• 품질경영학회지
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• 제21권2호
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• pp.109-120
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• 1993

Most systems are composed of components which have different failure chracteristics. Since the failure characteristics of components is different, it is rational and reasonable to establish a maintenance model to be considered repair and replacement policies which are proper to failure characteristics of these components. This paper proposes the age replacement time for a system composed of components which have different failure characteristics. In this model, it is assumed that a system is composed of a critical failure component, a major failure component, minor failure component. If any failure occurs to critical component before its age replacement time, the system should be replaced. If any failure does not occur until its age replacement time, preventive replacement should be performed at age replacement time T. Major component is minimal repaired if any failure occurs during operation. Minor component should be replaced as soon as failure is found. This paper determines the optimal replacement time of the system which minimize, total maintenance cost and initial stock Quantity of minor component within this optimal replacement time. Numerical example illustrates these results.

• 한국환경과학회지
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• 제17권11호
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• pp.1281-1293
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• 2008

This study aims at the estimation of dam failure time and dam failure scenario analysis of and applied to Yeoncheon Dam which was collapsed August 1st 1999, using HEC-HMS, DAMBRK-FLDWAV simulation model. As the result of the rainfall-runoff simulation, the lancet flood amount of the Yeoncheon Dam site was $10,324\;m^3/sec$ and the total outflow was $1,263.90\;million\;m^3$. For the dam failure time estimation, 13 scenarios were assumed including dam failure duration time and starting time, which reviewed to the runoff results. The simulation time was established with 30 minutes intervals between one o'clock to 4 o'clock in the morning on August 1, 1999 for the setup standard for each case of the dam failure time estimation, considering the arrival time of the flood, when the actually measured water level was sharply raising at Jeongok station area of the Yeoncheon Dam downstream, As results, dam failure arrival time could be estimated at 02:45 a.m., August 1st 1999 and duration time could be also 30 minutes. Those results and procedure could suggest how and when dam failure occurs and analyzes.

• Journal of the Korean Data and Information Science Society
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• 제14권4호
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• pp.997-1005
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• 2003

In this paper, the problem of determining optimal burn-in time is considered under a general failure model. There are two types of failure in the general failure model. One is Type I failure (minor failure) which can be removed by a minimal repair and the other is Type II failure (catastrophic failure) which can be removed only by a complete repair. In this model, when the unit fails at its age t, Type I failure occurs with probability 1 - p(t) and Type II failure occurs with probability p(t), $0{\leq}p(t)\leq1$. Under the model, the properties of optimal burn-in time maximizing mean time to the catastrophic failure during field operation are obtained. The obtained results are also applied to some illustrative examples.

• 산업경영시스템학회지
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• 제43권2호
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• pp.33-38
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• 2020

Anomaly detection of Machine Learning such as PCA anomaly detection and CNN image classification has been focused on cross-sectional data. In this paper, two approaches has been suggested to apply ML techniques for identifying the failure time of big time series data. PCA anomaly detection to identify time rows as normal or abnormal was suggested by converting subjects identification problem to time domain. CNN image classification was suggested to identify the failure time by re-structuring of time series data, which computed the correlation matrix of one minute data and converted to tiff image format. Also, LASSO, one of feature selection methods, was applied to select the most affecting variables which could identify the failure status. For the empirical study, time series data was collected in seconds from a power generator of 214 components for 25 minutes including 20 minutes before the failure time. The failure time was predicted and detected 9 minutes 17 seconds before the failure time by PCA anomaly detection, but was not detected by the combination of LASSO and PCA because the target variable was binary variable which was assigned on the base of the failure time. CNN image classification with the train data of 10 normal status image and 5 failure status images detected just one minute before.

• 한국복합재료학회:학술대회논문집
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• 한국복합재료학회 2000년도 추계학술발표대회 논문집
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• pp.128-133
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• 2000

The objective of this research is to develop real-time failure detection techniques for damage assessment of composite materials using optical fiber sensors. Signals from matrix cracking or fiber fracture in composite laminates are treated by signal processing unit in real-time. This paper describes the implementation of time-frequency analysis such as the Short Time Fourier Transform(STFT) to determine the time of occurrence of failure. In order to verify the performance of the optical fiber sensor for stress wave detection, we performed pencil break test with EFPI sensor and compared it with that of PZT. The EFPI sensor was embedded in composite beam to sense the failure signals and a tensile test was performed. The signals of the fiber optic sensor when damage occurred were characterized using STFT and wavelet transform. Failure detection system detected the moment of failure accurately and showed good sensitivity with the infinitesimal failure signal.

