• Journal of Korean Society for Quality Management
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• v.25 no.3
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• pp.96-107
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• 1997

The recent stream to reliability prediction is that it is totally inclusive in depth to consider even the operating and environmental condition at the level of finished goods as well as component itselves. In this study, firstly we present the reliability prediction methods by entire failure rate model which failure rate at the system level is added to the failure rate model at the component level. Secondly we build up the improved bases of reliability demonstration through a, pp.ication of Kaplan-Meier, Cumulative hazard, Johnson's methods as non-parametric and Maximum Likelihood Estimator under exponential & Weibull distribution as parametric. And also present the methods of curve fitting to piecewise failure rate under Weibull distribution, PRST (Probability Ratio Sequential Test), curve fitting to S-shaped reliability growth curve, computer programs of each methods. Lastly we show the practical for determination of optimal burn-in time as a method of reliability enhancement, and also verify the practical usefulness of the above study through the a, pp.ication of failure and test data during 1 year.

• Journal of Korean Society for Quality Management
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• v.37 no.4
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• pp.16-22
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• 2009

The inflection S-shaped software reliability growth model (SRGM) proposed by Ohba(1984) is one of the most commonly used models and has been discussed by many authors. The main purpose of this paper is to estimate the parameters of Ohba's SRGM within the Bayesian framework by applying the Markov chain Monte Carlo techniques. While the maximum likelihood estimates for these parameters are well known, the Bayesian method for the inflection S-shaped SRGM have not been discussed in the literature. The proposed methods can be quite flexible depending on the choice of prior distributions for the parameters of interests. We also compare the Bayesian methods with the maximum likelihood method numerically based on the real data.

• Journal of Korean Society for Quality Management
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• v.43 no.3
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• pp.221-238
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• 2015

Purpose: In this study, A reliability assurance model (or reliability program) is proposed to evaluate the reliability of an armed vehicle. The reliability assurance is performed through the reliability-centered activities during its life cycle of development/design, production, deployment, maintenance, and disposal. Methods: By reflecting the current situations of korea defense industry, a reliability assurance model is built up based on the benchmarking results of world leading companies' best practices in same fields. Results: The proposed reliability program of armed vehicles, which is based on the reliability program of ANSI/GEIA-STD 0009, uses DMAIC process of the six sigma methodology from design phase to testing and evaluation phase. Conclusion: This research is supposed to develop reliability program of armed vehicles by integrating DFSS, DFR and reliability growth process.

• Journal of the Korean Data and Information Science Society
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• v.17 no.3
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• pp.727-742
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• 2006

In general, weapon systems require very high reliability. Recently Korean defense reliability technologies growth rapidly. However, there are some matters of reform in reliability management, reliability assurance, and defense acquisition environment, etc. In this paper, we propose the reliability development plan for Korean defense system as follows; 1) reliability improvement programs for each acquisition stages, 2) reliability improvement methods for logistics support, 3) reliability improvement programs for developers and manufacturers, 4) reform matters for the defense acquisition law, 6) establishment of defense reliability assessment center and defense reliability committee.

• 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 Korea Society of Digital Industry and Information Management
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• v.10 no.4
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• pp.19-27
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• 2014

Software reliability in the software development process is an important issue. Software process improvement helps in finishing with reliable software product. Infinite failure NHPP software reliability models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, proposes the reliability model with log type mean value function (Musa-Okumoto and log power model), which made out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on mean square error (MSE) and coefficient of determination($R^2$), for the sake of efficient model, was employed. Analysis of failure using real data set for the sake of proposing log type mean value function was employed. This analysis of failure data compared with log type mean value function. In order to insurance for the reliability of data, Laplace trend test was employed. In this study, the log type model is also efficient in terms of reliability because it (the coefficient of determination is 70% or more) in the field of the conventional model can be used as an alternative could be confirmed. From this paper, software developers have to consider the growth model by prior knowledge of the software to identify failure modes which can be able to help.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.2
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• pp.29-36
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• 2014

Finite failure NHPP software reliability models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, proposes the Gompertz distribution reliability model, which made out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on mean square error (MSE) and coefficient of determination$(R^2)$, for the sake of efficient model, was employed. Analysis of failure using real data set for the sake of proposing fixed shape parameter of the Gompertz distribution was employed. This analysis of failure data compared with the Gompertz distribution model of shape parameter. In order to insurance for the reliability of data, Laplace trend test was employed. In this study, the proposed Gompertz model is more efficient in terms of reliability in this area. Thus, Gompertz model can also be used as an alternative model. From this paper, software developers have to consider the growth model by prior knowledge of the software to identify failure modes which can was helped.

• Proceedings of the KSR Conference
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• 2007.05a
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• pp.941-946
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• 2007

In this paper, as the step to assess and enhance the reliability of Korean Tilting Train eXpress (T.T.X), Door system is selected and reliability analysis is carried out. The door system is classified into subsystems and functional block diagrams and reliability block diagrams are drawn.Expessions for evaluating the reliability are derived and Mean Kilometer between Service Failure is calculated using the trial track test results. The calculation result show reliability growth of proposed system. This paper developed RAMS to make a door system of T.T.X. (Tilting Train eXpress) with maximum operation speed of 180 km/h.

• Journal of Information Technology Applications and Management
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• v.13 no.4
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• pp.1-12
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• 2006

Many software reliability growth models(SRGM) have been proposed since the software reliability issue was raised in 1972. The technology to estimate and grow the reliability of developing S/W to target value during testing phase were developed using them. Most of these propositions assumed the S/W debugging testing efforts be constant or even did not consider them. A few papers were presented as the software reliability evaluation considering the testing effort was important afterwards. The testing effort forms which have been presented by this kind of papers were exponential, Rayleigh, Weibull, or logistic functions, and one of these 4 types was used as a testing effort function depending on the S/W developing circumstances. I propose the methology to evaluate the SRGM using least square estimator and maximum likelihood estimator for those 4 functions, and then examine parameters applying actual data adopted from real field test of developing S/W.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.4
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• pp.7-14
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• 2011

Infinite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rate per fault (hazard function). This infinite non-homogeneous Poisson process is model which reflects the possibility of introducing new faults when correcting or modifying the software. In this paper, polynomial hazard function have been proposed, which can efficiency application for software reliability. Algorithm for estimating the parameters used to maximum likelihood estimator and bisection method. Model selection based on mean square error and the coefficient of determination for the sake of efficient model were employed. In numerical example, log power time model of the existing model in this area and the polynomial hazard function model were compared using failure interval time. Because polynomial hazard function model is more efficient in terms of reliability, polynomial hazard function model as an alternative to the existing model also were able to confirm that can use in this area.