• 경영과학
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• 제11권2호
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• pp.1-27
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• 1994

A reliability data processing MPRDP (Multi-Purpose Reliability Data Processor) has been developed in FORTRAN language since Jan. 1992 at KAERI (Korean Atomic Energy Research Institute). The purpose of the research is to construct a reliability database(plant-specific as well as generic) by processing various kinds of reliability data in most objective and systematic fashion. To account for generic estimates in various compendia as well as generic plants' operating experience, we developed a 'three-stage' Bayesian procedure[1] by logically combining the 'two-stage' procedure[2] and the idea for processing generic estimates[3]. The first stage manipulates generic plant data to determine a set of estimates for generic parameters,e.g. the mean and the error factor, which accordingly defines a generic failure rate distribution. Then the second stage combines these estimates with the other ones proposed by various generic compendia (we call these generic book type data). This stage adopts another Bayesian procedure to determine the final generic failure rate distribution which is to be used as a priori distribution in the third stage. Then the third stage updates the generic distribution by plant-specific data resulting in a posterior failure rate distribution. Both running failure and demand failure data can be handled in this code. In accordance with the growing needs for a consistent and well-structured reliability database, we constructed a generic reliability database by the MPRDP code[4]. About 30 generic data sources were reviewed and available data were collected and screened from them. We processed reliability data for about 100 safety related components frequently modeled in PSA. The underlying distribution for the failure rate was assumed to be lognormal or gamma, according to the PSA convention. The dependencies among the generic sources were not considered at this time. This problem will be approached in further study.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 1999년도 가을 학술발표회 논문집
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• pp.147-152
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• 1999

Distribution of fracture system is an important factor to analyse instability of jointed rock slope. In the most case of rock slopes, joint distribution properties are related to potential, shape, size and locality of slope failure. The purpose of this paper is to present an application of fracture characterization related to rock slope failure. Fracture data used in this study are collected by scanline survey. Two aspects of fracture characterization for rock slope are handled in this study First, In order to determine the potential and shape of slope failure, trace length of joints is considered as the weighting factor about collected orientation data. Second, Relationship between trace length and spacing is analysed to estimate failure location and size. The distribution of fracture system is directly influenced on wedge failure. It is effective to analyse the orientation of fractures by using weighting factors associated with the trace length of fractures rather than to analyse only that of fractures. It gives a conclusion that the wedge failure occurred along the peak of fracture density(or intensity) cycles.

• International Journal of Reliability and Applications
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• 제7권1호
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• pp.41-53
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• 2006

The exact cause of the system's failure is often unknown in the masked system lifetime data. In such type of data, there are two observable quantities, namely (i) the systems time to failure and (ii) the set of systems components that contains the component, which might cause the system to fail. Our objective in this paper is to use the maximum likelihood procedure in the presence of masked data to make inference for the reliability of the system's components. We assume a multi-component series system where each component has a constant failure rate. Different cases that permit for closed form solutions of point estimates are considered. The results obtained in this paper generalize other published results.

• 한국산학기술학회논문지
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• 제21권7호
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• pp.428-434
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• 2020

일회성 무기체계는 대기 상태로 있다가 단 한 번의 임무를 수행한 이 후 폐기되는 특성에 따라 높은 신뢰도를 요구받는다. 유도탄은 일회성 무기체계로써 특성상 저장 상태로 수명의 대부분을 보내고, 임무수행을 위한 운용시간은 짧기때문에 임무성공률이 아닌 저장 신뢰도로 분석해야 한다. 유도탄의 신뢰도를 분석할 때에 어떠한 방법을 사용하는지에 따라 그 결과는 달라질 수 있으며, 고장자료와 함께 포함되는 우측 관측중단자료의 비율에 따라서도 차이가 발생할 수 있다. 본 연구는 공군의 OO유도탄을 대상으로 미래의 고장률을 보다 정확하게 예측하기 위한 방법을 제시하고자 작성하였다. 제시하는 방법은 먼저 평균 고장시간(MTTF: Mean Time To Failure, 이하 MTTF)을 적용한 모델과 고장 간 평균시간(MTBF: Mean Time Between Failure, 이하 MTBF)을 적용한 모델로 고장률을 예측하고, 두 모델 중 실제 고장률과 차이가 작은 모델을 선택한다. 선택한 모델로 고장자료와 함께 포함되는 우측 관측중단자료의 비율을 달리하여 고장률을 예측하고, 실제 고장률과의 차이가 최소화되는 비율을 찾는다. 실제 자료를 바탕으로 제안한 비율과 현재 검사 비율의 비교를 통해 제안한 비율이 미래 고장률을 예측하기에 더 적합함을 보였다.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2011년도 정기총회 및 추계학술대회 논문집
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• pp.717-723
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• 2011

When the Balise(the device to transmit information between the on-board equipment and the wayside equipment) failure occurs, it may not be able to transmit data(Telegram) required for the train running. And in some cases, it may be able to cause an accident. Therefore, both the Balise failure affecting train safety running and the hazard in accordance with Balise failure require some activities to establish them. General failure mode & hazard analysis associated with the Balise are described in UNISIG SUBSET-036 spec & UNISIG SUBSET-088 spec. And, with reference to these specifications, safety activities are being performed. In recent domestic railway, the train control system applying ETCS(European Train Control System) Level 1, 2 is being serviced and is being planned, and as part of this system, the Balise is being applied. The design-method of the Balise device for each manufacturer are different, therefore the Balise failure mode & failure rate are different, either. But the functionalities & transmission-data format(Telegram) of the Balise in ETCS Level 1, 2 application for each manufacturer are identical. Accordingly, the hazard caused by function-fail can be identical, either. In order to establish these hazard, in this paper, we analyzed the detailed functions of the Balise. And we analyzed the Balise failure types & failure effects in accordance with the detailed functions.

