The AI-based iterated 3D Printing supports cost-effective production for small batch sizes, batch size 1, and prototyping. While with large batch sizes the cost of design is negligible, with small batch sizes the cost of design is much more significant. We employ generative AI to aid designers and reduce both the cost and the length of the design process. Specifically, we are developing a framework wherein a designer without technical knowledge can guide a generative algorithm by iteratively selecting designs among a batch of AI-generated ones. The final product is then 3D-printed to allow for a hands-on evaluation of its design and its physical and practical characteristics.

©Technical University of Munich. TUM School of Computation, Information and Technology. Chair of Data Processing. Munich Institute of Robotics and Machine Intelligence (MIRMI).


Luca Sacchetto

KI.FABRIK Research and Development (PaaS)