As part of its efforts to directly integrate artificial intelligence into the production of advanced materials, Neo Performance Materials has partnered with Estonia’s Tallinn University of Technology to bring AI and machine learning across its rare earth, magnetics and advanced materials operations.
“Through our Intelligent Systems Center, we are tackling AI and machine learning in a practical way, from processing complex industrial data to improving and optimizing processes in real time,” said Krister Kalda, Head of Industry Collaboration at TalTech. “Our collaboration with Neo Performance Materials provides a powerful opportunity to apply this to high-value manufacturing environments, where improved efficiency, yield and resource usage translate directly to competitive advantage and a more resilient supply chain.”
As a company that has been producing rare earth materials, magnets, and other advanced materials for over 30 years, Neo brings a wealth of proprietary production and quality control data to the partnership.
“By incorporating AI into our product development and manufacturing operations and partnering with research institutions such as TalTech, we are translating decades of rare earth expertise and real-world data into tangible results, primarily in permanent magnet manufacturing and rare earth separation,” said Rahim Suleman, President and CEO of Neo. “These advances will support more efficient processing and a stronger, more resilient rare earth supply chain.”
Rather than using AI only as a standalone analytical tool, Neo and TalTech aim to integrate machine learning directly into their advanced material operations, allowing their AI systems to continuously analyze production data, optimize processing conditions, and improve performance through real-time operational feedback.
Neo said the effort combines the company’s experience in rare earth chemistry, physics and magnetism with TalTech’s expertise in industrial AI systems and machine learning.
The company aims to embed AI systems trained by in-house datasets and advanced materials science teams directly into manufacturing processes, allowing the systems to optimize workflows while continuously learning from production results.
As rare earths and other advanced materials serve as essential building blocks for technologies ranging from AI data centers to smartphones, this partnership highlights the potential for AI to create larger feedback loops that optimize the production of advanced materials that enable AI.
Author biography
Shane Lasley, Metal Tech News
Having covered mining for over 18 years, Shane is known for his insight and in-depth analysis of mining, mineral exploration and technical metals.
