• 디지털산업정보학회논문지
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• 제10권2호
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• pp.1-11
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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. In this field, SPC (Statistical process control) is a method of process management through application of statistical analysis, which involves and includes the defining, measuring, controlling, and improving of the processes. The proposed process involves evaluation of the parameter of the mean value function and hence the values of the mean value function at various inter failure times to develop relevant time control chart. In this paper, was proposed a control mechanism, based on time between failures observations using Rayleigh and Burr distribution property, which is based on Non Homogeneous Poisson Process (NHPP). In this study, the proposed model is reliable in terms of hazard function, because it is more efficient in this area can be used as an alternative to the existing model. Through this study, software developers are considered by the various intended functions, prior knowledge of the software to identify failure modes to feed to some extent shall be able to help.

• 한국산학기술학회논문지
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• 제11권4호
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• pp.1239-1247
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• 2010

본 연구에서는 소프트웨어 제품을 개발하여 테스팅을 거친 후 사용자에게 인도하는 시기를 결정하는 방출문제에 대하여 연구되었다. 인도시기에 관한 모형은 무한 고장수에 의존하는 비동질적인 포아송 과정을 적용하였다. 이러한 포아송 과정은 소프트웨어의 결함을 제거하거나 수정 작업 중에도 새로운 결함이 발생될 가능성을 반영하는 모형이다. 강도함수는 여러 수명 분포들을 적합시키는데 효율적인 특성을 가진 콤페르쯔, 파레토, 로그-로지스틱 패턴을 이용하였다. 따라서 소프트웨어 요구 신뢰도를 만족시키고 소프트웨어 개발 및 유지 총비용을 최소화 시키는 방출시간이 최적 소프트웨어 방출 정책이 된다. 본 논문의 수치적인 예에서는 고장 간격 시간 자료를 적용하고 모수추정 방법은 최우추정법과 추세분석을 통하여 자료의 효율성을 입증한 후 최적 방출시기를 추정하였다.

• 한국산업융합학회 논문집
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• 제23권6_2호
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• pp.1103-1110
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• 2020

In this study, a segmented model with Upside-Down bathtub shaped failure intensity for a repairable system are proposed under the assumption that the occurrences of the failures of a repairable system follow the Non-Homogeneous Poisson Process. The proposed segmented model is the compound model of S-PLP and LIP (Segmented Power Law Process and Logistic Intensity Process), that fits the separate failure intensity functions on each segment of time interval. The maximum likelihood estimation is used for estimating the parameters of the S-PLP and LIP model. The case study of system A shows that the S-PLP and LIP model fits better than the other models when compared by AICc (Akaike Information Criterion corrected) and MSE (Mean Squared Error). And it also implies that the S-PLP and LIP model can be useful for explaining the failure intensities of similar systems.

• 한국통신학회논문지
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• 제37권1B호
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• pp.50-58
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• 2012

본 연구의 주된 목적은 사용자 관점에서 본 통신 시스템 서비스 가용도의 이론적 모델 개발이다. 이를 위하여 호(Call) 도착은 non-homogeneous 포아손 과정의 가정, 그리고 시스템 상태는 CTMC 모델의 가정을 토대로 서비스 가용도의 추계적 모델을 개발하였다. 제시한 모델은 시간에 따라 변하는 호 도착률을 포함하여 사용자 관점에서 본 서비스 신뢰도 모형의 사용자 모델을 효율적으로 나타냈다. 아울러 시스템 자원의 고장 없이도 사용자가 서비스를 받지 못하는 시스템 상태인 운영 고장 상태를 모델에 포함하여 제공자 입장이 아니라 사용자 관점에서 모델을 구축하였다.

• 한국군사과학기술학회지
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• 제14권5호
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• pp.859-870
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• 2011

The purpose of this paper is to develop reliability analysis procedures for repairable systems with interval failure time data and apply the procedures for assessing the storage reliability of a subsystem of a certain type of guided missile. In the procedures, the interval failure time data are converted to pseudo failure times using the uniform random generation method, mid-point method or equispaced intervals method. Then, such analytic trend tests as Laplace, Lewis-Robinson, Pair-wise Comparison Nonparametric tests are used to determine whether the failure process follows a renewal or non-renewal process. Monte Carlo simulation experiments are conducted to compare the three conversion methods in terms of the statistical performance for each trend test when the underlying process is homogeneous Poisson, renewal, or non-homogeneous Poisson. The simulation results show that the uniform random generation method is best among the three. These results are applied to actual field data collected for a subsystem of a certain type of guided missile to identify its failure process and to estimate its mean time to failure and annual mean repair cost.

• Journal of Information Technology Applications and Management
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• 제27권3호
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• pp.69-75
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• 2020

In this paper, we applied the shape parameters of the exponentialized exponential life distribution widely used in the field of software reliability, and compared the reliability properties of the software using the non-homogeneous Poisson process in finite failure. In addition, the average value function is also a non-decreasing form. In the case of the larger the shape parameter, the smaller the estimated error in predicting the predicted value in comparison with the true value, so it can be regarded as an efficient model in terms of relative accuracy. Also, in the larger the shape parameter, the larger the estimated value of the coefficient of determination, which can be regarded as an efficient model in terms of suitability. So. the larger the shape parameter model can be regarded as an efficient model in terms of goodness-of-fit. In the form of the reliability function, it gradually appears as a non-increasing pattern and the higher the shape parameter, the lower it is as the mission time elapses. Through this study, software operators can use the pattern of mean square error, mean value, and hazard function as a basic guideline for exploring software failures.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1995년도 춘계공동학술대회논문집; 전남대학교; 28-29 Apr. 1995
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• pp.682-693
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• 1995

• 디지털산업정보학회논문지
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• 제7권2호
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• pp.1-8
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• 2011

In this study, software products developed in the course of testing, software managers in the process of testing software test and test tools for effective learning effects perspective has been studied using the NHPP software. The finite failure non-homogeneous Poisson process models presented and the life distribution applied extreme distribution which used to find the minimum (or the maximum) of a number of samples of various distributions. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. As a result, the learning factor is greater than automatic error that is generally efficient model could be confirmed. This paper, a numerical example of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection were efficient using the mean square error.

• 한국신뢰성학회지:신뢰성응용연구
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• 제9권2호
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• pp.121-130
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• 2009

The power law process model the Rate of occurrence of failures(ROCOF) with monotonic trend during the operating time. However, the power law process is inappropriate when a non-monotonic trend in the failure data is observed. In this paper we deals with the reliability modeling of the failure process of large and complex repairable system whose rate of occurrence of failures shows the non-monotonic trend. We suggest a sectional model and a change-point test based on the Schwarz information criterion(SIC) to describe the non-monotonic trend. Maximum likelihood is also suggested to estimate parameters of sectional model. The suggested methods are applied to field data from an repairable system.

• 디지털산업정보학회논문지
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• 제8권2호
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• pp.1-10
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• 2012

In this study, software products developed in the course of testing, software managers in the process of testing software test and test tools for effective learning effects perspective has been studied using the NHPP software. The finite failure nonhomogeneous Poisson process models presented and the life distribution applied exponential and log shaped type hazard function. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. As a result, the learning factor is greater than autonomous errors-detected factor that is generally efficient model could be confirmed. This paper, a failure data analysis of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection were efficient using the mean square error and coefficient of determination.