• 대한안전경영과학회지
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• 제3권3호
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• pp.1-9
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• 2001

To keep an enterprise's competitiveness on the condition of the automatic manufacturing system such as FA, FMS and CIM, all the maintenance problems should be considered seriously In not only in production and maintenance but also in related industrial safety. As we analyze in the surveys the maintenance management of domestic enterprises and the causes of Industrial accident, there will be necessity of drawing up countermeasures for preventing industrial accidents and for ensuring expertise maintenance technologies. Based on these analyses, the safety information system, maintenance management information system, and the machinery condition diagnosis technique are studied by using of the knowledge-based system under the real-time computer-operating environment and using fuzzy linguistic variable. This computer system based knowledge-based diagnosis can easily provide not only the knowledge of expert system about deterioration phenomenon of industrial robots, but also the knowledge of relating safety and facility all the time. Therefore, it is expected to improve the efficiency of business processes in the production and safety when we use this system.

• 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.

• 한국CDE학회논문집
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• 제19권3호
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• pp.203-213
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• 2014

The O&M (Operation and Maintenance) phase of offshore plants with a long life cycle requires heavy charges and more efforts than the construction phase, and the occurrence of an accident of an offshore plant causes catastrophic damage. So previous studies have focused on design for reliability, and recently many studies have dealt with a maintenance system to prevent unexpected failures. Nowadays due to the emerging ICTs (Information Communication Technologies) and sensor technologies, it is possible to send health monitoring information of important equipment to administrator of an offshore plant in real time, which leads to having much concern on condition based maintenance policy or predictive maintenance. In this study, we have reviewed previous studies associated with condition-based maintenance of offshore plants, and introduced the approaches predicting failures of the compressor which is one of essential mechanical devices in LNG FPSO.

• 산업경영시스템학회지
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• 제37권4호
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• pp.12-23
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• 2014

The O&M (Operation and Maintenance) phase of offshore plants with a long life cycle requires heavy charges and more efforts than the construction phase, and the occurrence of an accident of an offshore plant causes catastrophic damage. So previous studies have focused on the development of advanced maintenance system to avoid unexpected failures. Nowadays due to the emerging ICTs (Information Communication Technologies) and sensor technologies, it is possible to gather the status data of equipment and send health monitoring data to administrator of an offshore plant in a real time way, which leads to having much concern on the condition based maintenance policy. In this study, we have reviewed previous studies associated with CBM (Condition-Based Maintenance) of offshore plants, and introduced an algorithm predicting the next failure time of the compressor which is one of essential mechanical devices in LNG FPSO (Liquefied Natural Gas Floating Production Storage and Offloading vessel). To develop the algorithm, continuous time Markov model is applied based on gathered vibration data.

• 품질경영학회지
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• 제49권3호
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• pp.299-312
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• 2021

Purpose: We provide a condition-based maintenance policy where a surrogate variable is used for monitoring system performance. We constructed a risk function by taking into account the risk and losses accompanied with erroneous decisions. Methods: Assuming a unique degradation process for the performance variable and its specific relationship with the surrogate variable, the maintenance policy is determined. A risk function is developed on the basis of producer's and consumer's risks accompanied with each decision. With a strategic safety factor considered, the optimal threshold value for the surrogate variable is determined based on the risk function. Results: The condition-based maintenance is analyzed from the point of risk. With an assumed safety consideration, the optimal threshold value of the surrogate variable is provided for taking a maintenance action. The optimal solution cannot be obtained in a closed form. An illustrative numerical example and solution is provided with a source code of R program. Conclusion: The study can be applied to situation where a sensor signal is issued if the system performance begins to degrade gradually and reaches eventually its functional failure. The study can be extended to the case where two or more performance variables are connected to a same surrogate variable. Also estimation of the distribution parameters and risk coefficients should be further studied.

