• Proceedings of the Korean Reliability Society Conference
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• 2004.07a
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• pp.161-166
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• 2004

A method of estimating B$_{\alpha}$ life of crack growth is proposed based on the linear elastic fracture mechanic model. It is assumed that the coefficients in the Paris-Erdogan equation are random variables and their distributions are estimated by the method of 2-stage estimation from the fatigue crack growth data. A case study is also given. is also given.

• Journal of Korean Society for Quality Management
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• v.37 no.3
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• pp.33-38
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• 2009

When we estimate the parameters of software reliability models, we usually use maximum liklihood estimator(MLE). But this method is required a large data set. In particular, when we want to estimate it with small observed data such as early stages of testing, we give rise to the non-existence of MLE. Therefore, it is interesting to look into the influence of parameter estimators obtained using MLE. In this paper, we use two non-homogenous poisson process software reliability growth model: delayed S-shaped model and log power model. In this paper, we calculate the sensitivity of estimators about failure intensity function for two SRGMs respectively.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.143-146
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• 2005

The software reliability growth depends on the testing time because the failure rate varies whether it is long or not. On the other hand, it might be difficult to reduce failure rate for most of the cases are not available for debugging during operational phase, hence, there are some literatures to study that the failure rate is uniform throughout the operational time. The failure rate reduces and the reliability grows with time regardless of debugging. As a result, the products reliability varies with the time duration of these products in point of customer view. The reason of this is that it accumulates the products experience, studies the exact operational method, and then finds and takes action against the fault circumstances. I propose the simple model to represent this status in this paper.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.1
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• pp.29-38
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• 1998

We summarize, in this paper, that we have learned from the slftwar reliability analysis of a large switching software composed of functional blocks which form slotware units. To determine the time of management activity related to sopftware reliability growth, we review the process of detection and correction of software failures. Also we apply the two softwre reliability frowth model, Goel-Okumoto and S-shaped model, to estimate the global software reliability growth to a set of failure found during period of the system test. The analysis methods and results can be applied to other large software development projects.

• The Transactions of the Korea Information Processing Society
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• v.6 no.3
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• pp.615-621
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• 1999

On the aspect of on-time and development resource use, it is very important to predict the software release time during the software development process. In this paper, we present the optimal release problem based on the evaluation indicator and cost evaluation. And also we show the optimal release point considered with both of them. We applied the Exponential Software Reliability Growth Model(E-SRGM) and Testing-effort dependent Software Reliability Growth Model(Te-SRGM) and decided the software release time according to software reliability indicator. As a result of two models comparison, we verify the Te-SRGM is more adopted in our switching system software.

• Journal of Applied Reliability
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• v.16 no.2
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• pp.162-170
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• 2016

Purpose: The purpose of this study was to analyze the failure modes of an auto transfer switch (ATS), determine the most common failure mechanisms, and iterate the design to improve reliability. Methods: We carried out failure mode and effect analysis (FMEA) to determine the failure modes and mechanisms. We identified the parts or modules that required improvement via two-stage quality function deployment based on FMEA, and improvements to reliability were monitored using the Gomperz growth model. Results: The main failure modes of the ATS were damage to, and deformation of, the stator / movable element due to repetitive movements. Five iterations of design modification were carried out, and the mean time to failure (MTTF) increased to 14,539 cycles, corresponding to 85% of the target MTTF. The Gompertz growth model indicates that the 10th iteration of design modification is expected to achieve the target MTTF. Conclusion: We improved the reliability of mechanical parts via failure mode analysis, and characterized the iterative improvements in the MTTF using the Gompertz growth model.

• Journal of KIISE
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• v.42 no.12
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• pp.1551-1560
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• 2015

Software Reliability Growth Models (SRGMs) are used to quantitatively evaluate software reliability and to determine the software release date or additional testing efforts using software failure data. Because a single SRGM is not universally applicable to all kinds of software, the selection of an optimal SRGM suitable to a specific case has been an important issue. The existing methods for SRGM selection assess the goodness-of-fit of the SRGM in terms of the collected failure data but do not consider the accuracy of future failure predictions. In this paper, we propose a method for selecting SRGMs using the trend of failure data and failure prediction ability. To justify our approach, we identify problems associated with the existing SRGM selection methods through experiments and show that our method for selecting SRGMs is superior to the existing methods with respect to the accuracy of future failure prediction.

• Proceedings of the KSR Conference
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• 2003.10a
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• pp.151-155
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• 2003

In this paper, as the first step to assess and enhance the reliability of Korea High Speed Train, electric traction system is selected and reliability analysis is carried out. The electric traction system is classified into subsystems and functional block diagrams and reliability block diagrams are drawn. Expressions to calculate the reliability are deducted and Mean Kilometer Between Service Failure is calculated using the trial test results on the track. Calculated results show reliability growth of the electric traction system.

• Journal of Information Technology Applications and Management
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• v.12 no.2
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• pp.1-13
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• 2005

This paper proposes a software-reliability growth model incoporating the amount of testing effort expended during the software testing phase after developing it. The time-dependent behavior of testing effort expenditures is described by a Logistic curve. Assuming that the error detection rate to the amount of testing effort spent during the testing phase is proportional to the current error content, a software-reliability growth model is formulated by a nonhomogeneous Poisson process. Using this model the method of data analysis for software reliability measurement is developed. After defining a software reliability, This paper discusses the relations between testing time and reliability and between duration following failure fixing and reliability are studied. SRGM in several literatures has used the exponential curve, Railleigh curve or Weibull curve as an amount of testing effort during software testing phase. However, it might not be appropriate to represent the consumption curve for testing effort by one of already proposed curves in some software development environments. Therefore, this paper shows that a logistic testing-effort function can be adequately expressed as a software development/testing effort curve and that it gives a good predictive capability based on real failure data.

• Journal of the Korea Society of Computer and Information
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• v.1 no.1
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• pp.195-210
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• 1996

For predicting the parameters and estimating the goodness of fit reliability growth model based on NHPP(Non Homogeneous Poission Process) among various reliability growth models, a Delayed S Shaped SRGM Tool is designed and Implemented. The Implemented tool is applied to real software error data, and the result Is compared and annalized.