• Journal of Wind Energy
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• v.14 no.3
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• pp.61-68
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• 2023

This paper aims to perform optimal operation and maintenance with an integrated monitoring system for offshore wind platforms. Based on the wind direction and wind speed data of existing wind farms, a monitoring system was established along with weather and weather data to maximize the operational efficiency of wind farms. Compared to wind power on land, offshore wind power is difficult to maintain due to weather, logistics and geographical limitations. Therefore, economic analysis of actual operation and maintenance is essential for large-scale offshore wind farms. In this paper, the availability of offshore wind farms was analyzed by using personnel resources, parts inventory, Crew Transfer Vessel (CTV) and Specialized service Operation Vessel (SOV) etc. before the actual operation and maintenance of wind farms. A comparative analysis was conducted to determine the optimum operating efficiency and economical maintenance costs.

• Journal of the Korea institute for structural maintenance and inspection
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• v.11 no.5
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• pp.160-170
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• 2007

This study predicts Life Cycle Cost of RC Slab bridge case in maintenance and operation level and calculated economic efficiency by the avoidable costs of a bridge. This result of the study can be summarized as follow: (1) LCC analysis model on the bridge case is suggested. (2) Maintenance and operation level of a bridge have been divided, and LCC of the bridge case has been predicted at current maintenance and operation level and required maintenance and operation level. (3) Reduction costs is predicted by LCC of the bridge case, and its economic efficiency is calculated.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.4
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• pp.693-700
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• 2024

This study aims to analyze the concept and application of AI-based predictive maintenance in the railroad industry and draw implications from it. Focusing on the adoption of AI-based maintenance systems by the Korea Railroad Corporation and Seoul Metro, we examined how AI technology can improve the efficiency and safety of railroad operations. We also compared and analyzed the application of AI technology in the European railroad industry through the cases of Deutsche Bahn in Germany and SNCF in France. The study found that AI-powered predictive maintenance contributes to reducing the frequency of breakdowns, reducing maintenance costs, and increasing the reliability of railroad operations.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.4
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• pp.505-516
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• 2018

In order to establish an efficient bridge maintenance strategy, the future performance of a bridge must be estimated by considering the current performance, which allows more rational way of decision-making in the prediction model with higher accuracy. However, personnel-based existing maintenance may result in enormous maintenance costs since it is difficult for a bridge administrator to estimate the bridge performance exactly at a targeting management level, thereby disrupting a rational decision making for bridge maintenance. Therefore, in this work, we developed a representative performance prediction model for each bridge element considering uncertainty using domestic bridge inspection data, and proposed a bayesian updating method that can apply the developed model to actual maintenance bridge with higher accuracy. Also, the feasibility analysis based on calculation of maintenance cost for monitoring maintenance scenario case is performed to propose advantages of the Bayesian-updating-driven preventive maintenance in terms of the cost efficiency in contrast to the conventional periodic maintenance.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.47 no.4
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• pp.323-327
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• 2002

Plant growth and the two components of respiration, growth and maintenance, were compared between low and high nitrogen applications in hydroponic culture on a high-yielding rice cultivar 'Takanari' (Oryza sativa L.). Grain yield decreased by high nitrogen application, and thus this cultivar has low adaptability to nitrogen. Growth efficiency (GE) and net assimilation rate (NAR) were lower in the high-nitrogen plot. The maintenance coefficient (m) and growth coefficient (g) of dark respiration were 0.0111 $d^{-1}$ and 0.196 in the low-nitrogen plot and 0.0166 $d^{-1}$ and 0.237 in the high-nitrogen plot, respectively. Thus, high nitrogen application increased both g and m. Calculated $R_m$ (maintenance respiration rate) was 70 and 90% of total respiration rate at heading, respectively. The significance of nitrogen adaptability and g was discussed.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.9
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• pp.1331-1338
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• 2010

Recently, the need for improving the economical efficiency of pumped-storage power plants has increased because of the decrease in the availability of electricity caused by an increase in the consumption of electricity at night. Therefore, a preventative maintenance cycle, especially an overhaul cycle, is required. Unconditional extension cannot be implemented because it may cause unanticipated failures due to insufficient maintenance. Therefore, in this study, a methodology for optimizing the preventative maintenance cycle by taking into account both reliability and economical efficiency is presented; this methodology has been developed by reviewing previous studies on reliability and considering the characteristics of pumped-storage power plants. Finally, an extended overhaul cycle is derived by applying this methodology to a domestic pumped-storage power plant.

• Korean Management Science Review
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• v.28 no.1
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• pp.107-116
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• 2011

The automated teller machine (ATM) is developed as a system to provide customers with an easy deposit and withdrawal of their money without time restriction and be served for 24 hours. Today, ATM is come up to the level of an unmanned branch. The automatic financing system is developed as an essential one for dealing with the rationalization of management and the globalization of financing in order to improve the efficiency of financial management work and increase the customer service quality. With reducing the operational cost of financial organizations through the efficient maintenance operation of ATM and increasing the service quality through the maximization of its processing efficiency, this study is to draw the scheme to ensure the competitiveness among the finance companies. The importance of ATM is highly recognized as the utilization of ATM is increased and the processing function is extended, but ATM is quite vulnerable to the malfunction occurred during the nighttime after banking hours. The ATM maintenance is done through consignment to the specialized maintenance company. The efficient operation of ATM maintenance work is important to the satisfaction of customer using ATM in the nighttime.

• Journal of Korean Society on Water Environment
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• v.36 no.1
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• pp.29-35
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• 2020

To manage the non-point source pollution and restore the water circulation, many technologies including infiltration or reservoir systems were installed in the urban area. These facilities have many problems regarding maintenance as their operation period becomes lengthier. The purpose of this study was to estimate the optimal maintenance timing through a long-term load test on the infiltration trench as one of the low impact development techniques. An infiltration trench was installed in the demonstration test facility, and stormwater was manufactured by Manual on installation and operation of non-point pollution management facilities from the Ministry of Environment, Korea and entered into the infiltration trench. Particle size distribution (PSD), suspended solids (SS) removal efficiency, and infiltration rate change tests were performed on inflow and outflow water. In case of the PSD, the maximum particulate size in the outflow decreased from 64 ㎛ to 33 ㎛ as the operating duration elapsed. The SS removal efficiency improved from 97 % to 99 %. The infiltration rate changed from 0.113 L/sec to 0.015 L/sec during the operation duration. The maintenance timing was determined based on the stormwater runoff requirements with these changes in water quality and infiltration rate. The methodologies in this study could be used to estimate the timing of maintenance of other low impact development techniques.

• Nuclear Engineering and Technology
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• v.46 no.6
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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.

• Journal of the Korea Society of Computer and Information
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• v.22 no.12
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• pp.145-153
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• 2017

Systemic management is required at each phase of the C4I system life cycle to achieve information advantage in the battlefield through stable operation of the C4I system under the NCOE. In particular, the maintenance phase is the longest period of the C4I system life cycle, and it is easy to utilize and analyze data such as faults that occur during system operation. However, according to the previous research, the maintenance is evaluated as a phase in which the definition and management of comprehensive indicators are insufficient compared to other phase. In this paper, we propose the method of C4I Maintenance Priority decision using Maintenance metric. As a result of modifying the Naval Tactical C4I System's preventive maintenance cycle according to the priority, the total number of faults is reduced and the maintenance efficiency is improved.