• Journal of Advanced Marine Engineering and Technology
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• v.24 no.2
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• pp.90-96
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• 2000

The technology of preventive maintenance and corrective maintenance is widely applied to ships in order to maintain the good voyageable condition. One of the most important fields of marine engineering is to seek the maximum availability and to solve the stochastic maintenance problem such that the cost for corrective maintenance is minimized. Accordingly, for the purpose of making the most suitable maintenance schedule which minimizes the expected cost function, this paper suggests the method to grasp the failure characteristics by the ship's maintenance data that are collected from the past. And, suggests the method to estimate the optimal maintenance interval by using the dynamic programming and the cumulative hazard rate function attained from the maintenance data.

• 연구논문집
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• s.32
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• pp.35-43
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• 2002

This study was performed to develop accelerated life test method of machanical parts using cumulative damage theory that used to model the fatigue of parts that receive variable load. The cumulative damage theory was introduced, and the estimation of life and calculation of accelerated life test time was illustrated. As the actual application example, accelerated life test method of agricultural tractor transmission was described. Life distribution of agricultural tractor transmission was supposed to follow Weibull distribution and life test time was calculated under the conditions of average life (MTBF) 3,000 hours and 90% reliability for one test sample. According to the cumulative damage theory, because test time can shorten in case increase test load, test time could be reduced by 482 hours when we put the load 1.1 times of rated load than 0.73 times of rated load that is equivalent load calculated by load spectrum of the agricultural tractor. This time, acceleration coefficient was 11.7. This accelerated test method was used to develop accelerated test method of gear reducer, hydraulic hose and bearing as well as agricultural tractor transmission and it is considered to be applied comprehensively to machanical parts the fatigue of which is happened by load or pressure etc.

• Journal of Biosystems Engineering
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• v.34 no.5
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• pp.325-330
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• 2009

This study was performed to develop accelerated life test methods for agricultural tractor transmission receiving variable load. To acquire parameters for calculation of accelerated life test, endurance tests were performed under different torque conditions. Test results showed that the shape factor of Weibull distribution was 1.5 and fatigue damage exponent was 5.4. The calculated test time was 5,877 hours under the conditions of average life (MTBF) 3,000 hours and 90% reliability for one test sample. According to the linear cumulative damage rule, test time could be reduced using increased test load. Test time could be reduced by 252 hours when 1.2 times of the rated load compared with 0.67 times of the rated equivalent load calculated by load spectrum of the agricultural tractor. Calculated acceleration coefficient was 23.3.

• International Journal of Reliability and Applications
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• v.4 no.1
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• pp.1-12
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• 2003

Many software reliability growth models (SRGM's) based on a nonhomogeneous Poisson process (NHPP) have been proposed by many researchers. Most of the SRGM's which have been proposed up to the present treat the event of software fault-detection in the testing and operational phases as a counting process. However, if the size of the software system is large, the number of software faults detected during the testing phase becomes large, and the change of the number of faults which are detected and removed through debugging activities becomes sufficiently small compared with the initial fault content at the beginning of the testing phase. Therefore, in such a situation, we can model the software fault-detection process as a stochastic process with a continuous state space. In this paper, we propose a new software reliability growth model describing the fault-detection process by applying a mathematical technique of stochastic differential equations of an Ito type. We also compare our model with the existing SRGM's in terms of goodness-of-fit for actual data sets.

• 한국신재생에너지학회:학술대회논문집
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• 2005.11a
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• pp.693-697
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• 2005

This study was performed to develop accelerated life test method of the wind-turbine gearbox using accumulated damage theory that used to model the fatigue of parts that receive variable load. The accumulated damage theory was introduced, and the estimation of life and calculation of accelerated life test time was illustrated. As the actual application example, accelerated life test method of the gearbox was described. Life distribution of the wind-turbine gearbox was supposed to follow Weibull distribution and life test time was calculated under the conditions of average life (MTBF) 140,600 hours and 99% reliability for one test sample According to the accumulated damage theory, because test time can shorten in case increase test load, test time could be reduced by 1.2 years when we put the load 1.2 times of rated load than 0.93 times of rated load that is equivalent load calculated by load spectrum of the wind turbine. This time, acceleration coefficient was 21.3. This accelerated test method was used to develop accelerated test method of gear reducer, gear and bearing as well as the industrial gearbox and it is considered to be applied comprehensively to mechanical parts the fatigue of which is happened by load or pressure etc.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.445-450
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• 2003

This study was performed 10 develop the accelerated life test method using Weibull-IPL(Inverse Power Law) model for mechanical components. Weibull-IPL model is concerned with determining the assurance life with confidence level and the accelerated life test time From the relation of weibull distribution factors and confidence limit, the testing times on the no number of failure acceptance criteria arc determined. The mechanical components generally represent wear and fatigue characteristics as a failure mode. IPL based on the cumulative damage theory is applied effectively the mechanical components to reduce the testing time and to achieve the accelerating test conditions. As the actual application example, accelerated life test method of agricultural tractor transmission was described. Life distribution of agricultural tractor transmission was supposed to follow Weibull distribution and life test time was calculated under the conditions of average life (MTBF) 3,000 hours and 90% confidence level for one test sample. According to IPL, because test time call be shorten in case increase test load test time could be reduced by 482 hours when we put the load 1.1 times of rated load than 0.73 times of rated load that is equivalent load calculated by load spectrum of the agricultural tractor. This time, acceleration coefficient was 11.7.

• 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.