• Journal of Applied Reliability
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• v.9 no.2
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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.

• 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 Information Technology Applications and Management
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• v.28 no.4
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• pp.13-20
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• 2021

In this paper, I was applied the life distribution following linear failure rate distribution, Lindley distribution and Burr-Hatke exponential distribution extensively used in the arena of software reliability and were associated the reliability possessions of the software using the nonhomogeneous Poisson process with finite failure. Furthermore, the average value functions of the life distribution are non-increasing form. Case of the linear failure rate distribution (exponential distribution) than other models, the smaller the estimated value estimation error in comparison with the true value. In terms of accuracy, since Burr-Hatke exponential distribution and exponential distribution model in the linear failure rate distribution have small mean square error values, Burr-Hatke exponential distribution and exponential distribution models were stared as the well-organized model. Also, the linear failure rate distribution (exponential distribution) and Burr-Hatke exponential distribution model, which can be viewed as an effectual model in terms of goodness-of-fit because the larger assessed value of the coefficient of determination than other models. Through this study, software workers can use the design of mean square error, mean value function as a elementary recommendation for discovering software failures.

• International Journal of Reliability and Applications
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• v.14 no.2
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• pp.55-70
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• 2013

This paper deals with the Bayesian analysis of the failure data of a repairable mechanical system subject to minimal repairs and periodic overhauls. The effect of overhauls on the reliability of the system is modeled by a proportional age reduction model and the failure process between two successive overhauls is assumed to be 2-parameter Engelhardt-Bain process (2-EBP). Power Law Process (PLP) model has a disadvantage which 2-EBP can overcome. On the basis of the observed data and of a number of suitable prior densities, point and interval estimation of model parameters, as well as quantities of relevant interest are found. Also hypothesis tests on the effectiveness of performed overhauls have been developed using Bayes factor. Sensitivity analysis of improvement parameter is carried out. Finally, a numerical application is used to illustrate the proposed method.

• Spatial Information Research
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• v.6 no.1
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• pp.77-90
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• 1998

The complex interactions of climate, topography, geology, biota and hwnan activities result in the land cover patterns, which are impacted by natural disturbances such as fire, earthquake and flood. Natural disturbances disrupt ecosystem communities and change the physical environment, thereby generating a new landscape. Community ecologists believe that disturbance is critical in determining how diverse ecological systems function. Fires were once a major agent of disturbance in the North American tall grass prairies, African savannas, and Australian bush. The major focus of this research was to develop stochastic model of spatial process of disturbance or spatial events and simulate the process based on the developed model and it was applied to the fire arrival process in the Great Victoria Desert of Australia, where wildfires generate a mosaic of patches of habitat at various stages of post-fire succession. For this research, Landsat Multi-Spectral Scanner(MSS) data covering the period from 1972 to 1994 were utilized. Fire arrival process is characterized as a spatial point pattern irregularly distributed within a region of space. Here, nonhomogeneous planar Poisson process is proposed as a model for the fire arrival process and rejection sampling thinning the homogeneous Poisson process is used for its simulation.

• International Journal of Reliability and Applications
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• v.8 no.1
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• pp.53-66
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• 2007

This paper proposes a new non-homogeneous Poisson process software reliability growth model based on the coverage information. The new model incorporates the coverage information in the fault detection process by assuming that only the faults in the covered constructs are detectable. Since the coverage growth behavior depends on the testing strategy, the fault detection process is first modeled for the general testing strategy and then realized for the uniform testing. Finally the model for the uniform testing is empirically evaluated by applying it to real data sets.

• Proceedings of the KSR Conference
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• 2001.05a
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• pp.347-358
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• 2001

In this paper, we apply NHPP model example to s/w process in order to get to know s/w reliability. The test is constructed by a test zig of commercial product loaded real embedded system s/w. It is established to s/w reliability prediction and estimation of real-time embedded system s/w. It is computed the prediction value of cumulative failures, the failure intensity, the reliability and the estimation value of MTTF, Failure Rate. To the more realization of high reliability in the real-time embedded system s/w, if the embedded system s/w is ensured to the test coverage and constructed to stable s/w process ＆ operating system, we can improve the performance and the reliability characteristic of the real-time embedded system s/w.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.29 no.2
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• pp.109-120
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• 2017

A discounted cost model for preventive maintenance of armor units of rubble-mound breakwaters is mathematically derived by combining the deterioration model based on a discrete-time stochastic process of shock occurrence with the cost model of renewal process together. The discounted cost model of condition-based maintenance proposed in this paper can take into account the nonlinearity of cumulative damage process as well as the discounting effect of cost. By comparing the present results with the previous other results, the verification is carried out satisfactorily. In addition, it is known from the sensitivity analysis on variables related to the model that the more often preventive maintenance should be implemented, the more crucial the level of importance of system is. However, the tendency is shown in reverse as the interest rate is increased. Meanwhile, the present model has been applied to the armor units of rubble-mound breakwaters. The parameters of damage intensity function have been estimated through the time-dependent prediction of the expected cumulative damage level obtained from the sample path method. In particular, it is confirmed that the shock occurrences can be considered to be a discrete-time stochastic process by investigating the effects of uncertainty of the shock occurrences on the expected cumulative damage level with homogeneous Poisson process and doubly stochastic Poisson process that are the continuous-time stochastic processes. It can be also seen that the stochastic process of cumulative damage would depend directly on the design conditions, thus the preventive maintenance would be varied due to those. Finally, the optimal periods and scale for the preventive maintenance of armor units of rubble-mound breakwaters can be quantitatively determined with the failure limits, the levels of importance of structure, and the interest rates.

• Journal of Korean Society for Quality Management
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• v.26 no.3
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• pp.71-81
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• 1998

In reliability analysis, the time difference between the expected next failure time and the current failure time or the Mean Time Between Failure(MTBF) is of significant interest. Until recently, in reliability growth studies, the reciprocal of the intensity function at current failure time has been used as being equal to MTBE($t_n$)at the n-th failure time $t_n$. That is MTBF($t_n$)=l/$\lambda (t_n)$. However, such a relationship is only true for Homogeneous Poisson Process(HPP). Tsokos(1995) obtained the upper bound and lower bound for the MTBF($t_n$) and proposed an estimator for the MTBF($t_n$) as the mean of the two bounds. In this paper, we provide the estimator for the MTBF($t_n$) which does not depend on the value of the shape parameter. The result of the Monte Carlo simulation shows that the proposed estimator has better efficiency than Tsokos's estimator.

• Journal of Integrative Natural Science
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• v.10 no.4
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• pp.249-257
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• 2017

The main focus when developing software is to improve the reliability and stability of a software system. We are enjoying a very comfortable life thanks to modern civilization, however, comfort is not guaranteed to us. Once software systems are introduced, the software systems used in the field environments are the same as or close to those used in the development-testing environment; however, the systems may be used in many different locations. Development of software system is a difficult and complex process. Generally, existing software reliability models are applied to software testing data and then used to make predictions on the software failures and reliability in the field. In this paper, we present an improved exponential NHPP software reliability model in different development environments, and examine the goodness-of-fit of improved exponential model and other model based on two datasets. The results show that the proposed model fits significantly better than other NHPP software reliability model.