A geometric reasoning approach for additive manufacturing print quality assessment and automated model correction

Abstract

The onset of affordable AM printers has democratized digital manufacturing and enabled rapid growth of the AM industry. The recent advancement of AM technology has allowed for fabrication of highly complex parts that were difficult to produce using traditional manufacturing techniques. However, designers and novice users of additive technologies often lack the awareness of manufacturing considerations leading to lower quality parts and print failures. Therefore, it is crucial to develop an automated system that can analyze and correct designs before they are sent for fabrication so that wasteful iterations of build–test–redesign can be minimized. This paper outlines fundamental geometric reasoning algorithms to enable 3D print quality assessment. The developed algorithms computationally recognize potential printing problems in a given 3D model and suggest automatic local geometric changes to the 3D model to rectify the identified printing problems. The potential problems are identified using variations of shape diameter function and morphological operations. Also, a physics-based mesh deformation scheme is developed to make localized corrections to slices for improving printability. The utility of the developed approach has been demonstrated on both 2D slice and 3D model level corrections.