• Journal of the Korean Geotechnical Society
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• v.29 no.5
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• pp.65-74
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• 2013

The natural disaster occurrences and the loss of lives caused by the steep-slope failures in Korea were investigated in this study. The investigation includes the frequency rate of the steep-slope failures with respect to the characteristics of precipitation, underlying bedrock, and weathered soils. Analysis on the problems in the existing estimation methods of steep-slope failure was also undertaken, and a new model using unsaturated infinite slope stability was developed for the better slope failure estimation. The slope analyses by the newly developed model were performed considering unsaturated infinite slope, the gradient of slope, and hydro/mechanical properties of soils. Steep-slope failure estimation criterion is proposed based on the analysis results. In addition, the precipitation amount corresponding to warning stages against steep-slope failure is provided as an equation of Intensity-Duration criterion.

• Journal of Applied Reliability
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• v.1 no.1
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• pp.47-54
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• 2001

This paper considers the parameter estimation problem of the failure intensity function and maintenance effect in a repairable system. We propose estimation procedures for repairable systems on which preventive maintenance is performed. The failure process is modeled by a proportional age reduction model [Brown, Mahoney and Sivazlian(1983)] which is useful to model the imperfect effect of preventive maintenance. When failure and maintenance (preventive) times are given, the maximum likelihood method is used to estimate the maintenance effect and the parameters of intensity function, simultaneously We obtain the maximum likelihood estimators using a genetic algorithm. A numerical example is also presented.

• Journal of Mechanical Science and Technology
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• v.19 no.6
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• pp.1280-1289
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• 2005

This paper presents the effects of corrosion environments of failure pressure model for buried pipelines on failure prediction by using a failure probability. The FORM (first order reliability method) is used in order to estimate the failure probability in the buried pipelines with corrosion defects. The effects of varying distribution types of random variables such as normal, lognormal and Weibull distributions on the failure probability of buried pipelines are systematically investigated. It is found that the failure probability for the MB31G model is larger than that for the B31G model. And the failure probability is estimated as the largest for the Weibull distribution and the smallest for the normal distribution. The effect of data scattering in corrosion environments on failure probability is also investigated and it is recognized that the scattering of wall thickness and yield strength of pipeline affects the failure probability significantly. The normalized margin is defined and estimated. Furthermore, the normalized margin is used to predict the failure probability using the fitting lines between failure probability and normalized margin.

• 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 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.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.4
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• pp.212-218
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• 2010

This paper shows accuracy comparison results of reliability estimation methods for one-shot systems with respect to sample sizes. To compare accuracy in reliability estimation methods, quantal-response data, characterizing one-shot systems, were simulated using failure times of LED obtained through the accelerated life test, and then the true reliability over time was evaluated using the failure times. The simulated quantal-response data were used to estimate the true reliability through applying reliability estimation methods in open literature. Accuracy of each reliability estimation method was compared in terms of both SSE (Sum of Squared Error) and MSE (Mean Squared Error), and then estimation trend for each method is found. Feasible bounds which true reliability would exist within were estimated through applying the found trends to quantal-response data set of a real weapon system.

• 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.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.10 no.2
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• pp.41-47
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• 2006

The Renewal process and the Non-homogeneous Poisson process (NHPP) process are probably the most popular models for describing the failure pattern of repairable systems. But both these models are based on too restrictive assumptions on the effect of the repair action. For these reasons, several authors have recently proposed point process models which incorporate both renewal type behavior and time trend. One of these models is the Modulated Power Law Process (MPLP). The Modulated Power Law Process is a suitable model for describing the failure pattern of repairable systems when both renewal-type behavior and time trend are present. In this paper we propose Bayes estimation of the next failure time after the system has experienced some failures, that is, Mean Time Between Failure for the MPLP model. Numerical examples illustrate the estimation procedure.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1557-1560
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• 2003

This paper presents the effect of varying boundary conditions such as ground subsidence on failure prediction of buried pipelines. The first order Taylor series expansion of the limit state function is used in order to estimate the probability of failure associated with three cases of ground subsidence. We estimate the distribution of stresses imposed on the buried pipelines by varying boundary conditions and calculate the probability of pipelines with von-Mises failure criterion. The effects of random variables such as pipe diameter, internal pressure, temperature, settlement width, load for unit length of pipelines, material yield stress and thickness of pipeline on the failure probability of the buried pipelines are also systematically studied by using a failure probability model for the pipeline crossing a ground subsidence region.

• 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.