Topics Real-time monitoring in Additive Manufacturing
Real-time monitoring in Additive Manufacturing In additive manufacturing, items are 3D printed layer-by-layer using materials like plastics, polymers, and metals. Unfortunately, instabilities in the printing process can produce defects like cracks, warping, and pores/voids within the printed item. Our goal at IPI is to develop computer vision systems that identify the creation of these defects in real time, then provide the 3D printer with sufficient information to intervene in a way that corrects, or avoids, the defect. Since these defects can occur over a very short amount of time (< 1 ms), our monitoring systems need to operate at very high speeds while also providing accurate results.
Melt pool monitoring: GPU-based real-time detection of pore defects using dynamic features and machine learning Using high speed cameras and photodiodes (sampling rates > 20 kHz), we are exploring AI models that can highlight defect creation.
IPI researcher Brian Booth discusses the icon Vision-in-the-Loop project results - KanaalZ video, press release, and news articles.
Vision2Reuse project: Smart cameras for the automatic monitoring of the quality of reusable packaging
iMatch (Image-based Material Characterization platform) and AM Platform (Additive Manufacturing platform)
The must-attend networking event if you need, offer, or are interested in R&D on Additive Manufacturing
Results of the UGent, VITO, Suez, and Umicore collaboration within the CHARAMBA project (EIT Raw Materials)
IPI researcher Michiel Vlaminck and partners showcase the results of the icon Analyst-PV project with a webinar and article
Demonstration of a real-time monitoring system for 3D metal printing based on AI and active learning
Brian Booth joined industry leaders earlier this year to speak on the use of AI in additive manufacturing workflows