A molecular dynamics based digital twin for ultrafast laser material removal processes

Abstract

Within the latest years, digital twins have become one of the most promising concepts that can be applied to complex manufacturing processes, due to their accuracy and adaptiveness in real-time what-if scenarios. In the current study, the process of material removal utilizing femtolasers has been examined both theoretically, with the use of molecular dynamics based simulations, and experimentally. The simulation responses are integrated into a digital twin utilizing machine learning techniques, physics and decision-making algorithms. The experimental data from the femtolaser ablation have been compared with the simulation results and the applicability of the digital twin model has been evaluated.