Assisted defect detection by in-process monitoring of additive manufacturing using optical imaging and infrared thermography

Layer-wise in-process monitoring in Fused Filament Fabrication (FFF) 3D printing can facilitate the detection of defects introduced during manufacturing. In this work, optical imaging and infrared (IR) thermography were used simultaneously for the detection of embedded defects, such as point and line defects. The optical images helped in identifying the necessary variables that can lead to real-time defect detection through image correlation. Through temperature monitoring and thermal image analysis, defect detection was accomplished by comparing to a baseline. It was found that as the number of embedded defects increased in a specimen, the average specimen temperature, T̃_specimen, increased. An increase in the number of defects by 2X and 5X led to an increase in T̃_specimen that is ∼18X and 37X the relative standard error. There was also a positive correlation between the global average hotspot temperature, T̃_hotspot, and the total number of embedded defects in the specimen. This study demonstrates that in-situ defect detection can be accomplished using optical and thermal imaging systems.