We are excited to share a new joint publication from AIMEN and LASEA: “Adapting Laser Ablation Models from Simulation to Experiment: A Transfer Learning Approach for Stainless Steel, Silicon and Aluminum”.

One of the key challenges in AI-driven manufacturing is making simulation models useful in the real world without requiring hundreds of costly and time-consuming experiments. In this work, the authors demonstrate how Transfer Learning can bridge the gap between simulations and experiments, enabling laser ablation models to be adapted to different materials, including stainless steel, silicon and aluminium, with only a small number of experimental samples.

The study also integrates Explainable AI techniques to reveal which parameters drive the process behaviour, turning AI models into valuable tools for both prediction and process understanding. By combining physics-based simulations, experiments and artificial intelligence, the proposed approach helps make advanced laser manufacturing more efficient, scalable and data-conscious.

Curious? Read the paper here: https://www.mdpi.com/2504-4494/10/7/244