• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.821-830
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• 2023

Various studies has tried to unveil causes of cost overrun and schedule delay in the road construction project. However, these causes need standardization due to difference by guidelines, relevant research, and facilities. Therefore, this study identifies and elaborate standard road construction cost and schedule variation factors that can be used in the planning and execution of the project. variation factors have been derived and grouped through literature review and modified and supplemented through expert interview. In addition, the connection with the relevant guidance factors is confirmed and the usability is reviewed by applying actual road construction cases. The factors suggested in this study comprehensively include factors of related guidelines and previous research, more clearly distinguish, support decision making.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.639-640
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• 2015

Traditional construction planning based on historical data and heuristic adjustment can no longer incorporate all the operational details and guarantee the expected performance. The variation between the expected and the actual production leads to cost overruns or delay. Although predicting reliable productivity on construction site is getting more important, the difficulty of this increases. In this regard, this paper suggested to develop BIM-integrated simulation framework. This framework could predict productivity dynamics by considering factors affecting on construction productivity at operational phase. We developed the following processes; 1) enabling a BIM model to produce input data for simulation; 2) developing the construction operation simulation; 3) running simulation using BIM data and obtaining productivity results. The BIM-integrated simulation framework was tested with structural steel erection model because steel erection work is one of the most critical process influencing on the whole construction budget and duration. We could improve to predict more dynamic productivity from this framework, and this reliable productivity helps construction managers to optimize resource allocation, increase schedule reliability, save storage cost, and reduce material loss.