• The Journal of Korean Institute for Practical Engineering Education
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• v.1 no.1
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• pp.30-37
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• 2009

The purpose of this study is the development and application of practical education program for the security of semiconductor equipments maintenance technology. For securing the semiconductor equipments maintenance technology, this study aims to research on the Training and Development. The main field of HRD is about the Training and Development. We develop the practical education program applying the ADDIE Model to conduct the education training. This developed program tests the education training on the officers of Samsung Electronics, the maker of semiconductor. By the test, we hope to provide the technology education program focusing on the practical experiences of systematic and effective companies.

• Korean Journal of Construction Engineering and Management
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• v.5 no.6 s.22
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• pp.118-128
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• 2004

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 Electrical Engineering and Technology
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• v.6 no.4
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• pp.431-438
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• 2011

To ensure that equipment outages do not directly impact the reliability of the ISO-controlled grid, market participants request permission and receive approval for planned outages from the independent system operator (ISO) in competitive electricity markets. In the face of major generation outages, the ISO will make a critical decision as regards the scheduling of the essential maintenance for myriads of generating units over a fixed planning horizon in accordance with security and adequacy assessments. Mainly, we are concerned with a fundamental framework for ISO's maintenance coordination in order to determine precedence of conflicting outages. Simulated annealing, a powerful, general-purpose optimization methodology suitable for real combinatorial search problems, is used. Generally, the ISO will put forward its best effort to adjust individual generator maintenance schedules according to the time preferences of each power generator (GENCO) by taking advantage of several factors such as installed capacity and relative weightings assigned to the GENCOs. Thus, computer testing on a four-GENCO model is conducted to demonstrate the effectiveness of the proposed method and the applicability of the solution scheme to large-scale maintenance scheduling coordination problems.

• Journal of Distribution Science
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• v.18 no.1
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• pp.59-69
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• 2020

Purpose: This study aims to examine such relationships as the experiential value that customers respond to with regard to maintenance service by empirically revealing how the quality of auto maintenance and repair service affects both customer satisfaction and intention to reuse the same service through the Perceived-experiential Value of customers. Research design, data and methodology: The research model was designed with service qualities such as human quality, material quality, interaction quality, and system quality as independent variables, perceived-experiential value as a parameter, and service satisfaction and return visit intention as dependent variables. Through a questionnaire composed of 24 items, a total of 319 survey data from customers with the experience of using car maintenance service centers in Korea were collected and analyzed using a structural equation. Results: The material quality did not affect the customers' perceived-experiential value, whereas the interaction quality had the greatest influence. It is confirmed that human quality, interaction quality, and system quality can generate customer satisfaction and repurchase intention through the perceived-experiential value. Conclusions: The experiential value of customers can play an important medium role in improving satisfaction, with customers considering interaction quality important. Therefore, the auto maintenance and repair service should consider relationship-focused service strategies.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.3
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• pp.18-30
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• 2022

Predicting remaining useful life (RUL) becomes significant to implement prognostics and health management of industrial systems. The relevant studies have contributed to creating RUL prediction models and validating their acceptable performance; however, they are confined to drive reasonable preventive maintenance strategies derived from and connected with such predictive models. This paper proposes a data-driven preventive maintenance method that predicts RUL of industrial systems and determines the optimal replacement time intervals to lead to cost minimization in preventive maintenance. The proposed method comprises: (1) generating RUL prediction models through learning historical process data by using machine learning techniques including random forest and extreme gradient boosting, and (2) applying the system failure time derived from the RUL prediction models to the Weibull distribution-based minimum-repair block replacement model for finding the cost-optimal block replacement time. The paper includes a case study to demonstrate the feasibility of the proposed method using an open dataset, wherein sensor data are generated and recorded from turbofan engine systems.

• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.4
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• pp.120-130
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• 2019

In this study, based on the correlation between traffic volume data and vertical displacement data developed in previous research using the bridge maintenance big data of 2006, the vertical displacement estimation model using the traffic volume data of Gwangan Bridge for 10 years A comparison of the performance of the developed model with the current applicability is presented. The present applicability of the developed model is analyzed that the estimated displacement is similar to the actual displacement and that the displacement estimation performance of the model based on the structured regression analysis and the principal component analysis is not significantly different from each other. In conclusion, the vertical displacement estimation model using the traffic volume data developed by this study can be effectively used for the analysis of the behavior according to the traffic load of Gwangan Bridge.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.1
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• pp.53-59
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• 2021

The marine transport industry generally applies new technologies later than other transport industries, such as airways and railways. Vessels require efficient operation, and their performance and lifespan depend on the level of maintenance and management. Many studies have shown that corrective maintenance (CM) and time-based maintenance (TBM) have restrictions with respect to enabling efficient maintenance of workload and cost to improve operational efficiency. Predictive maintenance (PdM) is an advanced technology that allows monitoring the condition and performance of a target machine to predict its time of failure and helps maintain the key machinery in optimal working conditions at all times. This study presents the development of a marine predictive maintenance (MPdM; maritime predictive maintenance) method based on applying PdM to the marine environment. The MPdM scheme is designed by considering the special environment of the marine transport industry and the extreme marine conditions. Further, results of the study elaborates upon the concept of MPdM and its necessity to advancing marine transportation in the future.

• Korean Journal of Cognitive Science
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• v.21 no.2
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• pp.359-386
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• 2010

In order to evaluate the domain-specific model and process-specific model of spatial and nonspatial working memory (WM), this study manipulated the memory load of the delayed response task and examined how the neural correlates of memory load effect was influenced by the stimulus domain (face and location) at the maintenance stage of WM using an event-related fMRI experiment. One or three face stimuli were presented as target stimuli and participants were asked to maintain the face itself (face WM) or the location of face stimuli (spatial WM). The results of recognition judgment accuracy showed no difference between face WM and spatial WM, and showed equivalent memory load effects of both WM. As a result of brian image analysis, memory load effect at maintenance stage showed that inferior, middle, and superior PFC were recruited by both face WM and spatial WM, and showed that VLPFC was the commonly activated area by both WM, supporting functional specialization of PFC by process components of WM. This study provides evidence for process-specific model in which maintenance of WM is associated with VLPFC.

• Journal of Internet of Things and Convergence
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• v.8 no.6
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• pp.55-63
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• 2022

In recent years, with the rapid development of large and medium-sized urban rail transit in China, the total operating mileage of high-speed railway and the total number of EMUs(Electric Multiple Units) are rising. The system complexity of high-speed EMU is constantly increasing, which puts forward higher requirements for the safety of equipment and the efficiency of maintenance.At present, the maintenance mode of high-speed EMU in China still adopts the post maintenance method based on planned maintenance and fault maintenance, which leads to insufficient or excessive maintenance, reduces the efficiency of equipment fault handling, and increases the maintenance cost. Based on the intelligent operation and maintenance technology of PHM(prognostics and health management). This thesis builds an integrated PHM platform of "vehicle system-communication system-ground system" by integrating multi-source heterogeneous data of different scenarios of high-speed EMU, and combines the equipment fault mechanism with artificial intelligence algorithms to build a fault prediction model for traction motors of high-speed EMU.Reliable fault prediction and accurate maintenance shall be carried out in advance to ensure safe and efficient operation of high-speed EMU.

• Journal of the Korea institute for structural maintenance and inspection
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• v.9 no.2
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• pp.217-224
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• 2005

A methodology of selecting an optimal model is proposed for applying a frequency-domain SI method effectively. Instead of using a reduced finite element model, a reasonably detail finite element model is established first and then the model is identified. To satisfy the identifiability criterion, a parameter grouping scheme is applied to control the number of unknowns. Among the simulated member grouping cases, an optimal model is selected as the one with the minimal statistical error. The proposed approach has been examined through simulation studies on a single span box-girder bridge.