  Assessing the quality of 3D printed models before they are printed remains a
challeng- ing 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 Analy- sis (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.