• 대한산업공학회지
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• 제21권4호
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• pp.507-517
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• 1995

The failure rate of an item depends on operational environment. When an item has a chance failure period and a wearout failure period in sequel, the severity of operational environment causes the increase in the slop of wearout failure rate or the increase in the magnitude of chance failure rate. For such a change of operational environment, this paper concerns the change of optimal preventive replacement time. Two preventive replacement policies, age replacement policy and periodic replacement policy with minimal repair, are considered. Investigated properties are: (a) in age replacement policy, optimal preventive replacement time increases as the chance failure rate increases and optimal preventive replacement time decreases as the slope of wearout failure rate increases, and (b) in periodic replacement policy with minimal repair, optimal preventive replacement time increases as the slope of wearout failure rate increases; however, the change of chance failure rate does not alter the optimal preventive replacement time.

• 한국수자원학회논문집
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• 제40권1호
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• pp.39-50
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• 2007

본 논문에서는 대수-선형 파손율 모형(log-linear ROCOF)과 와이블 파솔율 모형(Weibull ROCOF)을 이용하여 상수도 주철 배수관로의 파손율을 모형화하고, '수정된 시간 척도'를 이용하여 최적교체시기를 산정할 수 있는 방법이 개발되었다. 두 ROCOF의 모형화를 위하여 개별 관로의 파손시간을 기록한 '파손 시간자료(failure-time data)'와 일정 시간간격 사이에서 발생하는 파손횟수를 기록한 '파손 횟수자료(failure-number data)'를 이용하였고, 최대로그우도 추정값을 이용하여 두 ROCOF의 각 파손자료 유형에 대한 모형화 수행 능력을 검증하였다. 또한 두 ROCOF를 이용한 관로의 최적교체시기 방정식은 ROCOF의 매개변수 추정에 있어서 수렴성을 보장하기 위하여 '수정된 시간 척도'를 적용하여 유도하였다. 연구대상 주철 배수 관로들의 '파손 시간자료'와 '파손 횟수자료'에 두 파손율 모형을 적용시켜 본 결과 파손 시간자료를 이용할 경우 대수-선형 ROCOF가 와이블 ROCOF 보다 적합한 모형인 것으로 나타났다. 또한 두 모형 모두 '파손 시간자료'를 이용하는 것이 '파손 횟수자료'를 이용하는 것보다 모형화 수행 능력이 높아지는 것으로 나타나서, 분석에 사용된 관로의 파손율 모형화와 최적교체시기 산정을 위해서는 일정 시간간격 동안의 관로 파손횟수를 기록하는 것보다 관로의 파손시간을 기록하는 것이 더욱 우수한 모형화 결과를 낳는 것으로 나타났다.

• 품질경영학회지
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• 제18권2호
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• pp.33-42
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• 1990

This paper proposes the maintenance model of multi-component system when the failure characteristics and types of components are considered. In this model, it is assumed that a system is composed of a critical component, a major component and a minor component. Also, failure types is classified into major failure and minor failure. If major failure occurs to critical component before system age replacement time, the system is renewed. If major failure does not occur until its age replacement time, preventive maintenance is performed at age replacement time T. Minimal repairs are carried out after each minor failure. Major component is minimal-repaired if any failure is discovered during operation. Minor component should be replaced as soon as any failure is found. This paper determines the optimal replacement time of the system which minimizes total maintenance cost. Numerical example illustrates these results.

• 융합보안논문지
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• 제8권2호
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• pp.35-40
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• 2008

소트프웨어 고장 시간은 테스팅 시간과 관계없이 일정하거나, 단조 증가 혹은 단조 감소 추세를 가지고 있다. 이러한 소프트웨어 신뢰모형들을 분석하기 위한 자료척도로 자료에 대한 추세 검정이 개발되어 있다. 추세 분석에는 산술평균 검정과 라플라스 추세 검정 등이 있다. 추세분석들은 전체적인 자료의 개요의 정보만 제공한다. 본 논문에서는 고장시간을 측정하다가 시간절단이 될 경우에 미래의 고장 시간 예측에 관하여 연구되었다. 고장 시간 예측에 사용된 고장시간자료는 소프트웨어 고장 시간 분포에 널리 사용되는 와이블 분포에서 형상모수가 1이고 척도모수가 0.5를 가진 난수를 발생된 모의 자료를 이용 하였다. 이 자료를 이용하여 시계열 분석에 이용되는 ARIMA 모형 중에서 AR(1) 모형과 모의실험을 통한 예측 방법을 제안하였다. 이 방법에서 ARIMA 모형을 이용한 예측방법이 효율적임을 입증 하였다.

• 한국신뢰성학회:학술대회논문집
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• 한국신뢰성학회 2000년도 추계학술대회
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• pp.387-395
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• 2000

Circular consecutive-k-out-of-n:F system when the failure of component is dependent is studied. We assume that the failure of a component in the system increase the failure rate of the survivor which is working just before the failed component. In this case, a mean time to failure (MTTF), a average failure number of the system, and the expected cost per unit time are obtained. Then the minimum number of consecutive failed components to cause system failure to minimize the expected cost per unit time is determined as searching paths to system failure. And various numerical examples are studied.