New TUM Publication Showcases Learning by Printing

We are pleased to share that AM2PM partners from the Technical University of Munich (TUM), Luca Bettermann, Martin Slepicka, Sebastian Esser, and André Borrmann, have published a new research paper titled Data-Driven Parameter Calibration in Additive Manufacturing. The paper has been accepted for publication in the proceedings of the 32nd EG-ICE International Workshop on Intelligent Computing in Engineering, to be held from July 1 to 3, 2025, in Glasgow, Scotland.

The paper introduces the Learning by Printing framework, a novel approach designed to enhance performance and robustness in extrusion-based additive manufacturing for construction. Built on the foundation of Fabrication Information Modelling (FIM), the framework combines evaluation, prediction, and calibration processes into a unified, closed-loop system for fabrication learning.

Future developments will focus on scaling the framework to more complex systems and incorporating online learning for real-time process control, advancing Learning by Printing toward a fully predictive and adaptive digital fabrication method.

This work represents a significant step forward in the AM2PM project’s mission to bridge automation and data intelligence in 3D concrete printing. We congratulate the TUM team on this achievement.