We’re pleased to announce a new scientific contribution from the OPeraTIC project team, published in Springer – Advances in Artificial Intelligence in Manufacturing II.
Title: Synthetic Data for AI-Powered Ultrafast Laser Based Micro-structuring Method Description
Authors: Beatriz Blanco-Filgueira (AIMEN), Tamara Delgado García (AIMEN), Andrea Gregores (AIMEN), Céline Petit (LASEA), David Bruneel (LASEA), Pablo Romero (AIMEN), and Santiago Muiños-Landin (AIMEN)
The paper introduces a method that uses synthetic data from LS-Plume® simulations to train AI models predicting femtosecond laser surface texturing outcomes on stainless steel. This speeds up development by reducing the need for physical experiments. This approach highlights how simulation and machine learning can make ultrafast laser manufacturing more efficient and sustainable.
Read the full publication here: https://link.springer.com/chapter/10.1007/978-3-031-86489-6_6
