PhD Oral Exam - Amr Allam, Building Engineering

When studying for a doctoral degree (PhD), candidates submit a thesis that provides a critical review of the current state of knowledge of the thesis subject as well as the student’s own contributions to the subject. The distinguishing criterion of doctoral graduate research is a significant and original contribution to knowledge.

Once accepted, the candidate presents the thesis orally. This oral exam is open to the public.

Abstract

Deconstruction is a critical enabler of circular economy implementation in the construction sector. However, according to both literature and domain experts, as manifested by the PESTLE and SWOT analyses conducted in this study, its large-scale adoption remains limited due to fragmented data environment, lack of market integration, and the unavailability of digital planning tools. To address these challenges, this research aims to develop a BIM-based decision-support system, called DeconPlanner, that enables "performance-based deconstruction" through the integration of building data and market intelligence.

To achieve this aim, a five-stage research methodology was followed. Firstly, a critical review of the literature was conducted to synthesize the existing body of knowledge on deconstruction. Secondly, stakeholders’ needs, process factors, adoption technologies, and guidelines were analyzed to develop a conceptual model for the deconstruction of the built environment. Thirdly, deconstruction processes were mapped to the Industry Foundation Classes (IFC) schema to benefit from the broad adoption of open BIM in real-world practice. Fourthly, the DeconPlanner system was developed based on two core components: a Deconstruction Semantics module that parses IFC files to automatically generate topological and dependency relationships within a queryable Building Knowledge Graph (BuildingKG), and a Market Intelligence module that structures second-hand market information into a Customer Knowledge Graph (CustomerKG). These layers are merged into a unified Deconstruction Knowledge Graph (DeconKG) to align recoverable building elements with potential customers. An integration layer further links the system to industry-standard planning software to enable fully automated 4D simulations. Fifthly, the system was validated through a real-world case study and semi-structured interviews with industry professionals, demonstrating its practical relevance and strong interoperability.

The proposed digital solution of this study has significant implications for enabling demand-driven deconstruction, reducing material waste, and accelerating the digital transformation of circular construction practices. This contributes to improving the economic viability of deconstruction projects, increasing material recovery rates, and enhancing supply chain transparency for reclaimed materials.