• Journal of KIISE:Computing Practices and Letters
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• v.6 no.3
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• pp.311-318
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• 2000

The importance of the semiconductor industry in Korea has been growing, but the manufacturers are experiencing two major problems: poor optimization of production and low localization ratio of production equipments. Due to the complex manufacturing processes and special features such as OTD (On Time Delivery) and LIPAS (Line Item Performance Against Schedule) possibilities, several attempts to apply MRP or spreadsheet have been failed to meet the expectations. This paper describes the computer modeling technique as the solutions to analyze the problem, to formalize the semiconductor manufacturing process, and to build an advanced manufacturing environments. The computer simulation models are built referring the FAB facilities of the National Inter - University Semiconductor Research Center to show the FAB processes and the functions of each process.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.176-183
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• 2008

Recently, several large-scale Mega-Projects are being conducted. For these urban revitalization projects which requires many complex functions, the existing project management system based on single project level is limited in application. Therefore, our main objectives of this research are two 1) Develop a brand-new program management system(Prototype Ver 1.0) for mega-projects where various facilities are combined both horizontally and vertically. 2) Develop management strategies(Prototype Ver 1.0) based on the program level that enable the comprehensive management of a multiple various projects. The subtitles of this Research are i-PMIS(Program Management Information System) Development, Standardization & Optimization of Construction Life-Cycle Process, Comprehensive Project Cost & Process Management Technology, Effective and Optimized Integrated Performance Management Technology, and, we suggest to optimize the whole life cycle process, predict and respond to various risks, predict and control the process, the cost and the schedule, achieve maximum return on investment to the participating parties, and provide a brand-new Program-MIS including the visual-based web-portal platform to respond the changing business environments and decision making.

• Explosives and Blasting
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• v.38 no.4
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• pp.16-25
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• 2020

Multi-setting smart-investigation of the ground and large uncharged hole boring (MSP) method to reduce the blast-induced vibration in a tunnel excavation is carried out over 50m of long-distance boring in a horizontal direction and thus has been accompanied by deviations in boring alignment because of the heavy and one-directional rotation of the rod. Therefore, the deviation has been adjusted through the boring machine's variable setting rely on the previous construction records and expert's experience. However, the geological characteristics, machine conditions, and inexperienced workers have caused significant deviation from the target alignment. The excessive deviation from the boring target may cause a delay in the construction schedule and economic losses. A deep learning-based prediction model has been developed to discover an ideal initial setting of the MSP machine. Dropout, early stopping, pre-training techniques have been employed to prevent overfitting in the training phase and, significantly improved the prediction results. These results showed the high possibility of developing the model to suggest the boring machine's optimum initial setting. We expect that optimized setting guidelines can be further developed through the continuous addition of the data and the additional consideration of the other factors.