
A Swedish industrial consortium centered around the research institute RISE and Interspectral is working in the new RES2AM project on more robust and resource-efficient processes for metal 3D printing of large, complex components. The initiative is funded with just under 4 million euros as part of the Net Zero Industry program of the innovation agency Vinnova and aims to further establish additive manufacturing as an option for safety-critical applications in aerospace, energy and heavy industry.
In addition to Interspectral, GKN Aerospace, Saab, SKF and the Ringhals nuclear power plant are involved, as well as technology providers such as Nikon SLM Solutions and Hexagon. The goal is a modular, reconfigurable AM platform that is densely equipped with sensors and continuously captures and analyzes process data. The architecture is intended to be adaptable to different materials, component sizes and industry requirements.
In four industrial testbeds, use cases from aerospace, defense, nuclear technology and heavy machinery are being investigated. There, the consortium aims to demonstrate that material usage, energy consumption and scrap rate can be significantly reduced without undermining safety and documentation requirements. Interspectral is contributing visualization and machine learning tools for in-situ monitoring and digital quality assurance.
“Interspectral is excited to expand our visualization and machine learning tools for in-situ monitoring, supporting digital quality assurance across multiple sensors and industrial environments,” says Isabelle Hachette, CEO of Interspectral. “This project positions Sweden at the forefront of sustainable, circular, and resilient manufacturing.”
In the long term, RES2AM is intended to provide a blueprint for how additive manufacturing can be scaled within existing production landscapes without compromising the resilience of supply chains. The project is also closely linked to European climate targets and the EU Green Deal agenda, as circular economy and energy efficiency are explicitly addressed.
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