• Journal of Korea Society of Industrial Information Systems
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• v.3 no.1
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• pp.13-21
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• 1998

와이블분포의 척도모수와 형상모수를 베이지안 방법을 이용하여 추정한다. 깁스표본법을 사용하여 모수들에 대한 추정, 결합사후확률분포와 주변사후확률분포를 구한다. 9개의 열 전달기기자료와 10개의 인위적인 자료를 이용하여 제안된 방법을 적용하여 사례를 연구한다.

• Journal of the Korean Data and Information Science Society
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• v.20 no.1
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• pp.39-48
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• 2009

Fisher information matrix plays an important role in statistical inference of unknown parameters. Especially, it is used in objective Bayesian inference which derives to the posterior distribution using a noninformative prior distribution and is an example of metric functions in geometry. The more parameters for estimating in a distribution are, the more complicate derivation of the Fisher information matrix for the distribution is. In this paper, we derive to the Fisher information matrix for 3-parameters Weibull distribution which is used in reliability theory using Mathematica programs.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2009.11a
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• pp.339-343
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• 2009

The aim of the study was to investigate the statistical distribution of muzzle velocity of 155mm propelling charge K676 which is for the use of K9, a korean 155mm self-propelled artillery. A plenty of muzzle velocity data were collected from lot assessment test of propelling charge. The muzzle velocity of each test round is compensated by reference round. In the present work, the detailed statistical analysis of the muzzle velocity data is carried out using probability models including normal, Weibull 2-parameter and Weibull 3-parameter distributions. The results of goodness of fit test showed that the normal distribution described more appropriately the experimentally measured muzzle velocity data and the Weibull distribution is also applicable. The coefficient of variation showed that the mass production capability of each propelling charge lot has been maintained.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.3
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• pp.109-115
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• 2006

The Weibull distribution is a good candidate for accurate probabilistic model with its rich shape-forming ability and relatively simple CDF(cumulative distribution function). If there are sufficient information to get convincible mean and variance for a probabilistic event, reliable parameters of the Weibull distribution can be determined uniquely. However, sufficient information is not given as usual. There needs more deliberate model building method for that case. This Paper presents an effective parameter estimation technique for Weibull distribution with limited failure data.

• Proceedings of the KSME Conference
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• 2001.11a
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• pp.272-277
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• 2001

In order to evaluate variation of fatigue data of the LP steam turbine blade steel, it is important to estimate P - S - N curves to accurately define the probability distributions. In this study, new procedure is introduced to determine the expression of P - S - N curves. For this purpose, 3-parameter Weibull distribution was found to be most appropriate among assumed distributions when the probability distributions of the fatigue life were examined by the proposed analysis. Furthermore, parameter estimation for P - S - N curves was performed using various optimization to maximize the correlation coefficient. As a result of this, sequential linear programing method is used for estimation of P - S - N curves.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.3
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• pp.365-372
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• 2013

In this study, a statistical method for evaluating the fatigue life of a vehicle muffler was used to obtain reliable fatigue data using a limited number of specimens. Cyclic bending tests were conducted using specimens manufactured to be exactly the same as the mufflers installed in cars that are currently in use. To estimate the fatigue life by comparing the data obtained during the fatigue tests, the most suitable probability density function for the normal, lognormal, and Weibull distributions was selected. A goodness-of-fit test was performed on the probability distributions, and then a Weibull distribution using the least square method was selected. By using the selected Weibull distribution, the probability-moment-life curves (P-M-N curve) reflecting the fatigue characteristics were suggested as the data for the reliable design of a muffler.

• Journal of the Korean Data and Information Science Society
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• v.20 no.3
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• pp.485-492
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• 2009

In this paper, we studied process capability analysis for brake-pad manufacturing system and considered Weibull, normal and logistic distributions for density estimation of wear life of brake pads for a passenger car with a real data. These three distributions are seem to work well. Estimated percentiles of brake pads can be used to evaluate the design criteria and customers' need for brake pads.

• Convergence Security Journal
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• v.6 no.3
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• pp.117-126
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• 2006

Bayesian inference and model selection method for software reliability growth models are studied. Software reliability growth models are used in testing stages of software development to model the error content and time intervals between software failures. In this paper, could avoid multiple integration using Gibbs sampling, which is a kind of Markov Chain Monte Carlo method to compute the posterior distribution. Bayesian inference for general order statistics models in software reliability with diffuse prior information and model selection method are studied. For model determination and selection, explored goodness of fit (the error sum of squares), trend tests. The methodology developed in this paper is exemplified with a software reliability random data set introduced by of Weibull distribution(shape 2 & scale 5) of Minitab (version 14) statistical package.

• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.10
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• pp.82-88
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• 2018

The decoy defensive weapon system is a one-shot system. Reliability is maintained through periodic inspection and high reliability is required to confirm whether or not the functioning is normal after launch. The maintenance cycle of a decoy was set up without target reliability and reliability prediction during the development period. However, the number of operations in the military has been increasing, necessitating the optimization of the maintenance cycle. Reliability is analyzed using the maintenance data of a decoy operated for several decades and the optimal maintenance cycle is suggested. In chapter 2, data collection and classification methods are presented and analysis methodology is briefly introduced. In chapter 3, the data distribution analysis and fitness verification confirmed that applying the Weibull distribution is the most suitable for the maintenance data of the decoy. In chapter 4, we present the analysis result of percentile, survival probability and MTBF and the optimal maintenance cycle was derived from the reliability analysis. Finally, we suggest the application methods for this paper in the future.