In situ real time defect detection of 3D printed parts

Additive manufacturing (AM) allows for the production of custom parts with previously impractical internal features, but comes with the additional possibility of internal defects due to print error, residual stress buildup, or cyber-attack by a malicious actor. Conventional post process analysis techniques have difficulty detecting these defects, often requiring destructive tests that compromise the integrity (and thus the purpose) of the part. Here, we present a "certify-as-you-build" quality assurance system with the capability to monitor a part during the print process, capture the geometry using three-dimensional digital image correlation (3D-DIC), and compare the printed geometry with the computer model to detect print errors in situ. A test case using a fused filament fabrication (FFF) 3D printer was implemented, demonstrating in situ error detection of localized and global defects. (C) 2017 Elsevier B.V. All rights reserved.