Data-Driven Reverse Engineering Algorithm Development Method for Developing Interoperable Quantity Takeoff Algorithms Using IFC-Based BIM

Abstract

One main gap in the automation of construction quantity takeoff (QTO) is the lack of a systematic method to address building information models (BIMs) created from different BIM authoring tools and workflows. Even the Industry Foundation Classes (IFC), one of the ISO standard data schema, have been used in a variety of ways, some of which could be proprietary. To address this gap, the authors proposed a new data-driven reverse engineering algorithm development (D-READ) method for developing QTO algorithms based on IFC geometric analysis. The proposed method enables the development of QTO algorithms for IFC-based BIMs resulting from different BIM authoring tools and workflows, and therefore it enhances robustness of BIM-based QTO. It takes a novel bottom-up approach in QTO algorithm development compared to the traditional top-down approach. A model view definition (MVD) model for IFC model checking was developed and incorporated with the QTO algorithms. The proposed method was tested on nine different BIM instance models from different sources. A comparison with the state-of-the-art commercial software showed consistent QTO results, whereas the proposed D-READ method resulted in QTO algorithms that were more robust with regard to the different BIM authoring tools and workflows used.