• 한국ITS학회 논문지
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• 제18권4호
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• pp.80-95
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• 2019

최근 들어 센서 및 통신기술의 발달로 국내외 연구자들은 장비나 시스템의 상태정보를 수집하여 진단 및 예측 기법을 통한 유지보수를 결정하는 방법론에 대해 연구를 활발히 진행하고 있다. 본 연구에서는 이러한 연구 문헌 고찰을 통해 현시점의 차량부품 상태를 바탕으로 미래 시점까지의 차량부품 상태변화 추이를 예측하여 유지보수 의사결정을 수행하는 시스템 프레임워크를 제시하였다. 또한, 유지보수 활동에 따른 전과 후의 차량부품 상태변화 추적을 통해서 상태 진단 및 예측 데이터 조정이 가능하도록 구성하였다. 향후 본 연구 결과의 적용을 통해 대중버스를 이용하는 시민들의 안전과 차량의 상태기반 유지보수 체계 활성화에 조금이나마 기여할 수 있기를 기대한다.

• 한국항해항만학회지
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• 제46권6호
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• pp.562-569
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• 2022

기존 운항선박에 적용되어 있는 알람 모니터링 기술은 온도, 압력 등의 데이터 항목을 AMS(Alarm Monitoring System)으로 관리하고 해당 센싱 데이터가 정상 수준 범위를 초과할 경우만 선원에게 알람을 제공한다. 또한 기존 선박의 정비는 PMS(Planned Maintenance System)를 따른다. 이는 장비로부터 측정된 센싱 데이터가 설정범위 이상으로 측정되어 이에 따른 알람을 통해 정비하거나, 대상 기기의 고장 유무에 관계없이 일정 시간 사용 후 해당 부품을 사전에 교체하는 방식으로 운영되고 있다. 하지만 선박 기관운영의 신뢰성과 운항 안전성을 확보하기 위해서는 실시간 상태 모니터링 데이터 기반의 사전적 진단 및 예측이 가능해야 한다. 그러기 위해서 실선 데이터를 종합적으로측정하여 데이터베이스화 하고 이를 선박의 보조기기와 배관의 상태기반 예지보전을 위한 상태 진단 모니터링 시스템을 구현하고자 한다. 특히 반응형 웹 기반으로 선박의 보조기기와 배관 상태 정보를 관리할 수 있도록 하였으며, 선내 개인용 컴퓨터(Personal Computer, PC)에서 보는 용도뿐만 아니라 스마트폰 등 다양한 모바일 기기의 접근 및 활용이 가능하도록 화면과 해상도에 맞춰 최적화된 상태 관리가 가능하도록 하여 업데이트 비용이 적게 들며, 관리 방법도 쉽다. 본 논문에서는 자율운항선박 핵심 기술인 상태기반정비(Condition Based Management, CBM) 기술력을 확보하기 위해 선박의 보조기기 중 펌프와 청정기, 그리고 배관 중 해수 및 스팀 배관의 상태 진단 모니터링을 통해 이상 현상을 파악하고, 이를 통해 융합 분석할 수 있도록 선박 보조기기 및 배관의 성능 진단 및 고장 예측에 활용하여 예방정비 의사결정을 지원하고자 한다.

• 한국정밀공학회지
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• 제34권1호
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• pp.19-22
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• 2017

This paper describes the efficient equipment maintenance that can offer the exact time for repair and change of component in root industry. A conventional method offered the fixed time for repair and change of component because the method is based on early guarantee specification of the component. However the operating condition of manufacturing field is often under worse condition than early guarantee condition for high productivity. So, most components can't use until early guarantee time due to the operation of various different condition. Therefore we suggest the useful method for efficient equipment-maintenance by manufacturing-field analysis and feedback database. For this, the classification of root industry and related equipment is performed and then the detail classification of the process and component for equipment maintenance. And the monitoring module is also designed to gather data for feedback process and the environment is basically implemented for aging and reliability test.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2000년도 추계학술발표논문집
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• pp.181-185
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• 2000

• 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.