The ‘TWIN’ research project at ScaDS.AI and the University of Leipzig focused on the development process for manufacturing prototypes (product development phase) using selective laser melting. To this end, TWIN developed a digital product service system
involving the entire additive manufacturing value chain. The aim was to optimise and monitor complex industrial systems with the help of machine learning methods in order to be able to provide meaningful recommendations for action during the production process. This master’s thesis examined heat transfer during selective laser melting for the production of metal components as a significant quality feature. The focus was on the ability of neural networks to deliver robust approximate solutions to partial differential equations. To evaluate this approach, the results were compared with classical numerical solution methods.