Automated BIM-based Formwork Quantity Take Off

Çepni, Yaşar
Akçamete Güngör, Aslı
Kleın, Ralf
Quantity take-off (QTO) is an indispensable part of construction projects since it is used forscheduling and cost calculation. However, obtaining accurate QTOs from 2D traditional drawings is tedious and time-consuming. Therefore, the use of BIM for QTO is increasing. According to literature, the accurate, automated calculation of formwork areas from BIM remains still problematic. This is mainly due to lack of modeling conventions, agreed workflows, and classification, together with modeling errors like overlapping structural elements and limitations of BIM software. It is important to note that QTO is needed during several phases of the design and construction process, with differing requirements and available information. Moreover, automated formwork generation is not supported by the majority of BIM tools although it is also a timeconsuming task and necessary for construction phase planning, visualization, and interference check. Therefore, this publication describes how the extraction of formwork quantities and the creation of formwork models can be automated with Autodesk Revit Dynamo. A case study is presented, and the results obtained from the presented algorithm are verified with the manual operation of the BIM quantification features as well as manual calculations for some elements. Consequently, accurate and faster formwork quantification results and genericformwork models are automatically obtained. Ongoing research is focused on the extension of the tool to automate the creation of formwork models for 4D modeling for the construction stage, including the aspects of scheduling and clash detection in the context of open-BIM.
20th International Conference on Construction Applications of Virtual Reality, , October 2020


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Citation Formats
Y. Çepni, A. Akçamete Güngör, and R. Kleın, “Automated BIM-based Formwork Quantity Take Off,” presented at the 20th International Conference on Construction Applications of Virtual Reality, , October 2020, Teesside University, Middlesbrough, UK, 2020, Accessed: 00, 2021. [Online]. Available: