• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2004.05a
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• pp.370-373
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• 2004

The inside and outside of the country utilities considered that they focused energy and economic aspect for short-term in new environment change of restructure. but it need service reliability preservation and improvement countermeasure, that is no to use existent estimation method for reliability preservation. therefore, analyze the equipment failure rate for suitable reliability preservation through equipment failure rate analysis of power distribution r system and evaluated equipment that is composing power distribution system by the failure rate. This paper estimated failure causes and the TVFR(Time Varying Failure Rate) for main equipment that is composing power distribution system using Weibull distribution.

• Journal of Korean Society for Quality Management
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• v.25 no.3
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• pp.51-61
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• 1997

We introduce a method of estimating an unknown failure rate function based on sample data. We estimate failure rate function by a function s from a space of cubic splines constrained to be linear (or constant) in tails using maximum likelihood estimation. The number of knots are determined by Bayesian Information Criterion(BIC). Examples using simulated data are used to illustrate the performance of this method.

• Journal of Korean Society for Quality Management
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• v.25 no.4
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• pp.71-78
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• 1997

In this paper, we consider a hierarchical Bayes estimation of the parameter, the reliability and failure rate functions based on type-II censored samples from a Burr type-？ failure time model. The Gibbs sampler a, pp.oach brings considerable conceptual and computational simplicity to the calculation of the posterior marginals and reliability. A numerical study is provided.

• Journal of Korean Institute of Industrial Engineers
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• v.29 no.2
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• pp.145-149
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• 2003

We consider the estimation of failure rate and acceleration factor under type-I censoring without using acceleration model when testing is conducted in only one highly accelerated condition. Failure times of an item are assumed to be exponentially distributed. It is also assumed that the uncertainty about the acceleration factor, the failure time contraction ratio between accelerated condition and use condition, can be modeled by the uniform or gamma prior distribution of appropriate parameters. We respectively use Bayes and maximum likelihood approaches to estimate acceleration factor and failure rate in the use condition. An example is given to show how the method can be applied.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.66 no.1
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• pp.33-37
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• 2017

This paper describes the modeling of the failure rate estimation technique for applying the asset management technique to electric power facilities. There are many modeling techniques to estimate the failure rate. In this paper, the characteristics of the normal distribution, exponential distribution, weibull distribution, and piecewise linear functions are discussed. When evaluating reliability, the evaluation may be less meaningful if the sample data is insufficient. Therefore, Weibull distribution and piecewise linear function are adopted as the most suitable functions for estimating the failure rate of power facilities and the resulting failure rate function is derived.

• Nuclear Engineering and Technology
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• v.44 no.4
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• pp.405-414
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• 2012

In this paper, we propose a reliability estimation method for DI&C systems. At the system level, a fault tree model is suggested and Boolean algebra is used to obtain the minimal cut sets. At the component level, an exponential distribution is used to model hardware failures, and Bayesian estimation is suggested to estimate the failure rate. Additionally, a binomial distribution is used to model software failures, and a recently developed software reliability estimation method is suggested to estimate the software failure rate. The overall system reliability is then estimated based on minimal cut sets, hardware failure rates and software failure rates.

• Journal of the Korea Concrete Institute
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• v.18 no.2 s.92
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• pp.233-238
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• 2006

In lifetime estimation, the FEM analysis method is proposed for predicting corrosion failure time of concrete structures exposed to sea-water. This study shows that the corrosion rate of rebar in artificial pore solution can be transferred to the corrosion rate of rebar in concrete using the relationship between pore volume and concrete volume by Jennings' model. And this study considered the pitting corrosion effects of reinforcement bar on corrosion failure analysis, rebar size to cover depth and nonlinear crack analysis. These analysis results have good accordance with the experimental results of Williamson's work. This methodology can be applied to lifetime prediction procedure of reinforced concrete structures and also gives more reasonable results of concrete cover failure time estimation of reinforced concrete structures exposed to sea-water.

• International Journal of Precision Engineering and Manufacturing
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• v.4 no.6
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• pp.12-19
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• 2003

This paper presents the effect of boundary conditions in various failure pressure models published for the estimation of failure pressure. Furthermore, this approach is extended to the failure prediction with the aid of a failure probability model. The first order Taylor series expansion of the limit state function is used in order to estimate the probability of failure associated with each corrosion defect in buried pipelines for long exposure period with unit of years. A failure probability model based on the von-Mises failure criterion is adapted. The log-normal and standard normal probability functions for varying random variables are adapted. The effects of random variables such as defect depth, pipe diameter, defect length, fluid pressure, corrosion rate, material yield stress, material ultimate tensile strength and pipe thickness on the failure probability of the buried pipelines are systematically investigated for the corrosion pipeline by using an adapted failure probability model and varying failure pressure model.

• Journal of applied mathematics & informatics
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• v.9 no.2
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• pp.761-769
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• 2002

Due to the large scale application of software systems, software reliability plays an important role in software developments. In this paper, a software reliability growth model (SRGM) is proposed. The testing time on the right is truncated in this model. The instantaneous failure rate, mean-value function, error detection rate, reliability of the software, estimation of parameters and the simple applications of this model are discussed .

• Journal of the Korean Data and Information Science Society
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• v.9 no.2
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• pp.227-235
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• 1998

In this paper, we consider a hierarchical Bayes estimation of the parameter, the reliability and hazard rate function based on type-II censored samples from a Rayleigh failure model. Bayes calculations can be implemented easily by means of the Gibbs sampler. A numerical study is provided.