A Framework for Automated Quantity Extraction from .ifc Models and Normalized Bid Comparison - Farouk, Asmaa Mohamed (AUC Knowledge Fountain, 2026)
Accurate bid comparison remains a major challenge in construction tendering due to differences in Bill of Quantities formats, item naming conventions, and pricing methods across contractor submissions. These variations require time-consuming manual work and often lead to subjective decisions. This research presents a computational framework that uses Building Information Modeling through the .ifc file format, combined with text analysis techniques for automated bid normalization. The developed system uses a dual-component approach. Phase 1 extracts quantities from .ifc model files using 3D geometric calculations, automated element classification. Phase 2 uses text mining with a domain-specific dictionary of construction terms to interpret different contractor submissions, match items across BOQs, and classify line items as explicitly priced, bundled within other items, or absent. A proportional redistribution algorithm ensures that the total bid value stays consistent when adding values for bundled items. Testing against reference data from Revit schedules shows that the developed tool achieves 100% accuracy in element counting, significantly outperforming AI-based approaches which achieved only 35-65% accuracy. The framework generates standardized comparison sheets that allow objective evaluation of cost distribution, scope coverage, and pricing consistency across submissions. Results show major reduction in manual work while improving transparency in the tender evaluation process.