• Journal of Applied Reliability
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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).

• Journal of the Korea Safety Management & Science
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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.

• Journal of Information Technology Services
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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

There are many situations arising in reliability engineering and biomedical science where failure of a subsystem increases the failure rate of other subsystem under shared load models. In this paper, the maximum likelihood estimates and the modified maximum likelihood estimates of mean time to failure and reliability function for shared load model with guarantee time are obtained by using censored system life data. Some illustrative examples are included.

• Journal of Applied Reliability
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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.

• The Korean Journal of Applied Statistics
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• 제8권1호
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• pp.89-104
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• 1995

This paper is concerned with the method of estimating lifetime distributin from field data for products with multiple modes of failure. When product failures occur within warranty period, a manufacturer can obtain failure-record data; failure times, causes of failure, and covariates. Since these data are seriously incomplete for satisfactory inference, that is, only failures occured during warrantly period may be recorded, it is usually necessary to incoporate the failure-record data by taking a supplementary sample of items obtained following up a portion of products that survive warranty time. The log linear function is considered as a model for describing the relation between failure time of a product and covariates. General methods for obtaining pseudo maximum likelihood estimators(PMLEs) for the parameters are outlined and their asymptotic properties are studied, and specific formulas for exponential or Weibull distribution are obtained. Effects of follow-up percentage on the PMLEs are investigated. Extensions to calendar time warranty or calendar and obtaining time warranty are also considered.

• 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.

• 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.