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.