• 한국신뢰성학회지:신뢰성응용연구
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• 제10권2호
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• pp.93-105
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• 2010

The following thesis provides an explanation for the definition of the MIL-HDBK-2155 : Failure Reporting, Analysis and Corrective Action System (FRACAS), which systemizes the collection and analysis of failure data and the feedback process of the results. It also presents a plan based on MIL-HDBK-2155 for the collection and analysis of operating specifications on weapon systems. The collection and analysis of failure data and the feedback process utilizing FRACAS contributes to identifying improvement requirements during equipment operation as well as finding and eliminating the root cause of the failures. The objective of applying FRACAS to weapon systems is to receive source data feedback for reliability enhancements and performance improvements during operation. This is done by recognizing weaknesses in the design or operation by identifying the type of failures that might occur, and by performing Failure Modes, Effects and Criticality Analysis(FMECA) and Failure Tree Analysis(FTA).

• 대한안전경영과학회지
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• 제3권4호
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• pp.65-76
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• 2001

Field data have been recorded as the time to failure or the number of failure of systems. We consider the time to failure and covariate variables in some pre-specified follow-up or warranty period. This paper aims to investigate study on the reliability estimation when some additional field data can be collected within-warranty period or after-warranty period. A various likelihood-based methods are outlined and examined for exponential or Weibull distribution.

• Nuclear Engineering and Technology
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• 제39권2호
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• pp.129-132
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• 2007

It is generally known that software reliability growth models such as the Jelinski-Moranda model and the Goel-Okumoto's non-homogeneous Poisson process (NHPP) model cannot be applied to safety-critical software due to a lack of software failure data. In this paper, by applying two of the most widely known software reliability growth models to sample software failure data, we demonstrate the possibility of using the software reliability growth models to prove the high reliability of safety-critical software. The high sensitivity of a piece of software's reliability to software failure data, as well as a lack of sufficient software failure data, is also identified as a possible limitation when applying the software reliability growth models to safety-critical software.

• 한국IT서비스학회지
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• 제7권2호
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• pp.181-195
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• 2008

The rapid growth of mobile communication technology has provided the expansion of mobile internet services, particularly mobile realtime transaction takes much weight among mobile fields. There is an increasing demand for various mobile applications to process transactions in a mobile computing fields. Thus, During transmission in wireless networks a base station failure inevitably causes data loss of the base station buffer. It is required to compensate the loss for communication. The existing methods for a base station failure are not adequate because they all suffer from too much overhead and resolve only the link failure. In this paper, we study an efficient recovry systems for a mobile DBMS. We propose SLL (Segment Log List) that enables the mobile host to compensate data loss efficiently in the case of base station failure. In SLL, a base station deliveries an output information of data cells to a mobile host. when a base station fails, the mobile host can retransmit just next data cells. We also prove the efficiency of new method.

• Journal of the Korean Data and Information Science Society
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• 제20권3호
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• pp.467-474
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• 2009

시스템의 한 부품이 고장 나면 고장 난 부품이 분담하던 부하가 고장 나지 않은 다른 부품에 전가되어 다른 부품의 고장률에 영향을 주는 부하분배시스템에 대한 연구가 신뢰성 공학과 생물의학 분야에서 다양하게 이루어져왔다. 본 연구에서는 최소수명을 보증하는 부하분배체계의 체계단위수명 시험에서 부품의 수명관측이 불가능하며 체계의 수명관측이 가능한 경우에, 중도절단된 체계 고장데이터를 이용하여 부하분배체계의 평균수명과 체계 신뢰도의 최우추정치와 추정오차를 줄일 수 있는 수정된 최우추정치를 구하고 컴퓨터 모의실험을 통하여 그 성능을 비교한다.

• 한국신뢰성학회지:신뢰성응용연구
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• 제3권2호
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• pp.93-101
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• 2003

Life time data analysis requires some time-to-failure data to an extent. Some life tests result in few or no failure. In such cases, it is difficult to access reliability with traditional life tests that record only time to failure. Furthermore, with short product development time, reliability tests must be conducted with severe time constraints. For some devices, it is possible to obtain degradation measurements over time, and these measurements may contain useful information about product reliability. This article describes degradation reliability analysis methods to do inferences and predictions about a failure-time distribution by using software. In addition, the possibility of extension to CBM (Condition Based Maintenance) is suggested as an example of applied degradation data analysis.

