IFC-based automated deconstructability analysis with market data integration through knowledge graphs
Deconstruction is vital for circular economy implementation in the construction sector, yet thin profit margins stifle its large-scale adoption. Consequently, deconstruction demands rigorous and data-driven planning. While Building Information Modeling (BIM) can serve this purpose, its readiness for deconstruction remains limited. This paper introduces DeconPlanner , a system that integrates Knowledge Graphs (KGs) and Industry Foundation Classes (IFC) to support digitally enabled deconstruction planning through two modules: an inference-based module that semantically enriches BIM with deconstruction sequencing; and an AI-powered market integration module that semantically enhances BIM by establishing semantic links between facility inventory and potential downstream stakeholders. Validation through a real-world case study demonstrated high performance for dependency inference (96.6% precision; 97.3% recall) and market integration (99.4% precision; 94% recall). Additionally, expert interviews confirmed the system's practicality and industry relevance. The findings demonstrate this framework's potential to reduce information fragmentation and establish the semantic foundation for future performance-based deconstruction workflows.
Authors
- Mazdak Nik-Bakht
- Amr S. Allam
Institutions
- Concordia University (CA)
Publication Details
- Journal
- Automation in Construction
- Published
- 2026-08-26
- DOI
- https://doi.org/10.1016/j.autcon.2026.107219
- Primary Topic
- Manufacturing Process and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Research Council Canada
- Fonds de recherche du Québec – Nature et technologies