Empa and Terra Quantum developed a machine-learning model that predicts three-dimensional temperature fields and melt-pool boundaries in laser welding. After training, the Laser Processing Fourier Neural Operator produced predictions in about eight milliseconds at standard resolution and 88 milliseconds at twice that resolution, replacing physics simulations that took minutes or more than an hour.
The model learns how laser power and scanning speed affect the heated metal. Its formulation follows the moving laser and averages over time, making it useful for stable welding conditions. Strongly transient effects, including pore formation and collapsing vapour cavities, remain unresolved; real-time factory control is a prospective application rather than a demonstrated deployment.
