• 한국철도학회:학술대회논문집
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• 한국철도학회 2010년도 춘계학술대회 논문집
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• pp.1177-1190
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• 2010

The high-speed railway track occurs train operating result track irregularity, subsidence of the track, ballast abrasion. This is the unusual condition. High-speed railway track maintenance task is the behavior which repairs unusual section by using the human resource or machine resource. The resource used to maintenance task is restrictive. A resource can be efficiently used if the high-speed railway track maintenance scheduling is used. So the more task can be performed in the fit time. In conclusion, this manages the unusual condition of a track efficiently. So additional expenses is minimized cause by deteriorating unusual condition. And it offers comfortable ride to passenger. However, maintenance scheduling has to reflect well practical situation and environment. That's maintenance scheduling is used. We gather the opinions of the hands-on workers. So in this paper define field situation and condition. And suggest mathematical model about this. And we developed the track maintenance scheduling software engine using ILOG.

• 전기학회논문지
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• 제57권8호
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• pp.1305-1310
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• 2008

Traditional maintenance planning is based on a constant maintenance interval for equipment life. In order to consider economic aspect for time based preventive maintenance, preventive maintenance is desirable to be scheduled by RCM(Reliability-Centered Maintenance) evaluation. The main objective of RCM is to reduce the maintenance cost, by focusing on the most important functions of the system and avoiding or removing maintenance actions that are not strictly necessary. So, Markov state model is utilized considering stochastic state in RCM. In this paper, a Markov state model which can be used for scheduling and optimization of maintenance is presented. The deterioration process of system condition is modeled by the stepwise Markov model in detail. Also, because the system is not continuously monitored, the inspection is considered. In case study, simulation results about RCM will be shown using the real historical data of combustion turbine generating unit in Korean power systems.

• Journal of Computational Design and Engineering
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• 제2권2호
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• pp.119-127
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• 2015

In the case of a high-valuable asset, the Operation and Maintenance (O&M) phase requires heavy charges and more efforts than the installation (construction) phase, because it has long usage life and any accident of an asset during this period causes catastrophic damage to an industry. Recently, with the advent of emerging Information Communication Technologies (ICTs), we can get the visibility of asset status information during its usage period. It gives us new challenging issues for improving the efficiency of asset operations. One issue is to implement the Condition-Based Maintenance (CBM) approach that makes a diagnosis of the asset status based on wire or wireless monitored data, predicts the assets abnormality, and executes suitable maintenance actions such as repair and replacement before serious problems happen. In this study, we have addressed several aspects of CBM approach: definition, related international standards, procedure, and techniques with the introduction of some relevant case studies that we have carried out.

• KNOM Review
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• 제24권1호
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• pp.13-19
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• 2021

최근 산업 분야에서는 공장 자동화 뿐만 아니라 장애 진단/예측을 통해 고장/사고를 사전에 방지하여 생산량을 극대화하기 위한 연구가 진행되고 있으며, 이를 구성하기 위해 많은 양의 데이터 축적을 위한 클라우드 기술, 데이터 처리를 위한 빅 데이터 기술, 그리고 데이터 분석을 쉽게 진행하기 위한 AI(Artificial Intelligence)기술이 도입되고 있다. 또한 최근에는 장애 진단/예측의 발전으로 인해 설비 유지보수(PM: Productive Maintenance) 방식도 정기적으로 설비를 유지보수 하는 방식인 TBM(Time Based Maintenance)에서 설비 상태에 따라 유지보수 하는 방식인 CBM(Condition Based Maintenance)을 조합하는 방식으로 발전하고 있다. CBM 기반 유지보수를 수행하기 위하여 설비의 상태(condition)의 정의와 분석이 필요하다. 따라서 본 논문에서는 머신 러닝(Machine Learning) 기반의 장애 진단을 위한 시스템 및 데이터 모델(Data Model)을 제안하며, 이를 기반으로 장애를 사전 예측한 사례를 제시하고자 한다.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2011년도 춘계학술대회 논문집
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• pp.1612-1617
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• 2011

Rolling stock needs many maintenance works because of its long service life. The maintenance of rolling stock has periodic preventive maintenance system. This periodic preventive maintenance system can't reflect the characteristics of every part. The condition-based maintenance system which reflects the functional condition of every part prevents breakdown and reduces maintenance cost. This study will analyze the records of every part by unreasonable examples of time-based preventive maintenance and reliability management activities, and discuss the necessity of maintenance system reflected the results.

