Inferring Quality in Point Cloud-based 3D Printed Objects using Topological Data Analysis

Assessing the quality of 3D printed models before they are printed remains a challenging problem, particularly when considering point cloud-based models. This paper introduces an approach to quality assessment, which uses techniques from the field of Topological Data Analysis (TDA) to compute a topological abstraction of the eventual printed model. Two main tools of TDA, Mapper and persistent homology, are used to analyze both the printed space and empty space created by the model. This abstraction enables investigating certain qualities of the model, with respect to print quality, and identifies potential anomalies that may appear in the final product.

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Handling Anomalies in Object Slicing for 3-D Printing

This paper introduces and extension to our previous papers to handle anomalies in the point based object slicing method. The anomalies handled are point, line and plane touch cases as well as overlaps. These anomalies can cause major problems in any intersection procedure, yet, they are seldom discussed, let alone handled. It turns out that the point based approach is capable of handling these special cases with minor extensions.

Handling Anomalies in Object Slicing for 3-D Printing
W Oropallo, L Piegl, P Rosen, K Rajab
Computer-Aided Design and Applications, 2019