• International Journal of Reliability and Applications
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• v.15 no.2
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• pp.125-150
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• 2014

Accelerated life tests (ALTs) are extensively used to determine the reliability of a product in a short period of time. Test units are subject to elevated stresses which yield quick failures. ALT can be carried out using constant-stress, step-stress, progressive-stress, cyclic-stress or random-stress loading and their various combinations. An ALT with linearly increasing stress is ramp-stress test. Much of the previous work on planning ALTs has focused on constant-stress, step-stress, ramp-stress schemes and their various combinations where the stress is generally increased. This paper presents an optimal design of ramp soak-stress ALT model which is based on the principle of Thermal cycling. Thermal cycling involves applying high and low temperatures repeatedly over time. The optimal plan consists in finding out relevant experimental variables, namely, stress rates and stress rate change points, by minimizing variance of reliability function with pre-specified mission time under normal operating conditions. The Burr type XII life distribution and time-censored data have been used for the purpose. Burr type XII life distribution has been found appropriate for accelerated life testing experiments. The method developed has been explained using a numerical example and sensitivity analysis carried out.

• Journal of the Korean Society of Safety
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• v.32 no.5
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• pp.115-121
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• 2017

This paper is to introduce the main modeling assumptions and data structures associated with right-censored data to describe the successful methodological ideas for analyzing such a field-failure-data when components operating in different environments. The Kaplan - Meier method is the most popular method used for survival analysis. Together with the log-rank test, it may provide us with an opportunity to estimate survival probabilities and to compare survival between groups. An important advantage of the Kaplan - Meier curve is that the method can take into account some types of censored data, particularly right-censoring. The above non-parametric method was used to verify the equality of parts life used in different environments. After that, we performed the life distribution analysis using the parametric method. We simulated data from three distributions: exponential, normal, and Weibull. This allowed us to compare the results of the estimates to the known true values and to quantify the reliability indices. Here we used the Akaike information criterion to find a suitable life time distribution. If the Akaike information criterion is the smallest, the best model of failure data is presented. In this paper, no-nparametrics and parametrics methods are analyzed using R program which is a popular statistical program.

• The Korean Journal of Applied Statistics
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• v.9 no.2
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• pp.95-108
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• 1996

There are many clinical trials where a large portion of the patients are cured of disease. In such a case, one might be more interested in testing the differences in cure rates rather than other types of differences in failure distribution. For ethical and economic reasons, clinical trials must be repeatedly monitored for evidence of treatment benefit or harm. In this article, we examined by simulation the properties of nonparametric group sequential methods for comparing the cure rates between two treatment groups during the trial in a wide range of alternatives, censoring rates and cure rates.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.372-374
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• 2006

This paper presents a methodology to predict a failure probability related to the aging generating units in Korea power system. Each generator is represented by a combined reliability model of its individual components, which is determined by failure data. The Weibull distribution is used to calculate failure probability and its parameters are obtained from Type II Censoring. Consequently, the proposed methods would likely to permit utilities to reduce overall costs in the new deregulated environment.

• Journal of the Korean Data and Information Science Society
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• v.14 no.4
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• pp.751-758
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• 2003

We consider a life testing experiment in which several two-component shared parallel systems are put on test, and the test is terminated at a predesigned experiment time. The bivariate data obtained from such a system-level life testing can be classified into three cases: 1) the case of failed two components with known failures times, 2) the case of censored two components, and 3) the case of one censored component and the other failed component of which the failure time might be known or unknown. In this thesis, the likelihood estimators for Freund's bivariate exponential life distribution under above censoring scheme are obtained. Results of comparative studies based on Monte Carlo simulation are presented.

• Journal of the Korean Data and Information Science Society
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• v.26 no.1
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• pp.271-280
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• 2015

In this paper, the maximum likelihood estimators for parameters are derived under three step-stress accelerated life tests for Type-I hybrid censored data. The exponential distribution and the cumulative exposure model are considered based on the assumption that a log quadratic relationship exits between stress and the mean lifetime ${\theta}$. The test plan to search optimal stress change times minimizing the asymptotic variance of maximum likelihood estimators are presented. A numerical example to illustrate the proposed inferential procedures and some simulation results to investigate the sensitivity of the optimal stress change times by the guessed parameters are given.

• Proceedings of the KIEE Conference
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• summer
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• pp.464-466
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• 2004

This paper proposes a method to consider an aging failure probability and survival probability of power system components unlike uses only aging failure probability in existing mean life calculation. The estimates of the mean and its standard deviation is calculated by using Weibull distribution and each estimated parameters is obtained from Data Analytic Method (Type II Censoring). The parameter estimation using Data Analytic Method is simpler and faster than a traditional calculation method. This paper shows how to calculate the mean life and its standard deviation by the proposed method and illustrates a exactness using real historical records of generator utilities in korea.

• Journal of Korean Society for Quality Management
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• v.22 no.4
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• pp.59-78
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• 1994

In some observational studies, we have often random censoring model. However, the data available may be partially observable censored data consisting of the observed failure times and only those nonfailure times which are subject to follow up. In this paper, we present an extension of the problem of partially parametric estimation of the survival function to such partially observable censored data. The proposed estimator treats the observed failure times nonparametrically and uses a parametric model only for those nonfailure times which are subject to follow-up. We discuss the motivation and construction of the proposed estimator and investigate the limiting properties of the proposed estimator such as asymptotic normality. Also, when the assumed parametric model is exponential, the asymptotic variance of the estimator is obtained. Furthermore, an example is given to compare the proposed estimator with the modified Kaplan Meier(MKM) estimator. From the results, it is shown that the relative efficiency of the proposed estimator is higher than that of the MKM estimator in the follow-up study with increasing time.

• Journal of Korean Society for Quality Management
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• v.26 no.2
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• pp.27-38
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• 1998

Consider a life testing experiment in which multiple two-component shared parallel systems are put on test, and the test is terminated at a specified number of system failures. The bivariate data obtained from such a system-level life testing can be classified into three classes: 1) the case of failed two components with known failure times, 2) the case of censored two components, and 3) the case of one censored component and the other failed component of which the failure time might be known or unknown. Under this censoring scheme and the assumption of Freund's bivariate exponential life distribution, the maximum likelihood estimators are obtained. Results of comparative studies based on Monte Carlo simulation are presented.

• Journal of Korean Society for Quality Management
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• v.17 no.1
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• pp.89-106
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• 1989

For Weibull distributed lifetimes, this paper presents asymptotically optimal accelerated life test plans for practical applications under intermittent inspection and type-I censoring. Computational results show that the asymptotic variance of a low quantile at the design stress as optimal criterion is insensitive to the number of inspections at overstress levels. Sensitivity analyses indicate that optimal plans are robust enough to moderate departures of estimated failure probabilities at the design and high stresses as input parameters to plan accelerated life tests from their true values. Monte Carlo simulation for small sample study on optimal accelerated life test plans developed by the asymptotic maximum likelihood theory is conducted. Simulation results suggest that optimal plans are satisfactory for sample size in practice.