• Journal of Applied Reliability
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• v.1 no.1
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• pp.47-54
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• 2001

This paper considers the parameter estimation problem of the failure intensity function and maintenance effect in a repairable system. We propose estimation procedures for repairable systems on which preventive maintenance is performed. The failure process is modeled by a proportional age reduction model [Brown, Mahoney and Sivazlian(1983)] which is useful to model the imperfect effect of preventive maintenance. When failure and maintenance (preventive) times are given, the maximum likelihood method is used to estimate the maintenance effect and the parameters of intensity function, simultaneously We obtain the maximum likelihood estimators using a genetic algorithm. A numerical example is also presented.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.9
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• pp.96-102
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• 2009

In this study, performs analysis of the life of parallel opening type pneumatic chucks that are usually applied in the factory automation line. Pneumatic chucks have complicated failure cause because they are organized as a complex of various elements. Therefore, we analyzed the main failure mode of pneumatic chuck, and then performed life test and performance test according to the international standards. On the basis of these processes, shape parameter of pneumatic chuk is proposed that is the main factor for the calculation of zero failure test time for the reliability of pneumatic chuck and their data analysis of life distribution.

• Journal of the Semiconductor & Display Technology
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• v.22 no.1
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• pp.54-58
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• 2023

In this study, we compared the detection accuracy of the parameters of the scaffold failure detection model. A detection algorithm based on convolutional neural network was used to construct a failure detection model for scaffold. The parameter properties of the model were changed and the results were quantitatively verified. The detection accuracy of the model for each parameter was compared and the parameter with the highest accuracy was identified. We found that the activation function has a significant impact on the detection accuracy, which is 98% for softmax.

• 한국데이터정보과학회:학술대회논문집
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• 2004.04a
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• pp.1-5
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• 2004

In this paper, we calculate the premium rate of reliability insurance policy for T11 composite metreial under the assumption of Weibull physics of failure and Arrhenius law. We also describe the performance factors which have an effect on failure characteristics of wiper motors. The maximum likelihood estimates of shape parameter and scale parameter are obtained by using interval censored real data of sample sizes 6 using MINITAB.

• Journal of the Korean Data and Information Science Society
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• v.15 no.1
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• pp.49-57
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• 2004

In this paper, we calculate the premium rate of reliability insurance policy for wiper motors under the assumption of Weibull physics of failure. We also describe the performance factors which have an effect on failure characteristics of wiper motors. The maximum likelihood estimates of shape parameter and scale parameter are obtained by using interval censored real data of sample sizes 6 using MINITAB.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.2
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• pp.141-147
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• 2016

NHPP software reliability models for failure analysis can have, in the literature, exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, infinite failures NHPP models that repairing software failure point in time reflects the situation, was presented for comparing property. Commonly used in the field of software reliability based on Flexible Weibull extension distribution software reliability of infinite failures was presented for comparison problem. The result is that a relatively small shaping parameter was effectively. The parameters estimation using maximum likelihood estimation was conducted and model selection was performed using the mean square error and the coefficient of determination.. In this research, software developers to identify software failure property follows shape parameter, some extent be able to help is considered.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.10
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• pp.747-752
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• 2019

By using the failure information and the cumulative test execution time obtained by performing the reliability growth test, it is possible to estimate the parameter of the reliability growth model, and the Mean Time Between Failure (MTBF) of the product can be predicted through the parameter estimation. However the failure information could be acquired periodically or the number of sample data of the obtained failure information could be small. Because there are various constraints such as the cost and time of test or the characteristics of the product. This may cause the error of the parameter estimation of the reliability growth model to increase. In this study, the Bayesian method is applied to estimating the parameters of the reliability growth model when the number of sample data for the fault information is small. Simulation results show that the estimation accuracy of Bayesian method is more accurate than that of Maximum Likelihood Estimation (MLE) respectively in estimation the parameters of the reliability growth model.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.23 no.11 s.170
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• pp.2022-2032
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• 1999

In recent years, the subject of remaining life assessment has drawn considerable attention in the power generation industry. In power generation systems a variety of structural components, such as steam pipes, turbine rotors, and superheater headers, typically operate at high temperatures and high pressures. Thus a life prediction methodology accounting for fracture and rupture is increasingly needed for these components. For accurate failure assessment, in addition to the single parameter such as K or J-integral used in traditional fracture mechanics, the second parameter like T-stress describing the constraint is needed. The most critical defects in such structures are generally found in the form of semi-elliptical surface cracks in the welded piping-joints. In this work, selecting the structures of surface-cracked plate and straight pipe, we first perform line-spring finite element modeling, and accompanying elastic-plastic finite element analyses. We then present a framework for including constraint effects (T-stress effects) in the R6 failure assessment diagram approach for fracture assessment.

• Journal of Korean Society for Quality Management
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• v.25 no.4
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• pp.71-78
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• 1997

In this paper, we consider a hierarchical Bayes estimation of the parameter, the reliability and failure rate functions based on type-II censored samples from a Burr type-？ failure time model. The Gibbs sampler a, pp.oach brings considerable conceptual and computational simplicity to the calculation of the posterior marginals and reliability. A numerical study is provided.

• Magazine of the Korean Society of Agricultural Engineers
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• v.27 no.2
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• pp.23-37
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• 1985

This studies were carried out to get characteristics of frequency distribution, probable flood flows according to the return periods, and the correlation between return periods and those length of records affect the Risk of failure in the annual maximum series of the main river systems in Korea. Especially, Risk analysis according to the levels were emphasized in relation to the design frequency factors for the different watersheds. Twelve watersheds along Han, Geum, Nak Dong, Yeong San and Seom Jin river basin were selected as studying basins. The results were analyzed and summarized as follows. 1. Type 1 extremal distribution was newly confirmed as a good fitted distribution at selected watersheds along Geum and Yeong San river basin. Three parameter lognormal Seom Jin river basin. Consequently, characteristics of frequency distribution for the extreme value series could be changed in connection with the watershed location even the same river system judging from the results so far obtained by author. 2. Evaluation of parameters for Type 1 extremal and three parameter lognormal distribution based on the method of moment by using an electronic computer. 3. Formulas for the probable flood flows were derived for the three parameter lognormal and Type 1 extremal distribution. 4. Equations for the risk to failure could be simplified as $\frac{n}{N+n}$ and $\frac{n}{T}$ under the condition of non-parametric method and the longer return period than the life of project, respectively. 5. Formulas for the return periods in relation to frequency factors were derived by the least square method for the three parameter lognormal and Type 1 extremal distribution. 6. The more the length of records, the lesser the risk of failure, and it was appeared that the risk of failure was increasing in propotion to the length of return periods even same length of records. 7. Empirical formulas for design frequency factors were derived from under the condition of the return periods identify with the life of Hydraulic structure in relation to the risk level. 8. Design frequency factor was appeared to be increased in propotion to the return periods while it is in inverse proportion to the levels of the risk of failure. 9. Derivation of design flood including the risk of failure could be accomplished by using of emprical formulas for the design frequency factor for each watershed.