• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.864-865
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• 2011

Battery Disconnecting System (BDS) is the important equipment in electric vehicle system. Therefore, most of electric vehicle companies, i.e. Hyundai Motors, Renault Motors, General Motors, want to have the reliability of 15 years - 150, 000 miles. Recently, reliability prediction through Siemens Norm SN 29500 is considered without testing. In this paper, we will introduce the standard and various input parameters. Also the case study will be shown for BDS. Prediction model is constructed by listing all the components of BDS. It calculates the $\pi$ factors for each components using the conversion equation in the standard and converts the reference failure rates to the expected operating failure rates. According to the result, the parts which will be improved are EV-Relays.

• Journal of KIISE:Software and Applications
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• v.27 no.4
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• pp.393-401
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• 2000

This paper explores neuro-fuzzy system in order to improve the software reliability predictability from failure data. We perform numerical simulations for actual 10 failure count and 4 failure time data sets from different software projects with the various number of rules. Comparative results for next-step prediction problem is presented to show the prediction ability of the neuro-fuzzy system. Experimental results show that neuro-fuzzy system is adapt well across different software projects. Also, performance of neuro-fuzzy system is favorably with the other well-known neural networks and statistical SRGMs.

• Journal of Applied Reliability
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• v.9 no.2
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• pp.71-80
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• 2009

This paper discusses the service life prediction methods for CFRP bar for concrete reinforcement using accelerated degradation tests. The relationship between performance degradation and the rate of a failure-causing chemical reaction is assumed for the temperature accelerated degradation tests. Methods of obtaining acceleration factors and predicting service life of the CFRP bar using the degradation model are presented.

• The Transactions of the Korean Institute of Power Electronics
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• v.21 no.4
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• pp.328-334
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• 2016

This paper examines the reliability of a VSC-HVDC valve based on a modular multilevel converter (MMC) HVDC system. The main objective of this paper is to determine the redundancy of the MMC valve. Several prediction methods are introduced, but the binomial failure method is selected to be used. To determine the availability and reliability prediction of MMC valve, which comprises a DC/DC converter, a gate driver, a capacitor, and an IGBT, the failure data of the MMC module are used as the tracking data according to the experimental result. This method uses a simplified equation to find the valve redundancy by transforming the binomial function to De Moivre's formula. This method is the first to be used to find the valve margin.

• Journal of the Korean Society of Safety
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• v.18 no.1
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• pp.81-88
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• 2003

Recently, pile foundations were constructed in rough or soft ground than ground of well condition thus it is important that prediction of ultimate bearing capacity and calculation of proper safety factor applied pile foundation design. This study were performed to dynamic loading tests for the thirty two piles at four different construction sites and selected pile at three site were performed to static loading tests and then compare with measured value and value of static and dynamic loading tests. The load-settlement curve form the dynamic loading tests by CAPWAP was very similar to the results obtained from the static load tests. Based on dynamic and static loading tests, the reliability of pile-driving formula were analyzed and then suggested with proper safety factor for prediction of allowable bearing capacity in this paper.

• Proceedings of the Korean Reliability Society Conference
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• 2011.06a
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• pp.21-26
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• 2011

Initial reliability prediction done by calculation would be more practical if support by evidence from customer usage profile and field failure data to improve the prediction. Thus, the consistency of the design and the product would be practically validated. In this paper, it will address rationale and method to decide on Acceleration Factor (AF) to be used in Accelerated Life Test (ALT) through usage profile and field failure. The case study of tractor transmission is used to demonstrate the method which data obtained from surveys done on farmers, field visits and field failure data from service center. By considering all the elements, it will determine more relevant AF which indicates the real use conditions of the component.

• Communications for Statistical Applications and Methods
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• v.18 no.5
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• pp.667-674
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• 2011

A recent trend in software reliability engineering accounts for the coverage growth behavior during testing. The coverage growth function (representing the coverage growth behavior) has become an essential component of software reliability models. Application of a coverage growth function requires the estimation of the coverage growth function. This paper considers the problem of estimating the coverage growth function. The existing maximum likelihood method is reviewed and corrected. A method of minimizing the sum of squares of the standardized prediction error is proposed for situations where the maximum likelihood method is not applicable.

• Magazine of the Korean Society of Agricultural Engineers
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• v.43 no.4
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• pp.97-105
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• 2001

The ultrasonic pulse velocity test has a strong potential to be developed into a very useful and relatively inexpensive in-place test for assuring the quality of concrete placed in structure. The main problem in realizing this potential is that the relationship between compressive strength ad ultrasonic pulse velocity is uncertain and concrete is an inherently variable material. The objective of this study is to improve the reliability of in-place concrete strength predictions by ultrasonic pulse velocity method. Experimental cement content, s/a rate, and curing condition of concrete. Accuracy of the prediction expressed in empirical formula are examined by multiple regression analysis and linear regression analysis and practical equation for estimation the concrete strength are proposed. Multiple regression model uses water-cement ratio cement content s/a rate, and pulse velocity as dependent variables and the compressive strength as an independent variable. Also linear regression model is used to only pulse velocity as dependent variables. Comparing the results of the analysis the proposed equation expressed highest reliability than other previous proposed equations.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.1
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• pp.67-73
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• 2014

A reliability evaluation or prediction can be defined as MTBF which stands for mean time between failures (Exclusively for repairable failures). Spindle system has huge effect on performance of machine tools and working quality as well as is required of high reliability. Especially, it takes great importance in producing automobiles which includes a large number of working processes. However, it is unusually difficult to predict reliability because there are lack of data and research about reliability of spindle system. Standards and methods of examinations for reliability evaluation of machine tools are scarce at local and abroad as well. Therefore, this research is meant to improve the reliability of spindle system before mass produced with developing standards of reliability and methods of examinations through FMEA to assess reliability of spindle system in prototype stages of developing high speed spindle system of machining center.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.2
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• pp.159-169
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• 2019

Objective: Models for genomic selection assume that the reference population is an unselected population. However, in practice, genotyped individuals, such as progeny-tested bulls, are highly selected, and the reference population is created after preselection. In dairy cattle, the intensity of selection is higher in males than in females, suggesting that cows can be added to the reference population with less bias and loss of accuracy. The objective is to develop formulas applied to any genomic prediction studies or practice with preselected animals as reference population. Methods: We developed formulas for calculating the reliability and bias of genomically enhanced breeding values (GEBV) in the reference population where individuals are preselected on estimated breeding values. Based on the formulas presented, deterministic simulation was conducted by varying heritability, preselection percentage, and the reference population size. Results: The number of bulls equal to a cow regarding the reliability of GEBV was expressed through a simple formula for the reference population consisting of preselected animals. The bull population was vastly superior to the cow population regarding the reliability of GEBV for low-heritability traits. However, the superiority of reliability from the bull reference population over the cow population decreased as heritability increased. Bias was greater for bulls than cows. Bias and reduction in reliability of GEBV due to preselection was alleviated by expanding reference population. Conclusion: Cows are easier in expanding reference population size compared with bulls and alleviate bias and reduction in reliability of GEBV of bulls which are highly preselected than cows by expanding the cow reference population.