaks of pipelines are investigated. As a result, WInter breaks to annual breaks of CIP is 51.3%(Seoul), 51.1%(Taegu),38.7%(Pusan). This phenomena have direct correlation with average winter temp. of cities.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.749-757
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• 2007

Recently, with increasing interested in improvement of operational reliability and the systematic maintenance activities, the RCM analysis has been applied and tried to lots of applicable industries. This study covers applying the probability of failure cause to FMEA, and proposes an analytical method for this. Also, the measures of quantitative classification for the result of failure cause probability are addressed. Based on the field data, this thesis presents an identification for causes and characteristics of failure, and reviews them periodically from the above methodologies. As using FMEA applied the probability of failure cause, we in the future can look forward to improvement of efficiency for failure diagnosis & inspection, and reliability.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.2
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• pp.143-148
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• 2013

In FMEA, occurrence and detectability are not related to only failure modes itself but also their causes. It is assumed that any failure occurs after at least one cause corresponding to failure occurs in advance. Occurrence of the failure mode is described by occurrence time of its cause and elapsed time to the actual failure. Under the periodic monitoring plan, the monitoring interval is another factor to determine the detectability and occurrence of each failure mode. When a failure cause occurs, the failure does not occur if the cause is identified and remedied before it actually occurs. Under this situation, we construct an economic model for prioritizing failure modes. The loss function is based on the unfulfilled mission period. We also provide an optimal monitoring plan with an illustrative example.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.255-262
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• 2008

The railway is required to be highly reliable, which carries a lot of passenger and baggage. Presently, the reliability prediction method is based on independent failure. If the common cause failure affecting many components simultaneously in a system occurs, the system has seriously an aptitude to be broken out. Therefore, for raising the reliability of the railway power system, it is introduced that the analysis is conducted to use the common cause failure. The common cause failure is modeled and is combined with independent failure. Furthermore in order to examine the method, it is applied to the railway power substation. If this method is used to the power system, the reliability of the railway power system will be highly improved.

• Journal of the Korean Society of Hazard Mitigation
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• v.4 no.3 s.14
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• pp.25-31
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• 2004

Rail road slope can be fatted because of existence of unexpected soft subsoil. Purpose of this study is verifying the cause of rail road slope failure and determination of soil strength for remedy. Drilling some boreholes, cone penetration test and field vane test were executed in order to find out the cause of slope failure. In addition, laboratory test was conducted in order to determine soil strength of soft soil sampled as undisturbed state. As a result of both the in-situ and the laboratory tests, the cause of slope failure is thought to be propagation of failure zone by progressive rupture of overconsolidated clay Soft soil strength was determined through back analysis of the failed slope.

• IE interfaces
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• v.25 no.4
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• pp.382-392
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• 2012

Reactor protection system to keep nuclear safety and operational economy of plants requires high reliability. Such a high reliability of the system can be achieved through the redundant design of components. However, common cause failures of components reduce the benefits of redundant design. Thus, the common cause failure analysis, to accurately calculate the reliability of the reactor protection system, is carried out using alpha-factor model. Analysis results to 24 operating months are that 1) the system reliability satisfies the reliability goal of EPRI-URD and 2) the common cause failure contributes 90% of the system unreliability. The uncertainty analysis using alpha factor parameters of 0.05 and 0.95 quantile values shows significantly large difference in the system unreliability.