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

Introduction: In this paper, recent developments in non-destructive testing of 3D-printed ceramics and monitoring of additive manufacturing of ceramics are presented. Methods: In particular, we present the design and use of an inline midinfrared optical coherence tomography (MIR-OCT) system to evaluate printed and micro-structured specimens in lithography-based ceramic manufacturing (LCM). Results: The proposed system helps with the detection of microdefects (e.g., voids, inclusions, deformations) that are already present in green ceramic components, thereby reducing the energy and costs incurred. Discussion: The challenges during integration are discussed. Especially, the prospects for MIR-OCT imaging combined with machine learning are illustrated with regard to inline inspection during LCM of printed ceramics. [ABSTRACT FROM AUTHOR]