• Communications for Statistical Applications and Methods
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• v.6 no.1
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• pp.169-180
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• 1999

A Markov Chain Monte Carlo method with development of computation is used to be the software system reliability probability model. For Bayesian estimator considering computational problem and theoretical justification we studies relation Markov Chain with Gibbs sampling. Special case of GOS with Superposition for Goel-Okumoto and Weibull models using Gibbs sampling and Metropolis algorithm considered. In this paper discuss Bayesian computation and model selection using posterior predictive likelihood criterion. We consider in this paper data using method by Cox-Lewis. A numerical example with a simulated data set is given.

• Journal of the Korean Data and Information Science Society
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• v.7 no.2
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• pp.179-188
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• 1996

Accelerated life testing(ALT) of products quickly yields information on life. In this paper, we investigate asymptotic normalities of maximum likelihood(ML) estimators of parameters for ALT model under Type II censored data using results of Bhattacharyya(1985). Further illustrations include the treatment of asymptotic of the exponential and Weibull regression models.

• Proceedings of the Korea Concrete Institute Conference
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• 1997.10a
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• pp.703-708
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• 1997

In this study, the fatigue tests are performed on simply-supported R/C beams strengthened with steel plate and CFS (Carbon fiber sheet). Analysis results by Weibull distribution are compared with the test data. The unknown Weibull distribution parameters are estimated based on observations recorded in fatigue test. Safety factors for the number of cycles and the stress level are obtained. S-N-P curves are also generated from these testes and probabilities of failure.

• Journal of the Korean Statistical Society
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• v.12 no.2
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• pp.69-80
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• 1983

The purpose of this paper is to obtain representation of the mathematical special functions and the numerical values of the mean square errors for the quasi-ranges in random small smaples ($n \leq 30$) from the Weibull distribution with a shape and a scale parameters, and to estimate the scale parameter by use of unbiased estimator based on the quasi-range. It will be shown that the jackknife estimator of the range is worse than the range of random samples from the given distribution in the sense of the mean square error.

• Journal of the Korean Data and Information Science Society
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• v.16 no.2
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• pp.383-389
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• 2005

In this paper, we propose the pure premium rate of reliability insurance policy for radiators under the assumption of Weibull physics of failure. We also describe the performance factors which have an effect on failure characteristics of radiators. The maximum likelihood estimates of scale and shape parameters for assumed distribution are obtained by using accelerated life test data of sample sizes 5 using MINITAB.

• Journal of the Korean Data and Information Science Society
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• v.16 no.2
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• pp.401-410
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• 2005

In this paper, we calculate the premium rate of reliability insurance policy for brake pads for automobiles using real failure data obtained from use-condition. We try process capability analysis for the manufacturing process of brake-system. We describe the performance factors which have an effect on failure characteristics of brake pads. We also obtain the maximum likelihood estimates of shape and scale parameters of the fitted Weibull distribution for brake pads.

• Journal of the Korean Data and Information Science Society
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• v.10 no.1
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• pp.193-198
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• 1999

The estimation of parameters in regression models with multiplicative errors is usually based on the gamma or log-normal likelihoods. Under reciprocal misspecification, we compare the small sample efficiencies of two sets of estimators via a Monte Carlo study. We further consider the case where the errors are a random sample from a Weibull distribution. We compute the asymptotic relative efficiency of quasi-likelihood estimators on the original scale to least squares estimators on the log-transformed scale and perform a Monte Carlo study to compare the small sample performances of quasi-likelihood and least squares estimators.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.20 no.9
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• pp.793-797
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• 2007

In this paper, the long time breakdown characteristic of the epoxy composite, which is widely used in the insulation system for high voltage application, was estimated with Weibull distribution. In the procedure of the estimation, the short time breakdown characteristics for the epoxy composite specimens, which were made with the variation of hardener and/or filler, were tested firstly. Then the long time voltage-to-time test was implemented. Finally, the long time breakdown voltage of each specimen was estimated with the parameters obtained from the statistical treatment with Weibull distribution. Base on the results, it has been found that the optimal weight ratio of epoxy resin/hardener/filler that has the excellent long time breakdown characteristic was 100/100/65. It was due to the silane treatment which relieves the electric field at the interface between filler and epoxy.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.16 no.27
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• pp.121-125
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• 1993

This study deals with the estimation of the Weibull parameters, which have a close relation with product reliability characteristics. Among the many kinds of estimation methods, Kao's Weibull Probability Paper(WPP) is commonly used. The WPP is very convenient, but it has a great disadvantage in estimation accuracy by plotting method. It is very difficult to get the same results even if one use the same data several times. A computer program for the regression method is used for the parameter estimation to reduce these errors. Especially, the computer graphic program was written in GW-BASIC 3.22 language and the program appears in the appendix part with a couple of running examples for user's reference.

• IE interfaces
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• v.15 no.1
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• pp.89-98
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• 2002

This paper considers the optimum replacement times of a steam generator in nuclear power plant with failure data. It is assumed that the failure pattern of units is given as a Weibull distribution and repair and periodic preventive maintenance are performed periodically. The maximum likelihood method is used to estimated the Weibull parameters of failure distribution from failure data. Relpacement, output-decresing and maintenance costs are considered to determine the optimal replacement times by simulation. Numerical examples are included with actual failure data and cost estimators.