• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.201-201
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• 2016

The asymptotic extreme value distributions of maxima are a natural choice when designing against future extreme events like flood peaks or wave heights, given a stationary time series. The generalized extreme value distribution (GEV) is often utilised in this context because it is seen as a convenient single expression for extreme event analysis. However, the GEV has a drawback because the location of the distribution bound relative to the data is a discontinuous function of the GEV shape parameter. That is, for annual maxima approximated by the Gumbel distribution, the data is also consistent with a GEV distribution with an upper bound (no lower bound) or a GEV distribution with a lower bound (no upper bound). A more consistent single extreme value expression for design purposes is proposed as the Weibull distribution of smallest extremes, as applied to transformed annual maxima. The Weibull distribution limit holds here for sufficiently large sample sizes, irrespective of the extreme value domain of attraction applicable to the untransformed maxima. The Gumbel, Type 2, and Type 3 extreme value distributions thus become redundant, together with the GEV, because in reality there is only a single asymptotic extreme value distribution required for design purposes - the Weibull distribution of minima as applied to transformed maxima. An illustrative synthetic example is given showing transformed maxima from the normal distribution approaching the Weibull limit much faster than the untransformed sample maxima approach the normal distribution Gumbel limit. Some New Zealand examples are given with the Weibull distribution being applied to reciprocal transformations of annual flood maxima, where the untransformed maxima follow apparently different extreme value distributions.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.678-685
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• 2005

Estimating parameters of the lifetime distribution is investigated when field failure data are not completely reported. To take into account the reality and the accuracy of the estimates in such a case, the failure reporting probability is incorporated in estimating parameters. Firstly, method of maximum likelihood estimate(MLE) is used to estimate parameters of the lifetime distribution when failure reporting probability is known. Secondly, Expectation and Maximization(EM) algorithm is used to estimate the failure reporting probability and parameters of the lifetime distribution simultaneously when failure reporting probability is unknown. For both case, procedures of estimation are illustrated for single Weibull distribution and mixed Weibull distribution. Simulation results show that MLE obtained by the proposed method is more accurate than the conventional MLE.

• Journal of Applied Reliability
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• v.17 no.2
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• pp.112-121
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• 2017

Purpose: The most previous works on designing accelerated life tests (ALTs) are focused on the application of a single stress. Because of the difficulty to obtain the sufficient information in a reasonable duration using single stress only, there is needed in practice to use multiple-stress ALTs frequently. This paper presents new practical plans with two stresses for Weibull distribution. Methods: The four-level practical plans based on rectangle test region are proposed and compared with the corresponding three-level statistically optimal plans. Sensitivity analyses for assumed design parameters and life-stress relationship are conducted. Results: A procedure to choose practical ALT plans is illustrated with a numerical example and guidelines for planning two-stress ALTs are provided. Conclusion: The proposed two-stress ALT plans on practical constraints to assess a quantile of Weibull lifetime distribution at the use condition are efficient and robust.

• Journal of Korean Society for Quality Management
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• v.20 no.1
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• pp.48-58
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• 1992

This paper deals with a test procedures on reliablity using hybrid censoring when failure time follows two parameter Weibull distribution. In each case of single and two stage test with hybrid censoring, we construct a operating characteristic curve, and then obtain the censoring number and sample size which the producer's risk and the consumer's risk are both satisfied. This study suggests to determine the expected waiting time at a decision.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.1
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• pp.52-60
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• 2007

Estimating parameters of the lifetime distribution is investigated when field failure data are not completelyreported. To take into account the reality and the accuracy of the estimates in such a case, the failure reportingprobability is incorporated in estimating parameters, Firstly, method of maximum likelihood estimate (MLE) isused to estimate parameters of the lifetime distribution when failure reporting probability is known, Secondly,Expectation and Maximization (EM) algorithm is used to estimate the failure reporting probability and parame-ters of the lifetime distribution simultaneously when failure reporting probability is unknown. For both cases,procedures of estimation are illustrated for single Weibull distribution and mixed Weibull distribution. Simula-tion results show that MLE obtained by the proposed method is more accurate than the conventional MLE.

