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

Abstract

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 to compute a topological abstraction of the eventual printed model. This abstraction enables investigating certain qualities of the model, with respect to print quality, and identify potential anomalies that may appear in the final product.

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Citation

Paul Rosen, Mustafa Hajij, Junyi Tu, Tanvirul Arafin, and Les Piegl. Using topological data analysis to infer the quality in point cloud-based 3d printed objects. In CAD Conference and Exhibition, 2018.

Bibtex


@inproceedings{Rosen.2018.CAD,
  title = {Using Topological Data Analysis to Infer the Quality in Point Cloud-based 3D Printed Objects},
  author = {Paul Rosen and Mustafa Hajij and Junyi Tu and Tanvirul Arafin and Les Piegl},
  booktitle = {CAD Conference and Exhibition},
  year = {2018},
  abstract = {Assessing the quality of 3D printed models before they are printed remains 
   a challenging problem, particularly when considering point cloud based models. This 
    field of Topological Data Analysis to compute a topological abstraction of the eventual 
   printed model. This abstraction enables investigating certain qualities of the model, with 
   respect to print quality, and identify potential anomalies that may appear in the final 
   product. }
}