• Nuclear Engineering and Technology
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• 제55권5호
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• pp.1616-1629
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• 2023

To quantify the conservatism of existing ASME strain-based evaluation methods for seismic loading, this paper presents very low cycle fatigue test data of elbows under various cyclic loading conditions and comparison of evaluation results with experimental failure cycles. For strain-based evaluation methods, the method presented in ASME BPVC CC N-900 and Sec. VIII are used. Predicted failure cycles are compared with experimental failure cycle to quantify the conservatism of evaluation methods. All methods give very conservative failure cycles. The CC N-900 method is the most conservative and prediction results are only ~0.5% of experimental data. For Sec. VIII method, the use of the option using code tensile properties gives ~3% of experimental data, and the use of the material-specific reduction of area can reduce conservatism but still gives ~15% of experimental data.

• 대한전기학회논문지:전력기술부문A
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• 제52권7호
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• pp.401-406
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• 2003

Electric power industries in several countries are currently undergoing major changes, mainly represented by the privatizations of the power plants and distribution systems. Reliable operations of the power plants directly contribute to the revenue increases of the generation companies in such competitive environments. Strategic optimizations should be performed between the levels of the reliabilities to be maintained and the various preventive maintenance costs, which require the accurate estimations of the power plant reliabilities. However, accurate estimations of the power plant reliabilities are often limited by the lack of accurate power plant failure data. A power plant is not supposed to be failed that often. And if it fails, its impact upon the power system stability is quite substantial in most cases, setting aside the significant revenue losses and lowered company images. Reliability assessment is also important for Independent System Operators(ISO) or Market Operators to properly assess the level of needed compensations for the installed capacity based on the availability of the generation plants. In this paper, we present a power plant reliability estimation technique that can be applied when the failure data is insufficient. Median rank and Weibull distribution are used to accommodate such insufficiency. The Median rank is utilized to derive the cumulative failure probability for each ordered failure. The Weibull distribution is used because of its flexibility of accommodating several different distribution types based on the shape parameter values. The proposed method is applied to small size failure data and its application potential is demonstrated.

• 한국신뢰성학회지:신뢰성응용연구
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• 제16권2호
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• pp.98-103
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• 2016

Purpose: The purpose of this paper is to get a meaningful information for improving manufacturing quality of the products before they are produced in client's manufacturing process. Methods: A variety of data mining techniques have been being used for wide range of industries from process data in manufacturing factories for quality improvement. One application of those is to get meaningful information from process data in manufacturing factories for quality improvement. In this paper, the failure rate at client's manufacturing process is predicted by using the parameters of the characteristics of the product based on PCA (Principle Component Analysis) and regression analysis. Results: Through a case study, we proposed the predicting methodology and regression model. The proposed model is verified through comparing the failure rates of actual data and the estimated value. Conclusion: This study can provide the guidance for predicting the failure rate on the manufacturing process. And the manufacturers can prevent the defects by confirming the factor which affects the failure rate.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2009년도 춘계학술대회 논문집
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• pp.495-504
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• 2009

As the Reliability Centered Maintenance(RCM) is being studied, maintenance tasks can be performed effectively through the Risk Priority Number(RPN) evaluation about the components in the system. The RPN is usually calculated through arithmetical operations of three values, Severity, Occurrence, and Detection for each facility. This RPN provides information that includes risk level of the facility and the priority order of maintenance tasks for facility. However, if there is no sufficient historical failure data, it is difficult to calculate the RPN. In this case, historical failure data from other sources can be used and apply this data to korean railway system. In this paper, it is proposed that a new methodology to model the failure rate as a fuzzy membership function. This method is based on failure data from other sources by means of the fuzzy theory and the expert opinion system. And considering assessment tendency of each expert, distortions that happened when the failure rate of facilities is estimated were minimized. This results determine Occurrence values of facilities. Taking advantage of this result., the RPN can be calculated with Severity and Detection of facilities by using the fuzzy operation. The proposed method is applied the rail-way power substation.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2005년도 춘계공동학술대회 발표논문
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• pp.678-685
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• 2005

Estimating parameters of the lifetime distribution is investigated when field failure data are not completely reported. To take into account the reality and the accuracy of the estimates in such a case, the failure reporting probability is incorporated in estimating parameters. Firstly, method of maximum likelihood estimate(MLE) is used to estimate parameters of the lifetime distribution when failure reporting probability is known. Secondly, Expectation and Maximization(EM) algorithm is used to estimate the failure reporting probability and parameters of the lifetime distribution simultaneously when failure reporting probability is unknown. For both case, procedures of estimation are illustrated for single Weibull distribution and mixed Weibull distribution. Simulation results show that MLE obtained by the proposed method is more accurate than the conventional MLE.