Deploying Artificial Intelligence for Component-Scale Multi-physical Field Simulation of Metal Additive Manufacturing

Abstract

Additive manufacturing is evolving as a prominent aspect of the fourth industrial revolution and offers unprecedented design freedom for creating solid objects from 3D digital models. Effective contribution of metal additive manufacturing (MAM) to realization of Industry 4.0 requires improved mechanical integrity of the AM parts at a lower cost. This study aims to exploit the potential of multiscale modelling and artificial intelligence (machine learning and metamodelling) to realise reliable component-scale multi-physical field simulations for MAM. The thorough quantitative understanding of the various physical phenomena involved in MAM processes would enable a systematic optimisation of process conditions for achieving `first-time-right' high-quality production.