Author:
Fürstenberg David,Hjelseth Eilif,Klakegg Ole Jonny,Lohne Jardar,Lædre Ola
Abstract
AbstractAutomated quantity take-off from digital models in road projects has many benefits. In real project settings, however, it seems rarely to take place. This paper investigates automated quantity take-off in a real-life road project and the experiences from this automation. A literature and a document study were performed. 48 domain models serialized in IFC 2 × 3 were then analyzed before 10 project members were interviewed. The quantity take-off was automated to harvest classified quantities to a specification of work. The automated quantity take-off was reproducible at revisions for 40% of the cost items. However, the transferability of the procedures to other use cases than the specification of work is questionable because of the applied cost breakdown structure. The findings suggest three practical improvements for automated quantity take-off in road projects. The three include (1) using unambiguous classes assembled in an ontology, (2) avoiding hard coding of cost breakdown structures in authoring tools, and (3) implementing the Level of Information Need (LOIN) to improve reusability across project phases and use cases. The quantity take-off and experiences are assessed from the designer's perspective. The client’s and contractor’s perspectives were out of this paper’s scope.
Funder
Norges Forskningsråd
NTNU Norwegian University of Science and Technology
Publisher
Springer Science and Business Media LLC
Reference51 articles.
1. Aram, S., Eastman, C. & Sacks, R. A Knowledge-based framework for quantity takeoff and cost estimation in the AEC industry using BIM. In Proceedings of the 31st International Symposium on Automation and Robotics in Construction and Mining (ISARC). 434–442 (International Association for Automation and Robotics in Construction (IAARC)).
2. Mattern, H., Scheffer, M. & König, M. BIM-based quantity take-off. In Building Information Modeling: Technology Foundations and Industry Practice (eds. André Borrmann, Markus König, Christian Koch, & Jakob Beetz) 383–391 (Springer International Publishing, 2018).
3. Sacks, R., Eastman, C., Lee, G. & Teicholz, P. BIM Handbook: A Guide to Building Information Modeling for Owners, Designers, Engineers, Contractors, and Facility Managers. 3rd edn, 688 (John Wiley & Sons, 2018).
4. Ma, Z. & Liu, Z. BIM-based intelligent acquisition of construction information for cost estimation of building projects. Procedia Eng. 85, 358–367. https://doi.org/10.1016/j.proeng.2014.10.561 (2014).
5. Monteiro, A. & Martins, J. P. A survey on modeling guidelines for quantity takeoff-oriented BIM-based design. Autom. Constr. 35, 238–253. https://doi.org/10.1016/j.autcon.2013.05.005 (2013).