• Journal of Energy Engineering
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• v.20 no.2
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• pp.154-162
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• 2011

PMT(Preventive Maintenance Template) is a standardized maintenance program that describes maintenance items & period as operation condition to increase component reliability at the component level. The existing maintenance programs are focused on time based maintenance to inspect and repair component depend on fixed period. But recently, we have developed advanced maintenance program(named PMT) to increase reliability and optimize maintenance program of the plant significant component. This paper presents how to develop the PMT for nuclear power plant's static exciter.

• Proceedings of the Korean Reliability Society Conference
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• 2002.06a
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• pp.195-195
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• 2002

영광 원자력발전소 1,2호기의 계측제어기기에 대한 예방정비 최적화 분석을 수행중 기기의 정비주기 설정을 위하여 모델별 고장율 분석을 통하여 권고 주기를 산정 하였다. 현재 정비주기는 각 발전소 및 산업설비에서 제작사 지침의 적용과 현장 경험에 의한 선정이 이루어지고 있으나 제작사에 의한 주기 제시가 전체적으로 미미하여 경험에 크게 의존하고 있는 상태이다. 이에 본 논문에서는 정비주기의 최적화를 위하여 계측기 모델별 고장내용의 분석을 통한 data를 NCSL S2의 단순화 모델인 Jackson method를 기본으로 적용하여 최적주기 산정작업을 수행한 사례를 기술하고자 한다.

• Plant Journal
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• v.9 no.4
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• pp.37-42
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• 2013

Power plants have many components and equipment. It is difficult for operators to know the each equipment fails or what equipment fails. It is important to prevent failure in advance. Recently, outlook of maintenance tasks is changing from time based maintenance to condition based maintenance. In this study, we selected RCM-based maintenance intervals for coal handling equipment at coal power plant. For RCM analysis, we have made great progress in a maintenance task and interval. If we apply RCM analysis to the whole plant system, we can expect qualitative improvement and efficient operation of power plant system.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.927-932
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• 2005

전투기를 적절히 정비하는 활동은 공군력을 유지하는데 중요하다. 일반적인 정비정책은 정해진 일정으로 주요 모듈의 정비를 수행한다. 그러나, 이러한 정비활동은 시간에 따라 변하는 모듈의 특성을 반영할 수 없다. 이에 본 연구는 변동되는 평균 고장간 시간 (MTBF) 과 평균 수리 시간 (MTTR)을 산출할 수 있는 확률효과회귀모형을 이용하여 시간에 따라 변동되는 모듈의 특성을 반영한 동적 예방정비 주기를 예측하고자 한다. 본 연구의 결과는 대한민국 공군의 전투 준비 태세 향상에 이바지 할 것으로 기대된다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.9
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• pp.1325-1330
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• 2010

The breakdown of any critical component of a turbine results in the outage of power plants. Unexpected failure decreases equipment utilization and causes enormous economic losses. Currently, we conduct conservative preventive maintenance for a maintenance period that is proposed by a vendor. In the rapidly changing business environment, reliability-based maintenance is required in order to remain competitive and reduce maintenance costs while maintaining the reliability of equipment. In order to determine an appropriate maintenance period for guaranteeing reliability, we must determine the failure probability by carefully analyzing the failure history of the equipment. In this study, we created a database of failure history for power-plant turbines, predicted the best repair time using the Weibull function, and investigated how the appropriate maintenance cycle can be determined.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8700-8706
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• 2015

