• International Journal of Railway
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• v.9 no.1
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• pp.10-14
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• 2016

Life cycle cost analysis is compulsively required for the system operation. System operation costs are consisted of acquisition, operation, maintenance and so on. In the beginning of the system planning, we need to take into account of various costs following the system operating. To implement LCC, we need to analyze system life cycle to identify all costs during system life. The costs can be divided into three parts. The first part is purchasing cost, the second for operating cost and the last for disposal cost. The second operating cost can be decomposed of operating cost included labor, energy consumption cost for system running, maintenance costs to keep systems healthy, delay cost caused from maintenance and hazard cost, and so on. In this paper, we carried out for railway locomotives which operate over more 30years and which cost about 10 million USD. We decompose the life cycle of the locomotives and break down the locomotives into subsystems to require maintenance or not, and subsystems to need energy or not. We showed how to decide optimal locomotives through cost identification and system breakdown.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.357-361
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• 2022

Employing the available technologies and utilizing the advanced means to improve the level of health care provided to citizens in their various locations. Citizens have the right to get a proper health care services despite the location of their residency or the distance from the health care delivery centers, a goal that can be achieved by utilizing air ambulance systems. In such systems, aircrafts and their life spans are the essential component, the flight duration of the aircraft during its life span is determined by the maintenance schedule. This research, enhances the air ambulance systems by presenting a proposal that maximizes the aircraft flight duration during its life span. The enhancement will be reached by developing a set of algorithms that handles the aircraft maintenance problem. The objective of these algorithms is to minimize the maximum completion time of all maintenance tasks, thus increasing the aircraft operation time. Practical experiments performed to these algorithms showed the ability of these algorithms to achieve the desired goal. The developed algorithms will manage the maintenance scheduling problem to maximize the uptime of the air ambulance which can be achieved by maximizing the minimum life of spare parts. The developed algorithms showed good performance measures during experimental tests. The 3LSL algorithm showed a higher performance compared to other algorithms during all performed experiments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.11
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• pp.1511-1519
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• 2013

This paper proposes the allocation method for capacitor-reactor banks in a distribution system with dispersed generators to reduce the installation costs, the maintenance costs and minimize the loss of electrical energy. The expected lifetime and maintenance period of devices with moving parts depends on the total number of operations, which affects the replacement and maintenance period for aging equipment under a limited budget. In this paper, the expected device lifetimes and the maintenance period are included in the formulation, and the optimal operation status of the devices is determined using a genetic algorithm. The optimal numbers and locations for capacitor-reactor banks are determined based on the optimal operation status. Simulation results in a 69-bus distribution system with the dispersed generator show that the proposed technique performs better than conventional methods.

• Journal of Korean Society of Environmental Engineers
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• v.31 no.12
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• pp.1051-1070
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• 2009

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.1B
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• pp.41-51
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• 2004

Operation and maintenance (OAM) in optical burst switching (OBS) networks has not yet been addressed even though OBS has been gaining research interest in recent years. In this paper, we defined five OBS functions such as Burst Termination (BT), Burst Transmission (BTX), Burst Switching (BSW), Routing and Switching Control (RSC), and Protection and Restoration (PAR). A functional model for OBS networks and an OAM architecture are designed to meet the operational requirements. We present the first framework to realize OAM in OBS networks, including OAM activities, OAM-capable OBS nodes such as ingress edge, core, and egress edge nodes, OAM information and communication models and protocols. A number of examples of possible network failures are pointed out and the corresponding reactions to these using the proposed OAM architecture are presented.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.11
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• pp.1497-1502
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• 2014

Electric load forecasting is essential for stable electric power supply, efficient operation and management of power systems, and safe operation of power generation systems. The results are utilized in generator preventive maintenance planning and the systemization of power reserve management. Development and improvement of electric load forecasting model is necessary for power system maintenance and operation. This paper proposes daily maximum electric load forecasting methods for the next 4 weeks with a seasonal autoregressive integrated moving average model and an exponential smoothing model. According to the results of forecasting of daily maximum electric load forecasting for the next 4 weeks of March, April, November 2010~2012 using the constructed forecasting models, the seasonal autoregressive integrated moving average model showed an average error rate of 6,66%, 5.26%, 3.61% respectively and the exponential smoothing model showed an average error rate of 3.82%, 4.07%, 3.59% respectively.

• Nuclear Engineering and Technology
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• v.56 no.4
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• pp.1472-1479
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• 2024

Cyber-Physical Energy Systems (CPESs) integrate cyber and hardware components to ensure a reliable and safe physical power production and supply. Renewable Energy Sources (RESs) add uncertainty to energy demand that can be dealt with flexible operation (e.g., load-following) of CPES; at the same time, scenarios that could result in severe consequences due to both component stochastic failures and aging of the cyber system of CPES (commonly overlooked) must be accounted for Operation & Maintenance (O&M) planning. In this paper, we make use of Deep Reinforcement Learning (DRL) to search for the optimal O&M strategy that, not only considers the actual system hardware components health conditions and their Remaining Useful Life (RUL), but also the possible accident scenarios caused by the failures and the aging of the hardware and the cyber components, respectively. The novelty of the work lies in embedding the cyber aging model into the CPES model of production planning and failure process; this model is used to help the RL agent, trained with Proximal Policy Optimization (PPO) and Imitation Learning (IL), finding the proper rejuvenation timing for the cyber system accounting for the uncertainty of the cyber system aging process. An application is provided, with regards to the Advanced Lead-cooled Fast Reactor European Demonstrator (ALFRED).

• Nuclear Engineering and Technology
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• v.49 no.5
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• pp.914-919
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• 2017

While industry understands the importance of keeping equipment operational and well maintained, the importance of tracking maintenance information in reliability models is often overlooked. Prognostic models can be used to predict the failure times of critical equipment, but more often than not, these models assume that all maintenance actions are the same or do not consider maintenance at all. This study investigates the influence of integrating maintenance information on prognostic model prediction accuracy. By incorporating maintenance information to develop maintenance-dependent prognostic models, prediction accuracy was improved by more than 40% compared with traditional maintenance-independent models. This study acts as a proof of concept, showing the importance of utilizing maintenance information in modern prognostics for industrial equipment.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.4
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• pp.449-456
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• 2021

Impatience characteristics are an important factor to be considered in the defense field, which is sensitive to time, but there are not many cases applied. In addition, due to the difficulty of analysis that must consider various probabilistic factors (breakdown/maintenance distribution, impatience characteristics, etc.), military decision makers consider only simple data (number of occurrences per year, maintenance time, etc.) Therefore, in this study, a model capable of analyzing the performance of the emergency maintenance system for determining the appropriate size and organization of military and civilian maintenance personnel was presented in consideration of impatience characteristics and probabilistic factors. And through numerical analysis, the appropriate size of the military and civilian emergency maintenance teams was analyzed. This study is significant in that it can improve readiness of operational power and prevent waste of defense budget through efficient operation of the military's emergency maintenance system.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1008-1012
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• 1987

This paper describes the general approach to ISDN operation & maintenance. First we focused on the CCITT SG XVIII activities on the ISDN. As a general principles for operating and maintaining an ISDN they propose TMN(Telecommunication Management Network) concept which specifies several OM function modules and standard interfaces. Based on the concept we studied proper methodology to set up an efficient OM structure under the ISDN environments.