Initial work on the characterization of additive manufacturing (3D printing) using software image analysis

Abstract

A current challenge in additive manufacturing (commonly known as 3D printing) is the detection of defects. Detection of defects (or the lack thereof) in bespoke industrial manufacturing may be safety critical and reduce or eliminate the need for testing of printed objects. In consumer and prototype printing, early defect detection may facilitate the printer taking corrective measures (or pausing printing and alerting a user), preventing the need to re-print objects after the compounding of a small error occurs. This paper considers one approach to defect detection. It characterizes the efficacy of using a multi-camera system and image processing software to assess printing progress (thus detecting completion failure defects) and quality. The potential applications and extrapolations of this type of a system are also discussed.