Development of an Automated Workflow for Reinforced Concrete Structural Quantity Takeoff and Cost Estimation Using Visual Programming in a BIM Environment

Waraphong Saenpaeng; Suradet Tantrairatn; Aphai Chaphirom

doi:10.55003/ETH.420402

Authors

Waraphong Saenpaeng Institute of Engineering, Suranaree University of Technology University Avenue, Thailand
Suradet Tantrairatn Institute of Engineering, Suranaree University of Technology, University Avenu, Thailand
Aphai Chaphirom Institute of Engineering, Suranaree University of Technology University Avenue, Thailand

DOI:

https://doi.org/10.55003/ETH.420402

Keywords:

BIM, Visual Programming, Quantity Takeoff, Cost Estimation, Data Visualization

Abstract

In the construction industry, traditional quantity takeoff (QTO) methods still rely on manual measurement from 2D drawings, which are time-consuming, prone to human error, and difficult to verify. As Building Information Modeling (BIM) adoption grows, especially following the release of national BIM standards in 2020, there is increasing interest in developing automated and data-driven workflows to improve the accuracy and efficiency of material quantity estimation. This study proposes an integrated workflow for the automated quantity takeoff and cost estimation of reinforced concrete structures using BIM and visual programming. The workflow leverages Dynamo in Autodesk Revit to extract structured rebar and concrete data from BIM models, which is then exported to Excel using VBA macros for sorting and cleaning data and visualized in Power BI dashboards. A case study of a 7-story residential building demonstrates the application of the proposed workflow. Results show a significant reduction in processing time from several hours using manual Revit QTO to just a few minutes while maintaining high accuracy, standardization, and traceability. The dashboard allows multi-dimensional analysis by material type, structural component, and building floor, supporting effective decision-making in construction cost management. The findings point out the prospects for scalable deployment of this workflow in digital construction environments.

References

Y. Cepni, A. Akcamete and L. Klein, “Automated BIM-based formwork quantity take-off,” in Proc. 20th Int. Conf. Construction Applications of Virtual Reality (CONVR), Middlesbrough, UK, Sep. 30–2, 2020, pp. 220–227.

M. Valinejadshoubi, O. Moselhi, I. Iordanova, F. Valdivieso and A. Bagchi, “Automated system for high-accuracy quantity takeoff using BIM,” Automation in Construction, vol. 157, 2024, Art. no. 105155, 2024 doi: 10.1016/j.autcon.2023.105155.

X. Huang, “Application of BIM Big Data in Construction Engineering Cost,” Journal of Physics: Conference Series, vol. 1865, no. 3, 2021, Art. no. 032016, doi: 10.1088/1742-6596/1865/3/032016.

G. Digregorio, “Real-Time Data and BIM: Automated Protocol for Management and Visualisation of Data in Real Time,” M.S. thesis, Dept. Struct., Geotech. and Build. Eng., Politecnico di Torino, Turin, Italy, 2020. [Online]. Available:https://webthesis.biblio.polito.it/19447/

K. Zawada, K. Rybak-Niedziółka, M. Donderewicz and A. Starzyk, “Digitization of AEC Industries Based on BIM and 4.0 Technologies,” Buildings, vol. 14, no. 5, 2024, Art. no. 1350, doi: 10.3390/buildings14051350.

BIM Overlay to the RIBA Outline Plan of Work, Royal Institute of British Architects (RIBA), London, U.K. 2012, pp. 1–17.

B. Succar, “Building information modelling framework: A research and delivery foundation for industry stakeholders,” Automation in Construction, vol. 18, no. 3, pp. 357–375, 2009. doi: 10.1016/j.autcon.2008.10.003.

Organization and digitization of information about buildings and civil engineering works, including building information modelling (BIM) — Information management using building information modelling, ISO 19650-1:2018, International Organization for Standardization, Geneva, Switzerland, Dec. 2018.

Organization and digitization of information about buildings and civil engineering works, including building information modelling (BIM) — Information management using building information modelling, ISO 19650-2:2018, International Organization for Standardization, Geneva, Switzerland, Dec. 2018.

Organization and digitization of information about buildings and civil engineering works, including building information modelling (BIM) — Information management using building information modelling, ISO 19650-3:2020, International Organization for Standardization, Geneva, Switzerland, Jul. 2020.

Organization and digitization of information about buildings and civil engineering works, including building information modelling (BIM) — Information management using building information modelling, ISO 19650-4:2022, International Organization for Standardization, Geneva, Switzerland, Aug. 2022.

E. Çekin and S. Seyis, “BIM Execution Plan based on BS EN ISO 19650‐1 and BS EN ISO 19650‐2 Standards,” in 6th International Project and Construction Management Conference, Istanbul, Turkey, Nov. 12–14, 2020, pp. 1–9.

T. Pimchanok, S. Tiyanan and T. Thanatcha, “The Apply of Using Building Information Modeling (BIM) to Present Material Takeoff: Case Study Educational Building,” The Journal of Architecture, Design and Construction (JADC), vol. 3, no. 1, pp. 57–68, 2021.

K. L. O’Shea and D. Lamon, “A Critical Analysis of the Application of Visual Programming to Increase Efficiency in BIM Object Metadata Delivery Workflows During the Delivery Phase of an Asset,” Technological University Dublin , Dublin, Ireland, Rep. 1, 2021. [Online]. Available: https://doi.org/10.21427/W73K-9531

C. M. Olszak, “Business Intelligence Systems for Innovative Development of Organizations,” Procedia Computer Science, vol. 207, pp. 1754–1762, 2022. doi: 10.1016/j.procs.2022.09.233.

M. Djerdjouri, “Data and Business Intelligence Systems for Competitive Advantage: prospects, challenges, and real-world applications,” Mercados y Negocios, no. 41, pp. 5–18, 2020. doi: 10.32870/MYN.V0I41.7537.

M. Golestanizadeh, H. Sarvari, D. W. M. Chan, N. Banaitienė, and A. Banaitis, “MANAGERIAL OPPORTUNITIES IN APPLICATION OF BUSINESS INTELLIGENCE IN CONSTRUCTION COMPANIES,” Journal of Civil Engineering and Management, vol. 29, no. 6, pp. 487–500, 2023. doi: 10.3846/jcem.2023.19533.