• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.4
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• pp.1-9
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• 2012

Decisions on reliability screening rules and burn-in policies are determined based on the estimated reliability. The variability in a semiconductor manufacturing process does not only causes quality problems but it also makes reliability estimation more complicated. This study investigates the nonuniformity characteristics of integrated circuit reliability according to defect density distribution within a wafer and between wafers then develops optimal burn-in policy based on the estimated reliability. New reliability estimation model based on yield information is developed using a spatial stochastic process. Spatial defect density variation is reflected in the reliability estimation, and the defect densities of each die location are considered as input variables of the burn-in optimization. Reliability screening and optimal burn-in policy subject to the burn-in cost minimization is examined, and numerical experiments are conducted.

• Journal of Information Technology Services
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• v.8 no.4
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• pp.129-140
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• 2009

The accurate estimation of software reliability is important to a successful development in software engineering. Until recent days, the models using regression analysis based on statistical algorithm and machine learning method have been used. However, this paper estimates the software reliability using support vector regression, a sort of machine learning technique. Also, it finds the best set of optimized parameters applying immune algorithm, changing the number of generations, memory cells, and allele. The proposed IA-SVR model outperforms some recent results reported in the literature.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.106.1-106
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• 2002

$\textbullet$ Current status of reliability estimation techniques for robot systems $\textbullet$ Description of Bayesian Belief Nets(BBN) With an example $\textbullet$ Description of proposed reliability estimation method which combines all information necessary $\textbullet$ Application example of the method : the reactor inspection robot $\textbullet$ Results from the reliability estimation of reactor inspection robot $\textbullet$ Discussion on the proposed method (advantages and problems) $\textbullet$ Conclusion

• Journal of the Korea Management Engineers Society
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• v.23 no.4
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• pp.159-164
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• 2018

Human-machine serial systems must be normal in both systems. Though the failure of machine is irreducible by itself, the human errors are of recurring type. When the human performance is described quantitatively, non-homogeneous Poisson Process model of human errors can be developed. And the model parameters can be estimated by maximum likelihood estimation and numerical analysis method. System reliability is obtained by multiplying machine reliability by human reliability.

• Journal of the Korean Data and Information Science Society
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• v.14 no.4
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• pp.1055-1065
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• 2003

We shall propose maximum likelihood, Bayesian and generalized maximum likelihood estimation for the reliability of the two-unit hot standby system with exponential lifetime distribution that switch is perfect. Each estimation will be compared numerically in terms of various mission times, parameter values and asymptotic relative efficiency through Monte Carlo simulation.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.10
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• pp.747-752
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• 2019

By using the failure information and the cumulative test execution time obtained by performing the reliability growth test, it is possible to estimate the parameter of the reliability growth model, and the Mean Time Between Failure (MTBF) of the product can be predicted through the parameter estimation. However the failure information could be acquired periodically or the number of sample data of the obtained failure information could be small. Because there are various constraints such as the cost and time of test or the characteristics of the product. This may cause the error of the parameter estimation of the reliability growth model to increase. In this study, the Bayesian method is applied to estimating the parameters of the reliability growth model when the number of sample data for the fault information is small. Simulation results show that the estimation accuracy of Bayesian method is more accurate than that of Maximum Likelihood Estimation (MLE) respectively in estimation the parameters of the reliability growth model.

• Smart Structures and Systems
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• v.11 no.1
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• pp.103-122
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• 2013

It is essential to update the model with reflecting observation or inspection data for reliability estimation of existing structures. Authors proposed updated reliability analysis by using Particle Filter. We discuss how to apply the proposed method through numerical examples on reinforced concrete structures after verification of the method with hypothetical linear Gaussian problem. Reinforced concrete structures in a marine environment deteriorate with time due to chloride-induced corrosion of reinforcing bars. In the case of existing structures, it is essential to monitor the current condition such as chloride-induced corrosion and to reflect it to rational maintenance with consideration of the uncertainty. In this context, updated reliability estimation of a structure provides useful information for the rational decision. Accuracy estimation is also one of the important issues when Monte Carlo approach such as Particle Filter is adopted. Especially Particle Filter approach has a problem known as degeneracy. Effective sample size is introduced to predict the covariance of variance of limit state exceeding probabilities calculated by Particle Filter. Its validity is shown by the numerical experiments.

• Journal of information and communication convergence engineering
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• v.16 no.1
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• pp.38-42
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• 2018

In this paper, we consider measurement allocation problem in a spatially correlated sensor field. Our goal is to determine the probability of each sensor's being measured based on its contribution to the estimation reliability; it is desirable that a sensor improving the estimation reliability is measured more frequently. We consider a spatial correlation model of a sensor field reflecting transmission power limit, noise in measurement and transmission channel, and channel attenuation. Then the estimation reliability is defined distortion error between event source and its estimation at sink. Motivated by the correlation nature, we model the measurement allocation problem into a cooperative game, and then quantify each sensor's contribution using Shapley value. Against the intractability in the computation of exact Shapley value, we deploy a randomized method that enables to compute the approximate Shapley value within a reasonable time. Besides, we envisage a measurement scheduling achieving the balance between network lifetime and estimation reliability.

• Journal of the Korean Society of Propulsion Engineers
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• v.22 no.5
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• pp.40-48
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• 2018

This paper presents a simulation-based design reliability estimation method of a low-energy exploding foil initiator (LEEFI) using a meta-model and describes the design reliability estimation results. The flyer velocity of the LEEFI is critical to initiate the explosive. Evaluation of the flyer velocity from mechanistic models in open literature requires a long computation time due to the multi-physical phenomena that generate the velocity. Moreover, the higher levels of confidence required for an initiator with high reliability incur higher computation costs. Thus, a meta-model of the flyer velocity over time was constructed in order to increase the computational efficiency for a reliable estimation. For different distributions and sigma levels of the design variables, the design reliability estimation results using the meta-model are provided. Additionally, the computational efficiency and accuracy of the estimation method are analyzed.

• The Journal of the Acoustical Society of Korea
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• v.41 no.4
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• pp.410-418
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• 2022

Channel reliability estimation for iterative codes such as turbo codes is very important factor in time varying underwater acoustic channel, an incorrect estimation of channel reliability induced performance degradation. Therefore, this paper presents an optimal channel reliability estimation method for turbo coded FSK signal with rate of 1/3. The estimated BER algorithm is a method that can estimate the reliability of received data by comparing received data and decoded data, and we determine optimal channel reliability by using the method. In order to analyze the performance, the experiment was conducted on a lake in Munkyeong city by moving in the range of 300 m to 500 m. At the result of applying presented method to failed decoding packets, we confirm all packets are decoded successfully.