MANTIS - Modeling of induction heating in additive manufacturing for accurate prediction and control of deformations

The project enhances the Swedish aero engine industry’s competitiveness by maturing a novel DED method for large-scale, fossil-free propulsion components. It aims to reduce costly trial-and-error loops by improving predictive capability, cutting time, energy, and material consumption. A systematic FE-model of electromagnetic and thermomechanical fields will enable accurate prediction of temperature history, stress, and deformation evolution, leading to significantly lower in-situ deformations and defects. The project will develop validated analysis tools necessary for circular material flows, net-zero consumption, and sustainable supply chains. The generated numerical and experimental data will support physics-informed machine learning (PIML/AI) for robust DED processing. The consortium includes research actors, specialized SMEs, and end-users, led by GKN Aerospace Sweden, with RISE and Hexagon developing FE models, and University West conducting experimental validation.