If you are a mining operator dealing with low-grade ores that are too expensive to process — this project developed a CRM Recovery Selector and smart ore sorters that identify and extract valuable materials more efficiently.
AI-Driven Sustainable Recovery of Critical Raw Materials from Mining Waste and Low-Grade Ores
Imagine trying to find a few gold needles in a massive haystack of old rocks. This project builds a smart toolkit that uses AI and biology to pick out valuable metals more efficiently. It's like giving a mine a digital brain and a set of high-tech filters to stop wasting materials and energy.
What needed solving
European mining companies struggle to profitably extract critical raw materials from low-grade ores and complex waste. This leads to resource inefficiency and high environmental toxicity.
What was built
A suite of CRM recovery tools including smart sorters, bioleaching systems, AI-enabled recovery selectors, Digital Twins for plant simulation, and a market observatory system.
Who needs this
Who can put this to work
If you are a waste valorisation firm dealing with toxic mining tailings — this project developed a toolkit for toxicity management and waste valorisation that turns hazardous leftovers into usable resources.
If you are a mining tech provider dealing with inefficient plant monitoring — this project developed Digital Twins and a Virtual Miner NLP assistant that optimize productivity through simulation.
Quick answers
What is the cost or price of these technologies?
Based on available project data, specific pricing or cost structures for the technologies are not provided.
Can this be implemented at an industrial scale?
Yes, the project includes DEMOMINER, which showcases 6 use cases across Spain, Greece, Poland, Finland, and Chile to test recovery in real-world settings.
How is the IP and licensing handled?
Based on available project data, there are no specific details regarding the licensing models or patent strategies.
How does this integrate with existing mining operations?
Integration is achieved through the DIGIMINER platform, which provides smart monitoring, control, and a Decision Support System for operators.
What is the timeline for deployment?
The project runs from 2025-01-01 to 2028-12-31, suggesting that pilot results and tools will be available toward the end of 2028.
Who built it
The consortium is heavily weighted toward commercial application, with a 57% industry ratio consisting of 12 industrial partners, including 6 SMEs. This strong industrial presence, combined with 7 research entities and 1 university across 8 countries, suggests a high focus on market uptake and practical deployment rather than purely theoretical research.
Contact the Research Center for Communication and Computing Systems (EL)
Talk to the team behind this work.
Contact us to connect with the OPTIMINER consortium for pilot opportunities.