• Computers and Concrete
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• v.21 no.3
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• pp.291-298
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• 2018

In this study, the flexural fatigue performance of concrete beams made with 100% Coarse Recycled Concrete Aggregates (RCA) and 100% Coarse Natural Aggregates (NA) were statistically commanded. For this purpose, the experimental fatigue test results of earlier researcher were investigated using two parameter Weibull distribution. The shape and scale parameters of Weibull distribution function was evaluated using seven numerical methods namely, Graphical method (GM), Least-Squares (LS) regression of Y on X, Least-Squares (LS) regression of X on Y, Empherical Method of Lysen (EML), Mean Standard Deviation Method (MSDM), Energy Pattern Factor Method (EPFM) and Method of Moments (MOM). The average of Weibull parameters was used to incorporate survival probability into stress (S)-fatigue life (N) relationships. Based on the Weibull theory, as single and double logarithm fatigue equations for RCA and NA under different survival probability were provided. The results revealed that, by considering 0.9 level survival probability, the theoretical stress level corresponding to a fatigue failure number equal to one million cycle, decreases by 8.77% (calculated using single-logarithm fatigue equation) and 6.62% (calculated using double logarithm fatigue equation) in RCA when compared to NA concrete.

• Journal of Applied Reliability
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• v.13 no.2
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• pp.87-98
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• 2013

Accelerated degradation tests (ADTs) measuring failure-related degradation characteristic at the accelerated condition are widely used to assess the reliability of highly reliable products. Often, however, little degradation could be observed even in single-stress ADTs due to the high reliability of test unit, and as a result poor estimate of the reliability may be obtained. ADTs with multiple stress variables can be employed to overcome such difficulties. In this paper, optimal ADT plans with two stress variables are developed assuming that the degradation characteristic follows Weibull distribution by determining the stress levels, the proportion of test units allocated to each stress level such that the asymptotic variance of the maximum likelihood estimator of the q-th quantile of the lifetime distribution at the use condition is minimized.

• Journal of Power System Engineering
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• v.21 no.5
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• pp.13-19
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• 2017

The effect of heat treatment temperature (HTT) on the mechanical properties of polyacrylonitrile (PAN)-based carbon fiber had been investigated. The heat treatment on the carbon fiber was conducted under high vacuum atmosphere of $10^{-6}mmHg$, and the range of temperature of $1,000^{\circ}C$ to $2,000^{\circ}C$. As a results, The tensile strength of carbon fiber and carbon fiber composites showed increasing tendency with the rise of heat treatment temperature. And, the shape parameter of Weibull distribution for the strength of carbon single fiber showed an increasing trend until $1,800^{\circ}C$. But the shape parameter of Weibull distribution for the strength of carbon fiber composites showed no clear tendency with the rise of heat treatment temperature. The cause of reinforcement effect of the carbon fiber by the heat treatment was regarded as the carbonization of carbon single fiber.

• Communications for Statistical Applications and Methods
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• v.26 no.3
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• pp.325-336
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• 2019

In this article we extend the discrete Weibull regression model in the presence of missing data. Discrete Weibull regression models can be adapted to various type of dispersion data however, it is not widely used. Recently Yoo (Journal of the Korean Data and Information Science Society, 30, 11-22, 2019) adapted the discrete Weibull regression model using single imputation. We extend their studies by using multiple imputation also with several various settings and compare the results. The purpose of this study is to address the merit of using multiple imputation in the presence of missing data in discrete count data. We analyzed the seventh Korean National Health and Nutrition Examination Survey (KNHANES VII), from 2016 to assess the factors influencing the variable, 1 month hospital stay, and we compared the results using discrete Weibull regression model with those of Poisson, negative Binomial and zero-inflated Poisson regression models, which are widely used in count data analyses. The results showed that the discrete Weibull regression model using multiple imputation provided the best fit. We also performed simulation studies to show the accuracy of the discrete Weibull regression using multiple imputation given both under- and over-dispersed distribution, as well as varying missing rates and sample size. Sensitivity analysis showed the influence of mis-specification and the robustness of the discrete Weibull model. Using imputation with discrete Weibull regression to analyze discrete data will increase explanatory power and is widely applicable to various types of dispersion data with a unified model.

• Journal of Aerospace System Engineering
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• v.10 no.1
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• pp.51-58
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• 2016

In this paper, we present some results on No-failure accelerated life test of aerial vehicle for reliability demonstration. The design of general accelerated life test consists of the three phases: 1) Estimating normal life test time of a single product from Weibull distribution model; 2) Determining the acceleration factor (AF) by utilizing the relation between the life of mechanical components and the applied torque; 3) Calculating the accelerated life test time, which comes from dividing the estimated normal life test time into AF. Then, we applied the calculated life test time to the real reliability test of the flap actuating system, while considering the requirement specification for mechanical components and operating environment of the actuation system. Real experimental processes and results are presented to validate the theory.