Imagine having a perfect digital mirror of a steel factory that predicts exactly how metal will melt and shape in real-time. It's like using a high-tech GPS for the production line to avoid mistakes and waste. By using smart sensors and AI, the system ensures the raw scrap metal is high quality and the energy is used perfectly.
Steel producers struggle with high carbon footprints, inefficient scrap usage, and quality inconsistencies in crude steel and finished sheets.
A user-friendly digital platform utilizing AI and novel sensors for real-time control of electric arc furnaces and steel sheet leveling.
If you are an EAF operator dealing with inconsistent scrap quality and high energy waste — this project developed a digital platform that optimizes crude steel production. This can help reduce CO2 emissions by up to 6 million tonnes per year.
If you are a processing plant dealing with quality defects in finished steel sheets — this project developed a real-time control system for leveling. This improves the quality of final products and increases process yield.
If you are a scrap supplier dealing with inaccurate feedstock verification — this project developed novel sensors and AI models for better scrap verification. This ensures a more efficient supply chain for green steel production.
Based on available project data, the implementation of this digital platform has the potential to save up to €800 million in costs annually.
Yes, the digital platform will be implemented and verified in industrial process lines across three specific use cases: scrap verification, furnace optimization, and sheet leveling.
Based on available project data, specific licensing terms are not provided, but the project is coordinated by Fraunhofer, a major applied research organization.
The project focuses on a user-friendly digital platform that uses novel and soft sensors to integrate industrial data and human experience into the production process.
The project is active from November 1, 2024, and is scheduled to conclude by April 30, 2028.
The consortium is heavily weighted toward technical execution, featuring 12 partners from 5 European countries. With a 42% industry ratio (5 industrial partners) and 7 research organizations, the project balances academic AI development with practical industrial application. The leadership by Fraunhofer suggests a strong focus on applied research and technology transfer.
Contact Fraunhofer Gesellschaft for technical inquiries regarding the DiGreeS platform.
Contact SciTransfer to connect with the DiGreeS consortium for early adoption opportunities.
