• The KIPS Transactions:PartA
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• v.13A no.5 s.102
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• pp.421-428
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• 2006

This paper proposes an integrated recovery approach applying retry and rollback techniques to recover the TMR failure. Combining the time redundancy techniques with W system is apparently effective to recover the TMR failure(or masked error) primarily caused by transient faults. These policies need fewer reconfigurations at the cost of extra time required for the time redundant schemes. The optimal numbers of retry and rollback to minimize the mean execution time of tasks are derived for the proposed method through computing the likelihoods of all possible states of the failed system. The effectiveness of the proposed method is validated through examining certain numerical examples and simulations conducted with a variety of parameters governing environmental characteristics.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.2
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• pp.26-37
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• 2003

An optimal software release, which is related to the development cost, error detection and correction under the various operation systems, is a critical factor for managing project. This paper described optimal software release issues to predict the release time of large switching system with the system stability point of view and evaluated a timely supply of target system, proper utilization of resources under the software reliability valuation basis. Finally, Using initial failure data, based on the exponential reliability growth model methodology, optimal release time, and analysis of failure data during the system testing and managing methodologies were presented.

• Journal of the Korean Society of Visualization
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• v.19 no.1
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• pp.62-67
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• 2021

Selective catalytic reduction(SCR) is an exhaust gas reduction device to remove nitro oxides (NOx). SCR operation of ship can be controlled through valves for minimizing economic loss from SCR. Valve in SCR-high pressure (HP) system is directly connected to engine exhaust and operates in high temperature and high pressure. Long-term thermal deformation induced by engine heat weakens the sealing of the valve, which can lead to unexpected failures during ship sailing. In order to prevent the unexpected failures due to long-term valve thermal deformation, a failure prediction system using autoregressive integrated moving average (ARIMA) was proposed. Based on the heating experiment, virtual data mimicking temperature range around the SCR-HP valve were produced. By detecting abnormal temperature rise and fall based on the short-term ARIMA prediction, an algorithm determines whether present temperature data is required for failure prediction. The signal processed by the data collection algorithm was interpolated for the failure prediction. By comparing mean average error (MAE) and root mean square error (RMSE), ARIMA model and suitable prediction instant were determined.

• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.411-425
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• 2021

Accelerated failure time (AFT) model represents a linear relationship between the log-survival time and covariates. We are interested in the inference of covariate's effect affecting the variation of survival times in the AFT model. Thus, we need to model the variance as well as the mean of survival times. We call the resulting model mean and variance AFT (MV-AFT) model. In this paper, we propose a variable selection procedure of regression parameters of mean and variance in MV-AFT model using penalized likelihood function. For the variable selection, we study four penalty functions, i.e. least absolute shrinkage and selection operator (LASSO), adaptive lasso (ALASSO), smoothly clipped absolute deviation (SCAD) and hierarchical likelihood (HL). With this procedure we can select important covariates and estimate the regression parameters at the same time. The performance of the proposed method is evaluated using simulation studies. The proposed method is illustrated with a clinical example dataset.

• International Journal of Reliability and Applications
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• v.7 no.2
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• pp.111-125
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• 2006

This paper introduces different vectors of the reliability equivalence factors of a series system consists of n independent and nonidentical components. The failure rates of the system components are assumed to be constant. The reliability function and mean time to failure are used as performances to derive the reliability equivalences of the system. The results presented here generalize those available in the literatures. Numerical study is given to explain how one can utilize the theoretical results obtained.

• Proceedings of the KSR Conference
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• 1998.05a
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• pp.194-202
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• 1998

This paper shows two models of the duplex system having a fault tolerant system characteristic used in airplane and railway system. The architecture of these systems is based on Mc68000, and we designed the single system, single duplex system, dual system and dual duplex system to evaluate the system characteristic. We calculate the failure rate of components using MIL-SPEC-2l7F and evaluate the reliability, avaliability, safety and MTTF(Mean Time To Failure) of the designed systems by Markov model. We choose our system depending on the developing system characteristic.

• 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.

• 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.

• Journal of the Korean Society of Safety
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• v.23 no.2
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• pp.37-44
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• 2008

The safety assessment for facility industry is now being periodically performed. For the purpose of scientific safety management, QRA(Quantitative Risk Assessment) is also being performed, and reliability data of the facilities is essential to perform the assessment. Generally, the existing safety assessment is performed by using the values announced in other industry processes, which result in the drop of reliability. In order to solve this problem, there is an urgent need to establish reliability database for the facilities. The most appropriate method is to perform a direct reliability analysis towards the facilities undergoing safety assessment. In this study, in compliance with the assessment method and procedure of OREDA-2002 handbook, the facility reliability data are collected, which include the calendar time and operational time in terms of different facility items, the number of failures in terms of different failure mode, the mean, standard deviation, lower limit and upper limit of failure rate, and the failure rate. And the data process method for this special occasion is also proposed when the number of failure is 0.

• IE interfaces
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• v.1 no.2
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• pp.67-74
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• 1988

MTBF (Mean Time Between Failures) is one of the measures to express the reliability for a repairable system, especially for a military weapon system. But MTBF is meaningless without a clear definition of the system failures. In this paper we discuss two failure definitions, one is defined by US Army Training and Doctrine Command jointly with US Army Materiel Command and the other one is used to M1 Tank.