• 한국정보통신학회논문지
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• 제23권7호
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• pp.869-874
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• 2019

노화에 의한 시스템의 예기치 않은 장애 발생은 예방 관리 기능을 수행함으로써 줄일 수 있으며, 이를 통해 시스템의 가용도를 높일 수 있다. 예방 관리 기법은 크게 시간 기반과 조건 기반의 두 가지로 나눌 수 있다. 시간 기반 방식은 정해진 시간 간격마다 수행되고, 조건 기반 방식은 시스템 상태가 특정 조건을 만족할 때 수행된다. 조건 기반 방식은 시간 기반 방식과 비교했을 때 예방 관리의 효율성을 향상시킬 수 있다는 장점이 있다. 본 논문은 노화 상태에서 일정 시간이 지난 후 예방 관리를 수행하게 되는 시스템을 분석할 수 있는 확률 모형을 제시한다. 제시한 모형은 현실적인 상황을 반영하여 비 마르코비안 모형으로 모델링한다. 해당 확률 모형을 수학적으로 해석하여 정상 상태에서의 시스템 가용도와 수익을 분석한다.

• 산업경영시스템학회지
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• 제17권30호
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• pp.73-79
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• 1994

This paper propose Adaptive Maintenance as a new type of maintenance for machine failures which are unpredictable. A purpose of adpative maintenance is to decrease inconsistency. In order to pick up some of problems the traditional maintenance policy, We discussed Time Based Maintenance(TBM) and Condition Based Maintenance(CBM) with Bath-Tub Curve. By using Machine Condition Diagnosis Technique (CDT), Monitored condition maintenance deals with the dynamic decision making for diagnosis procedures at maintenance and caution level. Adaptive Maintenance is a powerful tool for Total Production Maintenance(TPM).

• 한국신뢰성학회지:신뢰성응용연구
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• 제17권3호
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• pp.246-255
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• 2017

Purpose: This study proposes the optimal PM (preventive maintenance) policy of leased equipment for lessee's decision-making using two types of reliability condition. Methods: We consider reliability threshold based PM model. Equipment reliability is estimated and used as condition variable. The effect of repair for maintenance is imperfect and represented by age reduction factor. Results: We provide two PM policies. Policy 1 is focused on minimized total cost. This policy guarantees reliability threshold until last maintenance action. Policy 2 focus on maintaining reliability threshold during leased period. The proposed approach provides optimal reliability threshold under number of PM. Through result, we finally construct decision-making process for lessee using reliability threshold and end of reliability. Conclusion: This study provides two PM policy for lessee's decision-making. Through numerical example, we get a result of optimal reliability threshold, number of PM, optimum alternative under lessee's reliability condition.

• 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.

• 한국경영과학회지
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• 제27권2호
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• pp.33-49
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• 2002

CBM (Condition-Based Maintenance) has increasingly drawn attention in industry because of its many benefits. CBM Problem Is characterized as a state-dependent scheduling model that demands simultaneous maintenance actions, each for an attribute that influences on machine condition. This problem is very hard to solve within conventional Markov decision process framework. In this paper, we present an intelligent machine maintenance scheduler, for which a new incremental decision tree learning method as evolutionary system identification model and shortest path problem as schedule generation model are developed. Although our approach does not guarantee an optimal scheduling policy in mathematical viewpoint, we verified through simulation based experiment that the intelligent scheduler is capable of providing good scheduling policy that can be used in practice.

• 한국신뢰성학회지:신뢰성응용연구
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• 제18권2호
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• pp.114-121
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• 2018

Purpose: This study proposes a process for evaluating the preventive maintenance policy for a system with degradation characteristics and for calculating the appropriate preventive maintenance cycle using time- and condition-based maintenance. Methods: First, the collected data is divided into the maintenance history lifetime and degradation lifetime, and analysis datasets are extracted through preprocessing. Particle filter algorithm is used to estimate the degradation lifetime from analysis datasets and prior information is obtained using LSE. The suitability and cost of the existing preventive maintenance policy are each evaluated based on the degradation lifetime and by using a minimum repair block replacement model of time-based maintenance. Results: The process is applied to the degradation of the reverse osmosis (RO) membrane in a seawater reverse osmosis (SWRO) plant to evaluate the existing preventive maintenance policy. Conclusion: This method can be used for facilities or systems that undergo degradation, which can be evaluated in terms of cost and time. The method is expected to be used in decision-making for devising the optimal preventive maintenance policy.

• 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.

• 한국신뢰성학회지:신뢰성응용연구
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• 제18권2호
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• pp.104-113
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• 2018

Purpose: This paper proposes the non-periodic preventive maintenance policy based on the level of cumulative hazard intensity. We aim to construct a cost-effectiveness on the proposed model with relaxing the constraint on reliability. Methods: We use the level of cumulative hazard intensity as a condition variable, instead of reliability. Such a level of cumulative hazard intensity can derive the reliability which decreases as the frequency of preventive maintenance action increases. We also model the imperfect preventive maintenance action using the proportional age setback model. Conclusion: We provide a numerical example to illustrate the proposed model. We also analyze how the parameters of our model affect the optimal preventive maintenance policy. The results show that as long as high reliability is guaranteed, the inefficient preventive maintenance action is performed reducing the system operation time. Moreover, the optimal value of the proposed model is sensitive to changes in preventive maintenance cost and replacement cost.

• 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.