• Korean Journal of Construction Engineering and Management
• /
• v.16 no.1
• /
• pp.119-128
• /
• 2015

Domestic dominant method in subcontract cost estimate for comprehensive program management is estimation by referencing similar cases or relying on the experience and expertise of the engaged. However, this method is not reliable due to lack of accuracy, making it harder for clients to plan and budget the program. Since budget itself is roughly estimated, it becomes a source of cost rise in the course of management due to design modifications. Therefore, the client and service providers shall calculate more accurate service cost by applying objective and scientific method in order to minimize cost rise and cost related dispute. Traditional cases, in estimating program management cost, took Top-Down approach based on precedents and experience. On the contrary, this study will categorize management structure into phases and activities, issue WBS for each phase to estimated schedule and cost for each code, and take Bottom-UP approach. By taking this approach named ICEP (Integrated Cost Estimate based on Project), Set project typical model will be developed for service cost estimating, calculate cost by applying project-specific factors. Also, by analyzing progress data and allocated management cost to complement them, more efficient construction management will take shape based on program management cost standards which reflect project-specific features.

• Korean Journal of Construction Engineering and Management
• /
• v.20 no.2
• /
• pp.3-12
• /
• 2019

Despite the importance and function of productivity information, in the Korean construction industry, the method of collecting and analyzing productivity data has not been organized. Also, in most cases, productivity management is reliant on the experience and intuitions of field managers, and productivity data are rarely being utilized in planning and management. Accordingly, this study intends to develop a prediction model for interior finishes of apartment using deep learning techniques, so as to provide a foundation for analyzing the productivity impacting factors and predicting productivity. The result of the study, productivity prediction model for interior finishes of apartment using deep learning techniques, can be a basic module of apartment project management system by applying deep learning to reliable productivity data and developing as data is accumulated in the future. It can also be used in project engineering processes such as estimating work, calculating work days for process planning, and calculating input labor based on productivity data from similar projects in the past. Further, when productivity diverging from predicted productivity is discovered during construction, it is expected that it will be possible to analyze the cause(s) thereof and implement prompt response and preventive measures.

• The Journal of the Korea Contents Association
• /
• v.21 no.11
• /
• pp.203-212
• /
• 2021

The high-tech industry, a highly knowledge-intensive industry based on advanced technologies such as electronics, new materials, and IT, is developing rapidly centering on the semiconductor, display, and battery fields. The market size of this industry is continuously increasing, and various challenges are coming forward due to various factors such as changes in the market, changes in demand, and the requirements of the clients. Many strategies are being implemented to advance the start-up time of factories, such as fast-track construction and basic line construction. Therefore, construction of high-tech factory is required to respond to various types of construction plans and early decision making, and an accurate and reliable method of calculating construction costs is needed. In this study the existing construction type was classified into the overall line configuration considering the total production of the factory, and a basic line configuration for quick production start-up. The correction ratio/value for each detailed construction required to calculate the construction cost of the basic line configuration type was derived. Finally, reliability and accuracy were verified by applying the correction ratio suggested in this study to a new high-tech factory construction project.