The first driving device of the power bogies for the Korean high-speed railway vehicle consists of the traction motor (TM) and the motor reduction gears unit (MRU). Although TM and MRU are the mechanically integrated structures, their time between overhauls (TBO) have two separate intervals due to different technical requirements(i.e. TBO of MRU: $1.8{\times}10^6km$, TBO of TM: $2.5{\times}10^6km$). Therefore, to reduce the unnecessary number of preventive maintenances, it is important to evaluate the optimal TBO with a viewpoint of reliability-center maintenance towards cost-effective solution. In this study, derived from the field data in maintenance, fault tree analysis and failure rate of the subsystem considering criticality of the components are evaluated respectively. To minimize the conventional total maintenance cost, the same optimal TBO of the components is derived from genetic algorithm considering target reliability and improvement factor. In this algorithm, a chromosome which comprised of each individual is the minimum preventive maintenance interval. The fitness function of the individual in generation is acquired through the formulation using an inverse number of the total maintenance cost. Whereas the lowest common multiple method produces only a four percent reduction compared to what the existing method did, the optimal TBO of them using genetic algorithm is $2.25{\times}10^6$km, which is reduced to about 14% comparing the conventional method.

• Journal of the Korean Society for Railway
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• v.20 no.5
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• pp.569-576
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• 2017

The electromagnetic valve of pneumatic doors of EMUs has a high failure rate due to air leakage because it supplies air on and off to operate the doors repeatedly. The electromagnetic valve is a very important safety component for which a very high reliability is required because failure makes it impossible to operate the passenger cars. However, domestic urban railway operators maintain electronic valves of the EMU door under a fixed cycle with a spare period according to the full overhaul cycle of the EMU. An improvement of the current maintenance cycle was suggested based on the reliability function and mission reliability. Using the statistical program MINITAB for the operational data of EMU line 6, we analyzed the characteristics of the fault distribution and derived the shape and scale parameters of the reliability function. If we limit the specific reliability probability to under a certain failure rate and calculate its statistical parameters, we can calculate the allowable inspection period with mission reliability. Through this study, we suggested a maintenance period based on RCM (reliability centered-maintenance) to improve the reliability of electromagnetic valves from 68% to 95%.

• Journal of the Korea Society for Simulation
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• v.20 no.4
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• pp.127-138
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• 2011

Certified Missile Round Concepts that is one-shot device use the periodic inspection policy to improve the continuously deteriorated reliability. In this paper, we suggest dormant reliability prediction model by simulation with real operational environment. The suggested prediction model is based on optimal inspection period decision model and additionally considers various constraints; moving, inspection or repair service time. The simulation results show the constraints affect dormant reliability and missile availability. Lastly, we suggest building up a depot to resolve the above problems by the suggested simulation model.

• Journal of the Korean Society of Propulsion Engineers
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• v.21 no.3
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• pp.91-100
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• 2017

The solution was developed for the maintenance decision support of combined cycle power plant gas turbine. The developed solution was applied to MHI501G gas turbine and is, in present, on the process of field test at GUNSAN combined cycle power plant, South Korea. The developed solution provides the calculated result of optimal overhaul maintenance period through following modules: Real Time Performance Monitoring, Model-Based Diagnostics, Performance Trend Analysis, Optimal Overhaul Maintenance Interval, Compressor Washing Period Management, and Blade Path Temperature Analysis. Model-Based Diagnostics module analyzed the differences between the data of gas turbine performance model and the online measurement. Compressor washing management module suggests the optimal point of balancing between the compressor performance and the maintenance cost.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.10
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• pp.82-88
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• 2018

The decoy defensive weapon system is a one-shot system. Reliability is maintained through periodic inspection and high reliability is required to confirm whether or not the functioning is normal after launch. The maintenance cycle of a decoy was set up without target reliability and reliability prediction during the development period. However, the number of operations in the military has been increasing, necessitating the optimization of the maintenance cycle. Reliability is analyzed using the maintenance data of a decoy operated for several decades and the optimal maintenance cycle is suggested. In chapter 2, data collection and classification methods are presented and analysis methodology is briefly introduced. In chapter 3, the data distribution analysis and fitness verification confirmed that applying the Weibull distribution is the most suitable for the maintenance data of the decoy. In chapter 4, we present the analysis result of percentile, survival probability and MTBF and the optimal maintenance cycle was derived from the reliability analysis. Finally, we suggest the application methods for this paper in the future.