#8: Using Physics-Informed Machine Learning to Optimize 3D Printing Processes

On the 3-March-2022 at 11:00 a.m. the eighth lecture of the Living Lab lecture series took place. In this talk, ScaDS.AI scientific researcher Benjamin Uhrich explained to the audience how to use physics-informed machine learning to optimize the 3D printing process.

The lecture focused on the development of physics-informed neural networks for intelligent real-time modeling and simulation of temperature processes in additive manufacturing. The resulting digital twin can be used to efficiently predict component quality deficiencies and optimize 3D printing processes. In particular, cost and working time can be reduced.

You can rewatch this lecture on YouTube.

TU
Universität
Max
Leibnitz-Institut
Helmholtz
Hemholtz