• Journal of Information Technology Applications and Management
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• v.24 no.1
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• pp.25-32
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• 2017

For repairable software systems, the Mean Time Between Failure (MTBF) is used as a measure of software system stability. Therefore, the evaluation of software reliability requirements or reliability characteristics can be applied MTBF. In this paper, we want to compare MTBF in terms of parameter estimation using Makeham life distribution. The parameter estimates used the least square method which is regression analyzer method and the maximum likelihood method. As a result, the MTBF using the least square method shows a non-decreased pattern and case of the maximum likelihood method shows a non-increased form as the failure time increases. In comparison with the observed MTBF, MTBF using the maximum likelihood estimation is smallerd about difference of interval than the least square estimation which is regression analyzer method. Thus, In terms of MTBF, the maximum likelihood estimation has efficient than the regression analyzer method. In terms of coefficient of determination, the mean square error and mean error of prediction, the maximum likelihood method can be judged as an efficient method.

• Journal of the Korean Data and Information Science Society
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• v.20 no.3
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• pp.467-474
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• 2009

There are many situations arising in reliability engineering and biomedical science where failure of a subsystem increases the failure rate of other subsystem under shared load models. In this paper, the maximum likelihood estimates and the modified maximum likelihood estimates of mean time to failure and reliability function for shared load model with guarantee time are obtained by using censored system life data. Some illustrative examples are included.

• Communications for Statistical Applications and Methods
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• v.19 no.2
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• pp.219-224
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• 2012

This article considers the mean time to failure(MTTF) of a dependent parallel system. We study how the degree of dependency components influences the increase in the mean lifetime for this system. The results are illustrated by tables and figures.

• International Journal of Reliability and Applications
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• v.5 no.2
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• pp.81-103
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• 2004

Improvements of a bridge network system are studied in this paper. Then equivalence between different improved designs of the bridge network system is discussed. Three different methods are used to get different better designs of the network in the sense of having higher reliability and mean time to failure. Then two different types of reliability equivalence factors of the system are derived. It is assumed here that the failure rates of the system's components are identical and constant. The reliability functions and mean time to failure of the original and improved designs of the network are derived. Comparison between the mean time to failures of the original system and improved designs of the system are presented. Numerical studies and conclusion are presented in order to explain how one can apply the the theoretical results obtained.

• 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.

• 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.

• Journal of the Korean Data and Information Science Society
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• v.18 no.2
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• pp.535-541
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• 2007

The Non-homogeneous Poisson process is probably the most popular model since it can model systems that are deteriorating or improving. The renewal process is a model that is often used to describe the random occurrence of events in time. But both these models are based on too restrictive assumptions on the effect of the repair action. The Modulated Power Law Process is a suitable model for describing the failure pattern of repairable systems when both renewal-type behavior and time trend are present. In this paper we propose maximum likelihood estimation of the next failure time after the system has experienced some failures, that is, Mean Time Between Failure for the MPLP model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.428-434
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• 2020

The one-shot weapon system is destroyed after only one mission. So, the system requires high reliability. Guided missiles are one-shot weapon systems that have to be analyzed by storage reliability since they spend most of their life in storage. The analysis results depend on the model and the ratio of correct censored data. This study was conducted to propose a method to more accurately predict the future failure rate of Air force guided missiles. In the proposed method, the failure rate is predicted by both MTTF (Mean Time To Failure) and MTBF (Mean Time Between Failure) models and the model with a smaller error from the real failure rate is selected. Next, with the selected model, the ratio of correct censored data is selected to minimize the error between the predicted failure rate and the real failure rate. Based on real field data, the comparative result is determined and the result shows that the proposed sampling rate can predict the future failure rate more accurately.

• International Journal of Reliability and Applications
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• v.16 no.1
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• pp.1-13
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• 2015

In this paper, we investigate reliability and availability of repairable systems with two types of failure. The first one is to one unit and the second one is to M units in parallel structure. Let failure rate and repair rate of [type1, type2] components are assumed to be exponentially distributed. The expressions of availability and reliability characteristics such as the system reliability and the mean time to failure are derived for two systems. We used several cases to analyze graphically the effect of various system parameters on the reliability system and availability system.

• International Journal of Reliability and Applications
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• v.16 no.2
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• pp.99-111
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• 2015

In this paper, we study the reliability analysis of a repairable system with two types of failure in which switching failures and reboot delay are considered. Let units in this system be cold standby, and failure rate and repair rate of [type1, type2] components be exponentially distributed. The expressions of reliability characteristics - such as the system reliability and the mean time to system failure MTTF - are derived. We use several cases to graphically analyze the effect of various system parameters on the system reliability and MTTF. We also perform a sensitivity analysis of the reliability characteristics with changes in specific values of the system's parameters.