Support-Structure Decision in 3D Printing With Unsupervised Computer Vision Available to Purchase

In 3D printing, support-structure decisions for CAD models heavily rely on expert knowledge. Automatically evaluating CAD geometry and deciding the need for support structures remains challenging. This study adopts the Oriented Fast and Rotated BRIEF feature detector and descriptor to match geometric features among CAD models and predict support-structure decisions for printing a new CAD model. This work demonstrates the potential of automating 3D printing process planning with AI tools.