• 시스템엔지니어링학술지
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• 제18권1호
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• pp.1-13
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• 2022

The Yongin Light Rail train was manufactured by Bombardier Transportation in Canada in 2008 and is a privately invested railway line that has been operating in Yongin-si, Gyeonggi-do, since 2013. When the frequency of train failure increases due to aging, and there is a delay in the delivery period of imported parts used in the Bombardier manufactured trains, timely vehicle maintenance may not be performed due to lack of parts. To solve this problem, it is necessary to build a 'vehicle parts maintenance demand forecasting system' that analyzes the accurate and actual maintenance demand annual based on the condition of vehicle parts. The full scope of analysis in this paper analyzes failure data from various angles after opening of Yongin light rail vehicle to analyze failure patterns for each part and identify replacement cycles according to possible failures and consumption of parts. Based on this study, it is expected that Yongin Light Rail's maintenance system will change from the existing time-based replacement (TBM) concept to the condition-based maintenance (CBM) concept. It is expected that this study will improve the efficiency of the Yongin Light Rail maintenance system and increase vehicle availability. This paper is a fundamental for establishing of a system for predicting the replacement timing of vehicle parts for Yongin Light Rail. It reports the results of data analysis on some vehicle parts.

• Nuclear Engineering and Technology
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• 제46권6호
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• pp.737-752
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• 2014

As condition-based maintenance (CBM) has risen as a new trend, there has been an active movement to apply information technology for effective implementation of CBM in power plants. This motivation is widespread in operations and maintenance, including monitoring, diagnosis, prognosis, and decision-making on asset management. Thermal efficiency analysis in nuclear power plants (NPPs) is a longstanding concern being updated with new methodologies in an advanced IT environment. It is also a prominent way to differentiate competitiveness in terms of operations and maintenance costs. Although thermal performance tests implemented using industrial codes and standards can provide officially trustworthy results, they are essentially resource-consuming and maybe even a hind-sighted technique rather than a foresighted one, considering their periodicity. Therefore, if more accurate performance monitoring can be achieved using advanced data analysis techniques, we can expect more optimized operations and maintenance. This paper proposes a framework and describes associated methodologies for in-situ thermal performance analysis, which differs from conventional performance monitoring. The methodologies are effective for monitoring, diagnosis, and prognosis in pursuit of CBM. Our enabling techniques cover the intelligent removal of random and systematic errors, deviation detection between a best condition and a currently measured condition, degradation diagnosis using a structured knowledge base, and prognosis for decision-making about maintenance tasks. We also discuss how our new methods can be incorporated with existing performance tests. We provide guidance and directions for developers and end-users interested in in-situ thermal performance management, particularly in NPPs with large steam turbines.

• International Journal of Reliability and Applications
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• 제2권1호
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• pp.57-71
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• 2001

Global competition to increase production output and to improve quality is spurring manufacturing companies to use condition monitoring and fault diagnostic systems for predictive maintenance. As monitoring, testing, and measuring techniques develop, predictive control of components and complete systems have become more practical and affordable. In this article, we will consider the computer based data acquisition system for condition monitoring and the condition parameter analysis techniques for fault detection and diagnostics in the machinery and briefly discuss reliability prediction and the limit value determination in condition monitoring.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 춘계학술대회논문집
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• pp.453-456
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• 2007

The purpose of this study is to explain the importance of Vibration Monitoring Device by introducing an example of Predictive Maintenance System using Condition Monitoring System of Hydro-turbine generator. Confirming vibration of generation equipment is commissioning procedure during equipment completion for checking guaranteed items. Data from Generator output range are used to determine output band to continue the performance of equipment. The Vibration Monitoring System is not absolute method of maintenance, but if it is used well with expert, it will be visible, data-analyzed, scientific maintenance more than others. And also, Condition Monitoring System is very important for remote controlled small hydro-power plant although most of it is installed in Large hydro-power plant.

• 유체기계공업학회:학술대회논문집
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• 유체기계공업학회 2006년 제4회 한국유체공학학술대회 논문집
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• pp.57-60
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• 2006

The purpose of this study is to explain the importance of Vibration Monitoring Device by introducing an example of Predictive Maintenance System using Condition Monitoring System of Hydro-turbine generator. Confirming vibration of generation equipment is commissioning procedure during equipment completion for checking guaranteed items. Data from Generator output range are used to determine output band to continue the performance of equipment. The Vibration Monitoring System is not absolute method of maintenance, but if it is used well with expert, it will be visible, data-analyzed, scientific maintenance more than others. And also, Condition Monitoring System is very important for remote controlled small hydro-power plant although most of it is installed in Large hydro-power plant.