• Journal of Korean Society of Industrial and Systems Engineering
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• v.17 no.30
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• pp.147-151
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• 1994

In this paper, we presents the prediction of failure point in facility by using the analysis of the failure symptoms. The status of a component is represented by the failure symptoms where as, the failure symptoms are expressed mathematically based on the Fuzzy Theory.

• Proceedings of the Korean Reliability Society Conference
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• 2004.07a
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• pp.183-190
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• 2004

Found important components in terms of frequency in the assembly (but not in terms of money). Component 39*** was most important. The failure mode was N69(no light on warning signal the cause of the failure was C15(bad connection). Formed a population for each component. Performed reliability and warranty cost analyses At the component level. At the subsystem level. At the system level. **They don'l trust the warranty cost analysis.** Reliability improvement. Among all the subsystems front \ulcorner subsystem is most vulnerable (among other things due to the large number of components in it), especially components 39*** and 28***.

• Journal of Applied Reliability
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• v.10 no.1
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• pp.1-9
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• 2010

In general, the performance of a component degrades as time goes by and failure of a component occurs when the performance degradation reaches a pre-specified level. It is difficult to obtain the failure time distribution data or the necessary number of failure data especially for the metal or machine part. Thus, a design of reliability qualification test based on performance distribution is more effective than failure time distribution. In this study, a performance-based reliability qualification test is developed and a numerical example is provided to illustrate the use of the developed reliability qualification test. This approach could be applied to many kinds of metal or machine part whose magnitude of strength could not be evaluated during at any random points but judgement can be made by only failure of the part. Besides, it is also possible that any parts which have a similar failure characteristics could be applicable to the developed reliability qualification test.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1992.10a
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• pp.325-329
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• 1992

The development of automatic production system have required intelligent diagnostic and monitoring function to repair system failure and reduce production loss by the failure. In order to perform accurate functions of intelligent system, inference about total system failure and fault analysis due to each mechanical component failures are required. Also the solution about repair and maintenance can be suggested from these analysis results. Generally, bearing is a essential mechanical component in the machinery. The bearing failure is caused by lubricant system failure, metallurgical defficiency, mechanical condition(vibration overloading misalignment), environmental effect. This study described roller bearing fault train due to stress variation and metallurgical defficiency from lubricant failure by using FTA.

• Earthquakes and Structures
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• v.13 no.4
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• pp.409-419
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• 2017

In order to analyze the vibration control effect of viscous damper in the concrete archaized buildings with lintel-column joints under seismic action, 3 specimens were tested under dynamic excitation. Two specimens with viscous damper were defined as the controlled component and one specimen without viscous damper was specified as the non-controlled component. The loading process and failure patterns were obtained from the test results. The failure characteristics, skeleton curves and mechanical behavior such as the load-displacement hysteretic loops, load carrying capacity, degradation of strength and rigidity, ductility and energy dissipation of the joints were analyzed. The results indicate that the load-bearing capacity of the controlled component is significantly higher than that of the non-controlled component. The former component has an average increase of 27.4% in yield load and 22.4% in ultimate load, respectively. Meanwhile, the performance of displacement ductility and the ability of energy dissipation for the controlled component are superior to those of the non-controlled component as well. Compared with non-controlled component, equivalent viscous damping coefficients are improved by 27.3%-30.8%, the average increase is 29.0% at ultimate load for controlled component. All these results reflect that the seismic performance of the controlled component is significantly better than that of the non-controlled component. These researches are helpful for practical application of viscous damper in the concrete archaizing buildings with lintel-column joints.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.194-202
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• 2019

