Segmentação de objetos para impressão 3D

Abstract

The Additives Manufacturing (ADs) market, popularly known as 3D printing, is constantly growing. Undoubtedly, ADs have proven to be useful and revolutionary for various industry segments. However, 3D printing machines have a physical limitation related to their printing volume, which leads to the segmentation of parts for printing. Splitting a 3D object intelligently is not trivial and many works have already been carried out in this context, but there are still few studies aimed at the ADs market. What makes this process complex is the number of variables that must be taken into account for segmentation. Faced with the difficulties of the partitioning process, this work aims to present a 3D object segmentation solution taking into account the printing dimensions. The work aims to produce an intelligent automated solution that receives a 3D object and returns the smallest number of segments, taking full advantage of the print volume. The prototype implements an object scanner, an object viewer, and a method to find intersections among vertexes and sides that receives as input the quality features of the segment and the chosen learning method.