• Proceedings of the KSR Conference
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• 2008.11b
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• pp.567-573
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• 2008

Life cycle costing is one of the most effective approaches for the cost analysis of long-term life products, like as railroad vehicle. Life cycle costing includes the cost of concept design, development, manufacture, operating, maintenance and disposal. Especially, life cycle costing in the railroad industry has been focused on the maintenance cost. In this paper, we investigated the standard, guide and maintenance information of railroad vehicle. For this purpose, we suggested the cost model of railroad vehicle maintenance information. We also performed maintenance cost analysis on the some sub-system of railroad vehicle for the case study.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.05a
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• pp.168-169
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• 2021

Maintenance is carried out over a long period of time, and various documents are utilized in the maintenance work. In maintenance work which is progressed simultaneously in a short period of time, it is important to provide relevant information to the parties in a timely manner. As the types of work increase, manager needs more time and effort to select and utilize the documents. It is necessary to have an information system that supports the person in charge by grasping work procedures for each construction and providing the necessary documents and information for that step. This paper proposes an process based nexus model that can provide necessary documents to the parties to the work steps by linking the maintenance work process and BIM. Through the nexus model presented, manager can efficiently acquire the necessary documents and utilize them for the construction works currently being carried out.

• Korean Journal of Construction Engineering and Management
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• v.12 no.2
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• pp.64-71
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• 2011

Construction projects are becoming larger in size and higher in complexity. Operation and maintenance, therefore, is an important part in providing the serviceability of the built facility from the perspective of life-cycle. This paper presents a 3D graphic model-integrated data extraction for bridge maintenance. The 3D graphic model environment assigns attributes to the member blocks in CAD, and link the attributes to the data stored in a database. Then, the user can click the member block to extract the data associated with the attributes. A prototype has been developed to test the applicability of the 3D graphic model environment using CAD and web. Application of the system in an actual bridge construction showed that the 3D graphic model environment can help the user find necessary data at a shorter time, thereby increasing the effectiveness of operation and maintenance in bridge structures.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.227-233
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• 2021

Predictive maintenance has been one of important applications of data science technology that creates a predictive model by collecting numerous data related to management targeted equipment. It does not predict equipment failure with just one or two signs, but quantifies and models numerous symptoms and historical data of actual failure. Statistical methods were used a lot in the past as this predictive maintenance method, but recently, many machine learning-based methods have been proposed. Such proposed machine learning-based methods are preferable in that they show more accurate prediction performance. However, with the exception of some learning models such as decision tree-based models, it is very difficult to explicitly know the structure of learning models (Black-Box Model) and to explain to what extent certain attributes (features or variables) of the learning model affected the prediction results. To overcome this problem, a recently proposed study is an explainable artificial intelligence (AI). It is a methodology that makes it easy for users to understand and trust the results of machine learning-based learning models. In this paper, we propose an explainable AI method to further enhance the explanatory power of the existing learning model by targeting the previously proposedpredictive model [5] that learned data from a core facility (Hyper Compressor) of a domestic chemical plant that produces polyethylene. The ensemble prediction model, which is a black box model, wasconverted to a white box model using the Explainable AI. The proposed methodology explains the direction of control for the major features in the failure prediction results through the Explainable AI. Through this methodology, it is possible to flexibly replace the timing of maintenance of the machine and supply and demand of parts, and to improve the efficiency of the facility operation through proper pre-control.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.1
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• pp.69-77
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• 2010

The failure rate model of External Environment Maintenance(EEM) for a system under severe environment is investigated. EEM, which is recently introduced concept, is a maintenance activity controlling external environment factors that potentially cause system failure such as cleaning equipment, controlling temperature (humidity) and removing dust inside of electronic appliances. EEM can not have any influence on the inherent failure rate of a system but reduce the severity of the external environment causing failure since it deals with only external environment factors. Therefore, we propose two failure rate models to express the improvement effect of EEM: The intensity reduction model and age reduction model. The intensity and age reduction models of EEM are developed assuming the quality of improvement effect is proportioned to an extra intensity or age respectively. The validation of proposed failure rate models is performed in order of data generation, parameter estimation and test for goodness-of-fit.

