The EU-funded MaaSiveTwin project is using AI, data and digital twins to identify vulnerabilities in critical-material supply chains before disruptions lead to industrial shortages. Running from April 2024 until June 2028, it is designed to help companies and policymakers model how interruptions could affect European industry and identify weak points before shortages emerge.
The project has a total cost of 5.25 million euros and involves researchers from Serbia and five other European countries. Cyprus, Germany, Greece, Poland, Serbia and Switzerland are highlighted in the project, giving the Western Balkans a direct role in research focused on Europe’s industrial resilience.
MaaSiveTwin is building digital representations of supply chains using public data, trade and company information, production data and potentially satellite imagery. AI tools extract information from large volumes of fragmented material, while digital twins model physical assets and the flows connecting them. Materials whose availability could be monitored include graphite, cobalt, rare earths and other materials.
The models are intended to show how disruptions at mines, processing plants, transport corridors or supplier networks could affect European industry. Researchers have reported high data coverage for some battery-material supply chains, including battery-grade graphite.
The project’s approach reflects the multiple stages between extraction and delivery to a European factory. Raw materials can pass through several countries for refining, precursor production and component manufacturing, so mine production alone does not capture Europe’s supply dependencies. A bottleneck at a processing hub, port or intermediate producer can be as consequential as a mine shutdown.
Early warnings could give manufacturers more time to adjust procurement, identify substitutes, change inventory levels or qualify new suppliers if a disruption is likely to tighten material availability. The modelling could also support investment decisions by revealing gaps in European processing, transport or recycling capacity.
MaaSiveTwin reflects a shift in mining intelligence toward continuous data monitoring rather than periodic static reports. Digital twins could become a decision layer for investors and industrial users, linking geology and mine output with logistics, pricing, processing capacity and final demand. The project’s models are intended to combine reliable data with realistic physical constraints and distinguish a genuine supply shock from market noise.
