Using Topological Data Analysis to Infer the Quality in Point Cloud-based 3D Printed Objects

Introduction: 3D printing of parts is gaining incredible popularity in manufacturing. However, assessing the quality of models before they are printed remains a challenging problem, particularly when you consider point cloud based models [3], such as those that come from 3D scanners. This paper introduces an approach to quality assessment, which uses techniques from the eld of Topological Data Analysis (TDA) to compute a topological abstraction of the eventual printed model. This abstraction enables investigating certain properties of the model, with respect to print quality, and identify potential anomalies that may appear in the nal product.