• Korean Journal of Construction Engineering and Management
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• v.6 no.5 s.27
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• pp.78-88
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• 2005

Given the trend of increased apartment buildings and high-rise buildings, the maintenance of apartment buildings has been set a higher value. For this reason, a total performance evaluation model of the existing buildings has recently been developed. But, it has a lack of the management work analysis. The purpose of this study, therefore, is the management work analysis for items selection of maintenance performance evaluation of apartment buildings. Candidate items of Maintenance performance evaluation was made with the existing literature and business system analysis. Easy systemicity of performance evaluation supplemented doing question to academic experts and housing managers. Finally decided maintenance performance evaluation items are to classify 14 administrative and 15 technical items.

• Journal of KIISE:Software and Applications
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• v.31 no.5
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• pp.555-562
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• 2004

Software industry has put more emphasis on maintenance and enhancement work than on the new development. The existing effort estimation models can still be applied to maintenance projects, though modifications are needed. This paper suggests a way to estimate the size of a maintenance project from the regression analysis of ISBSG's benchmarking data. First of all, among the 3 elements(addition, modification and deletion of the program) which influences the software cost, we selected and classified 4 groups from a total of 8 which shows actual maintenance cost from ISBSG's data. Moreover, we developed statistical model and a model which uses RBF(Radial Basis Function) Network and after evaluating each functions we concluded that the RBF Network is superior to the statistical model.

• Nuclear Engineering and Technology
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• v.56 no.2
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• pp.526-535
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• 2024

This paper proposes a safety-critical standby component unavailability model that contains aging effects caused by the elapsed time from installation, component degradation due to surveillance tests, and imperfect maintenance actions. An application of the model to a Motor-Operated Valve and a Motor-Driven Pump involved in the HPIS of a VVER/1000-V446 nuclear power plant is demonstrated and compared with other existing models at component and system levels. In addition, the effects of different unavailability models are reflected in the NPP's risk criterion, i.e., core damage frequency, over five maintenance periods. The results show that, compared with other models that do not simultaneously consider the full effects of degradation and maintenance impacts, the proposed model realistically evaluates the unavailabilities of the safety-related components and the involved systems as a plant age function. Therefore, it can effectively reflect the age-dependent CDF impact of a given testing and maintenance policy in a specified time horizon.

• Korean Journal of Construction Engineering and Management
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• v.3 no.4 s.12
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• pp.123-131
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• 2002

The M&R(Maintenance & Repair) budgeting system for domestic military facilities based incremental budgeting model has caused many problems due to the difference between M&R requirement and budget, so military facility become early deterioration. this study proposes the application method of foreign M&R budgeting model for domestic military facility to improve current M&R budgeting system. In order to investigate the current status and problem of M&R budgeting system, this study reviewed various literature related characteristics and types of the foreign M&R budgeting model. The interview was performed for domestic military facility official. The model would greatly improve the current M&R budgeting process for the domestic military facilities.

• KIEAE Journal
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• v.8 no.4
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• pp.19-27
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• 2008

The carbon dioxide is brought from the energy consumption and regarded as a criteria material to estimate the Global Warming Potential. Building shares about 30% in national energy consumption and affects to environment as much as the energy consumption. But there is not enough data to forecast the amount of the carbon dioxide during the maintenance stage. Various factors are related with the energy consumption and carbon dioxide emission such as the physical area, the building exterior area, the maintenance type and location. Among these factors, the building carbon-dioxide emission can be estimated by the overall building characteristics such as the maintenance area, the number of household, the heating type, etc., The physical amount such as the thickness of the insulation and window infiltration could explained the limited scope and might not be use to estimate the total carbon-dioxide emission energy because the each value could not include or represent the overall building. In this paper, it provided the estimation model of the carbon-dioxide emission, explained by the overall building characteristics. These factors are shown as the maintenance area, no. of household, the heating type, the volume of the building, the ratio of the window to wall area etc., For providing the estimation model of th carbon-dioxide emission, it conducted the corelation analysis to filter the variables and suggested the estimation model with the power model and multiple regression model. Most of the model have a good statistics and fitted in the curve line.