• Communications for Statistical Applications and Methods
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• 제29권4호
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• pp.403-411
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• 2022

This article presents an independence test between pairs of interval censored failure times. The Mantel-Haenszel test is commonly applied to test the independence between two categorical variables accompanied with a strata variable. Hsu and Prentice (1996) applied a Mantel-Haenszel test to the sequence of 2 × 2 tables formed at the grids which are composed of failure times. In this article, due to unknown failure times, the suitable grid points should be determined and the status of failure and at risk are estimated at those grid points. We also consider a weighted test statistic to bring a more powerful test. Simulation studies are performed to evaluate the power of test statistics under finite samples. The method is applied to analyze two real data sets, mastitis data from milk cows and an age-related eye disease study.

• 응용통계연구
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• 제8권1호
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• pp.89-104
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• 1995

사용현장에서의 고장데이터는 미리 정해진 보증기간동안 고장이 발생한 제품으로부터 얻어지는 고장시간, 고장원인, 설명변수값과 보증기간동안 고장나지 않는 제품 중 일정비율을 추적조사하여 얻은 설명변수 값들로 구성된다. 사용현장에서 얻어지는 이와 같은 데이터를 이용하여 제품수명분포의 모수가 설명변수와 대수선형관계일 때, 수명분포의 모수에 대한 의사(pseudo) 최우추정량을 구하고 그 점근성질을 규명하였으며, 고장원인별 제품수명이 와이블분포를 따를 때의 의사최우추정량과 점근분산을 구하였다. 제품의 보증기간이 달력시간이고 제품의 고장이 운영시간에 의존하는 경우와 제품의 보증이 달력시간과 운영시간의 혼합인 경우의 분석방법도 제시하였다. 또한 모의 실험을 통하여 추적조사비율에 따른 효과를 알아보았다.

• Geomechanics and Engineering
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• 제28권4호
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• pp.335-346
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• 2022

Buckling failure is a typical slope instability mode that should be paid more attention to. It is difficult to provide systematic guidance for the monitoring and management of such slopes due to unclear mechanism. Here we examine buckling failure as the potential instability mode for a slope above a railway tunnel in southwest China. A comprehensive model test system was developed that can be used to conduct buckling failure experiments. The displacement, stress, and strain of the slope were monitored to document the evolution of buckling failure during the experiment. Monitoring data reveal the deformation and stress characteristics of the slope with different slipping mass thicknesses and under different top loads. The test results show that the slipping mass is the main subject of the top load and is the key object of monitoring. Displacement and stress precede buckling failure, so maybe useful predictors of impending failure. However, the response of the stress variation is earlier than displacement variation during the failure process. It is also necessary to monitor the bedrock near the slip face because its stress evolution plays an important role in the early prediction of instability. The position near the slope foot is most prone to buckling failure, so it should be closely monitored.

• Geomechanics and Engineering
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• 제23권1호
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• pp.51-59
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• 2020

In this paper, the WEKA platform was used to mine and analyze measured data of floor failure depth and a prediction system of floor failure depth was developed with Java. Based on the standardization and discretization of 35-set measured data of floor failure depth in China, the grey correlation degree analysis on five factors affecting the floor failure depth was carried out. The correlation order from big to small is: mining depth, working face length, floor failure resistance, mining thickness, dip angle of coal seams. Naive Bayes model, neural network model and decision tree model were used for learning and training, and the accuracy of the confusion matrix, detailed accuracy and node error rate were analyzed. Finally, artificial neural network was concluded to be the optimal model. Based on Java language, a prediction system of floor failure depth was developed. With the easy operation in the system, the prediction from measured data and error analyses were performed for nine sets of data. The results show that the WEKA prediction formula has the smallest relative error and the best prediction effect. Besides, the applicability of WEKA prediction formula was analyzed. The results show that WEKA prediction has a better applicability under the coal seam mining depth of 110 m~550 m, dip angle of coal seams of 0°~15° and working face length of 30 m~135 m.