• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.2
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• pp.308-313
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• 2009

This paper presents a reliability analysis of S-bonds for AF track circuits, which detect train movement and transmit a speed control signal to the train. Field survey shows that S-bonds are exposed to very large vibrations transferred from rail, and suffer from frequent failures when they were installed on ballasted track. We collected the time-to-failure data of S-bonds from the maintenance field of Seoul metro line 2, and made a parametric approach to estimate the statistical distribution that fits the time-to-failure data. The analysis shows that S-bonds have time-to-failure characteristics described by Weibull distribution. The estimated shape parameter of Weibull distribution is 1.1, which means the distribution has constant failure rate characteristics like exponential distribution. The reliability function, hazard function, percentiles and mean lifetime are derived for maintenance support.

• International Journal of Reliability and Applications
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• v.16 no.1
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• pp.15-26
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• 2015

Present study investigates the fuzzy reliability of some systems using intuitionistic fuzzy Weibull lifetime distribution, in which the lifetime parameters are assumed to be fuzzy parameter due to uncertainty and inaccuracy of data. Expressions for fuzzy reliability, fuzzy mean time to failure, fuzzy hazard function and their ${\alpha}$-cut have been discussed when systems follow intuitionistic fuzzy Weibull lifetime distribution. A numerical example is also taken to illustrate the methodology to calculate the fuzzy reliability characteristics of systems.

• Journal of Biosystems Engineering
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• v.11 no.1
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• pp.76-85
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• 1986

This study was intended to examine the failure characteristics and breakdowns of the head-fed type combines generally used on farms. The failure distribution was assumed to follow Weibull distribution function and the Weibull parameters of the major parts, units and combine as whole were estimated by using the data collected in a survey. A computer program for the estimation of the Weibull parameter was developed. Monte Carlo method was used in predicting the time between failures. The results of study may be summarized as follows: 1. The number of failures per combine was 4.83 times per year and 0.3 times per hectare of combines of different ages. 2. According to the Kolmogorov-Smirnov test method, it was proved that the Weibull distribution function is well fitted to the characteristics of the failure and breakdowns of combines. 3. Weibull parameters of failure distribution of the combine as a whole were estimated to give the shape parameter ${\beta}$=1.3089 and the scale parameter ${\alpha}$=105.2409. The combining area with 80% reliability was 1.1 ha, and the probability of operating the combine without any failure for a year, was $2.76{\times}10^{-4}$. 4. The mean time between failures (MTBF) of the combines was predicted to be 3.2 ha of operation, which corresponds to 32 hours of operation.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1331-1336
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• 2008

This paper suggests a method using Bayesian inference to estimate the parameters of Weibull distribution and acceleration parameters under the condition that the stresses are time-dependent functions. A Bayesian model based on the discrete time approximation is formulated to infer the parameters of interest from the failure data of the virtual tests and a statistical analysis is considered to decide the most probable mean values of the parameters for reasoning of the failure data.

• Journal of Biosystems Engineering
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• v.28 no.6
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• pp.537-544
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• 2003

The objectives of this study were to investigate the failure characteristics of a total of 90 parts of tractor driveline, and to predict their average annual demands required to perform the after-sales service. The failure characteristics such as failure mode, mean time between failures, characteristic life and reliability were analyzed using the data collected through the experienced mechanics at the part centers of the tractor manufacturers. The analysis was based on the assumption that the failure distribution follows the Weibull distribution. The average annual demands were also predicted for the replacement parts using the mean time between failures and the renewal theory based on the Weibull distribution. The results of the study revealed that the driveline parts failure was mostly from wearout and their average characteristic life is about 1.760 hours. The estimated mean time between failures was in a range of 670∼3,740 hours and reliability in a range of 40∼60％. The annual replacement demands were in a range of 4∼45 for a service of 100 tractors.

• Journal of the Korean Institute of Gas
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• v.7 no.4 s.21
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• pp.20-23
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• 2003

The analysis of reliabilities of process facilities often uses models based on the Weibull distribution. The parameters in these models are functions of operating conditions, and determined by experiments. Using these values, we calculate the reliability, mean time to failure, and standard deviation. The conventional method assumes that the operating condition is constant, and thus treats the model parameters as constants. In this paper, a reliability function is proposed which is applicable when the scale parameter is a function of time, and an analysis method based on this is also presented. A case study on a cooling fan resulted in a big difference from the conventional method to which the average operating conditions were applied. The proposed method is also applicable to other process facilities, and expected to effectively take into account the effects of changes in the operating conditions on the reliabilities of the facilities.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.11
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• pp.548-556
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• 2005

Reliability evaluation of power distribution system is very important to both power utilities and customers. It present the probabilistic number and duration of interruption such as failure rate, SATDI, SAIFI, and CAIDI. However, it has a fatal weakness at reliability index because of accuracy of failure rate. In this paper, the Time-varying Failure Rate(TFR) of power distribution system equipment is extracted from the recorded failure data of KEPCO(Korea Electric Power Corporation) in Korea. For TFR extraction, it is used that the fault data accumulated by KEPCO during 10 years. The TFR is approximated to bathtub curve using the exponential(random failure) and Weibull(aging failure) distribution function. In addition, Kaplan-Meier estimation is applied to TFR extraction because of incomplete failure data of KEPCO. Finally, Probability plot and regression analysis is applied. It is presented that the extracted TFR is more effective and useful than Mean Failure Rate(MfR) through the comparison between TFR and MFR

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.59 no.2
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• pp.154-157
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• 2010

In this paper, the Time-varying Failure Rates(TFR) of power distribution system components are extracted from the recorded failure data of KEPCO(Korea Electric Power Corporation) and the reliability of power distribution system is evaluated using Mean Failure Rate(MFR) and TFR. The TFR is approximated to bathtub curve using the exponential and Weibull distribution function. In addition, Kaplan-Meier estimation is applied to TFR extraction because of incomplete failure data of KEPCO. Also the reliability of the real power distribution system of Korea is evaluated using the MFR and TFR extracted from real failure data, respectively and the results of each case are compared with each other. As a result, it is proved that the reliability evaluation using the TFR is more realistic than MFR. In addition, it is presented that the application method at power distribution system maintenance and repair using the result of TFR.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.4
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• pp.63-68
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• 2006

This research presents the reliability analysis of the pneumatic actuator within the tape feeder that is used to transfer the correct force to linked parts during l.0E+7 cycles. First, the degradation analysis for thrust and air leakage is executed to obtain the failure data of a product based on its performance over time. Second, once the parameters has been calculated using the weibull 2-parameter distribution and MLE(Maximum Likelihood Estimation), information related to life such as reliability, failure rate, probability density function is estimated. Finally, MTTF(Mean Time To Failure) and $B_{10}$ life of actuators are calculated. MTTF means the mean life at the confidence level and $B_{10}$ life refers to the time by which 10% of the product would fail. In this study, failure causes and solutions are examined using the reliability analysis.

• 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.