AUTHOR=Heise Bettina , Zorin Ivan , Duswald Kristina , Karl Verena , Brouczek Dominik , Eichelseder Julia , Schwentenwein Martin 

TITLE=Mid-infrared optical coherence tomography and machine learning for inspection of 3D-printed ceramics at the micron scale

JOURNAL=Frontiers in Materials

VOLUME=Volume 11 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/materials/articles/10.3389/fmats.2024.1441812

DOI=10.3389/fmats.2024.1441812

ISSN=2296-8016

ABSTRACT=Here, information is provided for the inspection of 3D printed ceramics in a non-destructive way and for monitoring additive manufacturing (AM) of ceramics. Especially, a design and use of an inline Mid-infrared (MIR) Optical Coherence Tomography (OCT) system is presented, focused on printed and micro-structured specimens in lithography-based ceramic manufacturing (LCM). The detection of micro-defects (e.g., voids, inclusions, deformations) already in green ceramics parts saves energy and costs. The challenges of integration are discussed and perspectives for MIR-OCT imaging combined with machine learning (ML) are illustrated for inline inspection in LCM process of printed ceramics.