Introducing Computing to Construction Management Undergraduate Students through Automated Quantity Takeoff from IFC-Based BIM
Publication: Computing in Civil Engineering 2023
ABSTRACT
Industry foundation classes (IFC) can facilitate quantity takeoff (QTO) from building information models (BIMs). In this paper, a Cartesian point-based computing method (named the automation extraction method, or AEM) was introduced to get the area of polygonal-shaped building components from IFC-based BIM. The AEM was implemented using Python programming language, tested on a sale area and a utility room of a commercial building, and adopted in an undergraduate construction management (CM) course project to help students gain experience with computing in CM tasks. The result using the AEM was compared to a manual extraction and calculation method. Results showed the difference from the manual QTO was within 1%, and it took stably less time in finishing the task with AEM. Post-project survey results showed about 49% students indicated the AEM method and exercise helped improve their understanding of computing concepts and applications in the architecture, engineering, and construction (AEC) domain.
Get full access to this article
View all available purchase options and get full access to this chapter.
REFERENCES
Abanda, F. H., Kamsu-Foguem, B., and Tah, J. H. M. (2017). “BIM – New rules of measurement ontology for construction cost estimation.” Engineering Science and Technology, 20(2), 443–459.
Akanbi, T., and Zhang, J. (2020). “Automated design information extraction from construction specifications to support wood construction cost estimation.” Construction Research Congress 2020, ASCE, Reston, VA.
Akanbi, T., and Zhang, J. (2021). “Design information extraction from construction specifications to support cost estimation.” Automation in Construction, 131(2021), 103835.
Akanbi, T., Zhang, J., and Lee, Y.-C. (2019). “Automated Item Matching and Pricing (IMP) for Wood Building Elements to Support BIM-Based Wood Construction Cost Estimation.” International Conference on Computing in Civil Engineering 2019, ASCE, Reston, VA, 402–409.
Arage, S. S., and Dharwadkar, N. V. (2017). “Cost estimation of civil construction projects using machine learning paradigm.” 2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), 594–599.
Chan, T. W. (2014). “Barriers of Implementing BIM in Construction Industry from the Designers’ Perspective: A Hong Kong Experience.” Journal of System and Management Sciences, 4(2), 024–040.
Fazeli, A., Dashti, M. S., Jalaei, F., and Khanzadi, M. (2020). “An integrated BIM-based approach for cost estimation in construction projects.” Engineering, Construction and Architectural Management, 28(9), 2828–2854.
Gamil, Y., Abdullah, M. A., Abd Rahman, I., and Asad, M. M. (2020). “Internet of things in construction industry revolution 4.0: Recent trends and challenges in the Malaysian context.” Journal of Engineering, Design and Technology, 18(5), 1091–1102.
Kermanshachi, S., and Rouhanizadeh, B. (2018). “Feasibility analysis of post disaster reconstruction alternatives using automated BIM-based construction cost estimation tool”. In Proceeding of CSCE 6th International Disaster Mitigation Specialty Conference, Canadian Society of Civil Engineering, Montreal, Canada, 13–16.
Lawluvy, Y. K., Guo, F., and Wang, K. (2022). “A Framework for Assessing Strategies to Combat Individuals’ Resistance to Technological Innovation in the Construction Industry.” Construction Research Congress 2022, ASCE, Reston, VA, 974–982.
Lines, B. C., Sullivan, K. T., Smithwick, J. B., and Mischung, J. (2015). “Overcoming resistance to change in engineering and construction: Change management factors for owner organizations.” International Journal of Project Management, 33(5), 1170–1179.
Mohd Nawi, M. N., Baluch, N. H., and Bahaudin, A. Y. (2014). “Impact of fragmentation issue in construction industry: An overview.” MATEC Web of Conferences, 15, 01009.
Rafiei, M. H., and Adeli, H. (2018). “Novel Machine-Learning Model for Estimating Construction Costs Considering Economic Variables and Indexes.” Journal of Construction Engineering and Management, 144(12), 04018106.
Riazi, S. R. M., Zainuddin, M. F., Nawi, M. N. M., Musa, S., and Lee, A. (2020). “A critical review of fragmentation issues in the construction industry.” Journal of Talent Development and Excellence, 12(2), 1510–1521.
Sanni-Anibire, M. O., Mohamad Zin, R., and Olatunji, S. O. (2021). “Developing a preliminary cost estimation model for tall buildings based on machine learning.” International Journal of Management Science and Engineering Management, 16(2), 134–142.
Sattineni, A., and Bradford, R. (2011). Estimating with BIM: A Survey of US Construction Companies.
Sepasgozar, S. M. E., Costin, A. M., Karimi, R., Shirowzhan, S., Abbasian, E., and Li, J. (2022). “BIM and Digital Tools for State-of-the-Art Construction Cost Management.” Buildings, 12(4), 396.
Smith, D. (2007). “An Introduction to Building Information Modeling (BIM)”. Journal of Building Information Modeling, 12–14.
Wu, J., Akanbi, T., and Zhang, J. (2022). “Constructing Invariant Signatures for AEC Objects to Support BIM-based Analysis Automation Through Object Classification.” Journal of Computing in Civil Engineering, 36(4), 04022008.
Information & Authors
Information
Published In
Computing in Civil Engineering 2023
Pages: 630 - 638
History
Published online: Jan 25, 2024
ASCE Technical Topics:
- Architectural engineering
- Building information modeling
- Building management
- Colleges and universities
- Computer languages
- Computer models
- Computer programming
- Computing in civil engineering
- Construction engineering
- Construction management
- Construction methods
- Education
- Engineering fundamentals
- Models (by type)
- Practice and Profession
- Students
- Undergraduate study
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.