Stereo vision enabled flexible in-situ process authentication of additive manufacturing

Abstract

Additive manufacturing (AM) has been increasingly adopted in aerospace, healthcare, and many other industries to fabricate parts with complex geometries. Despite the rapid market growth, the digital thread of AM makes it vulnerable to cyber-attacks, which raises concerns among researchers and practitioners. Notably, most of cyber-attacks maliciously manipulate the workpiece by altering the printing path. For AM authentication, it is important to monitor the printing process and detect malicious alterations in the printing path. Most existing studies mounted a camera onto the 3D printer and recorded videos of the extruder and printing bed to analyze the printing path. Besides the inconvenience and potential interferences to the AM process, these approaches are sensitive to camera positions and angles, and they are limited in the ability to precisely track the kinematics of the extruder and printing bed. To advance the state-of-the-art, this study leverages stereo vison and develops a new in-situ monitoring scheme for AM process authentication. With the stereo camera, RGB-D videos (RGB images + depth information) can be collected in real time from the extruder and printing bed. The kinematics of the extruder and bed are then estimated using optical flow and pinhole model for the reconstruction of the printing trajectory. Finally, a control chart is built upon the Hausdorff distance between the reconstructed path and the designed one (from the G-code) for the detection of printing path alterations. The developed scheme is evaluated and validated through case studies with multiple types of attack patterns.