Muhammed Emin Oral
A Knowledge Graph Approach to Critical Raw Materials Risk Monitoring: Developing a Strategic Digital Twin with Neo4j.
Rel. Alessandro Savino, Nicolò Maunero, Andrea Bernardini, Francesco Giancaterini. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
|
Preview |
PDF (Tesi_di_laurea)
- Tesi
Licenza: Creative Commons Attribution Non-commercial No Derivatives. Download (10MB) | Preview |
Abstract
European industrial economies face a structural vulnerability in their dependence on external suppliers for Critical Raw Materials (CRMs) - minerals that are indispensable to the green and digital transition, advanced manufacturing, and defense industries. The European Union has responded by enacting the Critical Raw Materials Act (CRMA), which requires companies to trace their supply chains back to the point of origin and to assess disruption risks at every stage. However, existing monitoring tools rely on aggregate country-level indicators that treat entire nations as single supply nodes. These tools are unable to capture firm-level dependencies or the indirect, multi-hop paths through which localized disruptions actually propagate across trade networks.
To address this gap, this thesis draws on two technical foundations: the regulatory architecture of the EU CRMA and the computational properties of graph database systems
Relatori
Anno Accademico
Tipo di pubblicazione
Numero di pagine
Corso di laurea
Classe di laurea
Aziende collaboratrici
URI
![]() |
Modifica (riservato agli operatori) |
