BIM and procurement data integration in industrialized construction using artificial intelligence

Abstract

Industrialized construction (IC) has experienced significant achievements in the development of innovative construction methods in response to the demands of the construction industry. In this context, building information modeling (BIM) integrates and manages data throughout prefabrication phases (design, bid, and procurement) within an IC project. However, manual tasks such as data transfer between BIM models and enterprise resource planning (ERP) systems result in delays and errors due to the constant change of versions and large data flow between the involved parties. This research proposes the implementation of a novel method based on artificial intelligence (AI) to integrate the required information contained in elements in the BIM model with construction materials databases normally managed by ERP systems to procure and purchase materials in IC enterprises. Using a case study approach, this research presents a workflow with the proposed method whereas the results show that 81.57% of the elements were successfully identified, leading to a 63.47% reduction in the time compared to the manual assignment approach. Despite classifying a considerable percentage of the elements, it was identified that the implemented workflow depends on manual-dependent tasks during the design phase, such as modeling methodologies. This research contributes by providing new methods to improve IC projects and is expected to contribute to future research related to AI-based.