Future Remanufacturing Data and AI Driven Innovations for Growing Manufacturing Business (FREIMAN)

In the recent years, customers have increasingly demanded remanufactured parts as they improve the sustainability and offer a lower cost option compared to new parts made from virgin materials.

Many companies have successfully implemented remanufacturing as a profitable business model; however, its growth is constrained by supply–demand challenges. In practice, companies engaged in remanufacturing face significant difficulties in securing sufficient quantities of “core” components, such as used engines, gearboxes, or hydraulic parts, that are suitable for the remanufacturing process. Without a steady flow and adequate volumes of incoming used parts, companies are unable to produce enough remanufactured components to meet customer demand.

The FREIMAN project addresses the globally recognized imbalance between the demand for and availability of remanufactured parts. By leveraging data, artificial intelligence, and decision-support tools, the project enhances transparency and control within the return loop. The primary use case focuses on the remanufacturing of core components for wood harvesters.

The FREIMAN consortium consists of Ponsse, Nokian Renkaat, Masino‑Konaflex, Kaltiot, Motoajo, the University of Oulu, and VTT as the coordinating organization. The project duration spans from 2026 to 2027.