Reliability analysis of the components frequently starts with the data that manufacturer provides. If enough failure data are collected from the field operations, the reliability should be recomputed and updated on the basis of the field failure data. However, when the failure time record for a component contains only a few observations, all statistical methodologies are limited. In this case, where the failure records for multiple number of identical components are available, a valid alternative is combining all the data from each component into one data set with enough sample size and utilizing the useful information in the censored data. The ROK Navy has been operating multiple Patrol Killer Guided missiles (PKGs) for several years. The Korea Multi-Function Control Console (KMFCC) is one of key components in PKG combat system. The maintenance record for the KMFCC contains less than ten failure observations and a censored datum. This paper proposes a Bayesian approach with a Dirichlet mixture model to estimate failure time density for KMFCC. Trends test for each component record indicated that null hypothesis, that failure occurrence is renewal process, is not rejected. Since the KMFCCs have been functioning under different operating environment, the failure time distribution may be a composition of a number of unknown distributions, i.e. a mixture distribution, rather than a single distribution. The Dirichlet mixture model was coded as probabilistic programming in Python using PyMC3. Then Markov Chain Monte Carlo (MCMC) sampling technique employed in PyMC3 probabilistically estimated the parameters' posterior distribution through the Dirichlet mixture model. The simulation results revealed that the mixture models provide superior fits to the combined data set over single models.

• Journal of Korean Society for Quality Management
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• v.25 no.3
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• pp.96-107
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• 1997

The recent stream to reliability prediction is that it is totally inclusive in depth to consider even the operating and environmental condition at the level of finished goods as well as component itselves. In this study, firstly we present the reliability prediction methods by entire failure rate model which failure rate at the system level is added to the failure rate model at the component level. Secondly we build up the improved bases of reliability demonstration through a, pp.ication of Kaplan-Meier, Cumulative hazard, Johnson's methods as non-parametric and Maximum Likelihood Estimator under exponential & Weibull distribution as parametric. And also present the methods of curve fitting to piecewise failure rate under Weibull distribution, PRST (Probability Ratio Sequential Test), curve fitting to S-shaped reliability growth curve, computer programs of each methods. Lastly we show the practical for determination of optimal burn-in time as a method of reliability enhancement, and also verify the practical usefulness of the above study through the a, pp.ication of failure and test data during 1 year.

• Proceedings of the Korean Nuclear Society Conference
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• 1997.10a
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• pp.244-250
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• 1997

The mean time to failure (MTTF) expressing the mean value of the system life is a measure of system effectiveness. To estimate the remaining life of component and/or system, the dynamic mean time to failure concept is suggested. It is the time-dependent Property depending on the status of components. The Kalman filter is used to estimate the reliability of components using the on-line information (directly measured sensor output or device-specific diagnostics in the intelligent sensor) in form of the numerical value (state factor). This factor considers the persistency of the fault condition and confidence level in measurement. If there is a complex system with many components, each calculated reliability's or components are combined, which results in the dynamic MTTF or system. The illustrative examples are discussed. The results show that the dynamic MTTF can well express the component and system failure behaviour whether any kinds of failure are occurred or not.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.2
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• pp.273-281
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• 2007

The decision of how long performing system burn-in must be answered with a probabilistic model of a system lifetime at which infant mortality failures created during assembly processes are quantified. In this paper, we propose such a model which is modified from previous results. Using the system model, we derived system reliability in terms of component and system burn-in times for the two cases of minimal repair at system failure and of component replacement and connection repair at their failure times. The procedure is illustrated with a bridge system and the optimal system burn-in times are obtained for maximizing system reliability. The result suggests that an assumption of minimal repair at system failure may underestimate the optimal burn-in time in practice.

• Journal of the Korean Society of Safety
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• v.35 no.1
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• pp.18-24
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• 2020

This research conducted an the failure analysis was performed based on the failure and operation data for Seven years using the Reliability, Availability, Maintainability, and Safety(RAMS) constructed at the operation stage after the opening of the D urban railway. therefore, the risk priority was selected for failure frequency component within the door system that showed high failure. Finally, the goal was to suggest ways to improve the door system. For this purpose, the analysis of thermal characteristics of failed components such as Door Control Unit(DCU) in the door system based on the Seven-year failure analysis data of RAMS was performed. These results were applied to the main component exchange cycle of the door unit, the mean time between failure(MTBF) and mean kilometer between failure(MKBF) values of RAMS increased by 26% in 2017-2018 when the improvement measures were taken, and the MTBF value of DCU was 300,000 hours, which was a 57% improvement in reliability. The results of this thesis identify potential enhancements in reliability and improvements in maintenance of the door system that, if implemented, would contribute to train safety and reduce instances of failure in the future.