Improving the Stability and Performance of Laser-Based Polymer 3D Printing

The enrichment project has successfully extended high-speed 3D printer monitoring capabilities to new materials, building upon the existing system developed at Flanders Make and Ghent University. The project has delivered an industrially-relevant dataset from Selective Laser Sintering (SLS) print experiments, providing crucial validation data. New synchronization scripts have been developed and integrated into the FAIR toolbox, enabling precise coordination of multiple sensors in both space and time. The existing AI models, originally designed for metal 3D printing, have been successfully adapted for some SLS printing scenarios, with comprehensive documentation of their applicability and limitations now available in the toolbox below. The monitoring system proves to maintain its high-speed performance, operating at 100 kHz, significantly outpacing traditional camera-based monitoring systems. The expanded monitoring system has proven detection and tracking of potential symptoms of polymer print quality indicators, despite the more stringent requirements and smaller error margins of polymer 3D printing compared to metal printing.

Beside the technological achievements, this enrichment project allows the researchers to clearly identify industrial requirements for SLS processes and set-up a potential industrial consortium for a follow up implementation project.

Downloads

LaserMon Toolbox - sensor fusion technique for laser-based 3D print monitoring, including scripts for spatiotemporal data synchronization. https://github.com/bgbooth/LaserMon 

Hybrid Data Fusion for Low-Cost High-Speed Monitoring in Powder Bed Fusion 3D Printing

Contact: Dries Verhees (FM), Abdellatif Bey-Temsamani (FM) and Ljilana Platisa (UGent)
Researchers: Dries Verhees (Research engineer - FM), Brian Booth (Research associate - UGent), Pieter-Jan Delvaux (Research engineer) and Stijn Helsen (Research engineer)
Research groups: Flanders Make and UGent - IPI