• Journal of the Korea Society of Computer and Information
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• v.11 no.5 s.43
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• pp.9-18
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• 2006

Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, Goel-Okumoto and Yamada-Ohba-Osaki model was reviewed, proposes the exponentiated exponential distribution reliability model, which maked out efficiency substituted for gamma and Weibull model(2 parameter shape illustrated by Gupta and Kundu(2001) Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE, AIC statistics and Kolmogorov distance, for the sake of efficient model, was employed. Analysis of failure using NTDS data set for the sake of proposing shape parameter of the exponentiated exponential distribution was employed. This analysis of failure data compared with the exponentiated exponential distribution model and the existing model (using arithmetic and Laplace trend tests, bias tests) is presented.

• Polymer(Korea)
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• v.32 no.5
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• pp.440-445
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• 2008

The failure mechanism and failure morphology of linear low density polyethylene (LLDPE) tubing under hydrostatic pressure were investigated. Microscopic observations using video microscope and scanning electron microscope indicate that the failure mode is a brittle fracture including cracks propagated from inner wall to outer wall. In addition, oxidation induction time and Fourier transform infrared spectroscopy results show the presence of exothermic peak and the increase in carbonyl index on the surface of fractured LLDPE tubing, due to thermal-degradation. An accelerated life test methodology and testing system for LLDPE tubing are developed using the relationship between stresses and life characteristics by means of thermal acceleration. Statistical approaches using the Arrhenius model and Weibull distribution are implemented to estimate the long-term life time of LLDPE tubing under hydrostatic pressure. Consequently, the long-term life time of LLDPE tubing at the operating temperature of $25^{\circ}C$ could be predicted and also be analyzed.

• Industry Promotion Research
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• v.7 no.4
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• pp.1-8
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• 2022

There are many one-shot devices that are used once and thrown away. One-shot devices such as firecrackers and ammunition are typical, and they are stored for a while after manufacture and then disposed of after use when necessary. However, unlike general operating systems, these one-shot devices have not been properly evaluated. This study first examines what the government does to secure reliability in the case of ammunition through ammunition stockpile reliability program. Next, in terms of statistical analysis, we show what the reliability analysis methods are for one-shot devices such as ammunition. Specifically, we show that it is possible to know the level of reliability if sampling inspection plan such as KS Q 0001 which is acceptance sampling plan by attributes is used. Next, non-parametric and parametric methods are introduced as ways to determine the storage reliability of ammunition. Among non-parametric methods, Kaplan-Meier method can be used since it can also handle censored data. Among parametric methods, Weibull distribution can be used to determine the storage reliability of ammunition.

• The Korean Journal of Applied Statistics
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• v.8 no.1
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• pp.89-104
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• 1995

This paper is concerned with the method of estimating lifetime distributin from field data for products with multiple modes of failure. When product failures occur within warranty period, a manufacturer can obtain failure-record data; failure times, causes of failure, and covariates. Since these data are seriously incomplete for satisfactory inference, that is, only failures occured during warrantly period may be recorded, it is usually necessary to incoporate the failure-record data by taking a supplementary sample of items obtained following up a portion of products that survive warranty time. The log linear function is considered as a model for describing the relation between failure time of a product and covariates. General methods for obtaining pseudo maximum likelihood estimators(PMLEs) for the parameters are outlined and their asymptotic properties are studied, and specific formulas for exponential or Weibull distribution are obtained. Effects of follow-up percentage on the PMLEs are investigated. Extensions to calendar time warranty or calendar and obtaining time warranty are also considered.

• 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 Digital Contents Society
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• v.15 no.1
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• pp.19-27
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• 2014

In order to estimate the life of 2,5 inch HDD which is adopted by PC environment, make the test plan which reflect the failure mode of market, make the test model of accelerated life test which reflect the stress of temperature. after an analysis of the environment of PC using, test procedure was decided that operation was write 50 % and read 50 %, and then access method was sequential 50 % and random 50%. The acceleration life test was executed on condition that temperature was $50^{\circ}C$ and $60^{\circ}C$, performance was 95 % in max performance, test time was 1000 hours. by the test of goodness of fit of anderson-darling of the failure data during test, it was confirmed that the distribution of failure fellow weibull. test for shape and scale was equal, and shape parameter was 0.7177, characteristic life was 429434 hours at normal user condition($30^{\circ}C$) by the analysis of weibull-arrhenius modeling. It made no difference about the statistics when equality test was executed. The activation energy was 0.2775eV. In analyzing between the failure samples of acceleration test and the samples of market return even though there is detail difference about the share of failure mode, the rank of share was almost same. This study suggest the test procedure of acceleration test of 2.5 inch HDD in PC using environment, and help the life estimation at manufacture and user.

• Journal of Navigation and Port Research
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• v.43 no.3
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• pp.186-196
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• 2019

Berthing energy is majorly influenced by the berthing velocity. It is necessary to design an appropriate berthing velocity for each pier, since excessive berthing velocity can cause berthing accident causing damage to the ship and pier. In this study, as a statistical approach for berthing velocity, the probability distributions suitable for the berthing velocities were confirmed using the K-S test, the A-D test and the Q-Q plot. As a result, the frequency distribution of the berthing velocity was found to be suitable using the Weibull distribution as well as the lognormal distribution. Additionally, the predicted values obtained through estimation of the berthing velocity using the concept of probability of exceedance in this study is proposed as a reference of design berthing velocity. It can be observed that the design berthing velocity is set to be somewhat low so that it does not practically match with the reality. This study and its results can be expected to contribute to the development of a proper design velocity calculation method.

• Journal of the Korean Data and Information Science Society
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• v.28 no.4
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• pp.797-810
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• 2017

The Korean peninsula is exposed to typhoons every year. Typhoons cause huge socioeconomic damage because tropical cyclones tend to occur with strong winds and heavy precipitation. In order to understand the complex dependence structure between strong winds and heavy precipitation, the copula links a set of univariate distributions to a multivariate distribution and has been actively studied in the field of hydrology. In this study, we carried out analysis using data of wind speed and precipitation collected from the weather stations in Busan and Jeju. Log-Normal, Gamma, and Weibull distributions were considered to explain marginal distributions of the copula. Kolmogorov-Smirnov, Cramer-von-Mises, and Anderson-Darling test statistics were employed for testing the goodness-of-fit of marginal distribution. Observed pseudo data were calculated through inverse transformation method for establishing the copula. Elliptical, archimedean, and extreme copula were considered to explain the dependence structure between strong winds and heavy precipitation. In selecting the best copula, we employed the Cramer-von-Mises test and cross-validation. In Busan, precipitation according to average wind speed followed t copula and precipitation just as maximum wind speed adopted Clayton copula. In Jeju, precipitation according to maximum wind speed complied Normal copula and average wind speed as stated in precipitation followed Frank copula and maximum wind speed according to precipitation observed Husler-Reiss copula.