ORCID
https://orcid.org/0000-0003-3639-3881
Date of Award
Spring 5-15-2020
Degree Name
Master of Science (MS)
Degree Type
Thesis
Abstract
Many industries are rapidly adopting additive manufacturing (AM) because of the added versatility this technology offers over traditional manufacturing techniques. But with AM, there comes a unique set of security challenges that must be addressed. In particular, the issue of part verification is critically important given the growing reliance of safety-critical systems on 3D printed parts. In this thesis, the current state of part verification technologies will be examined in the con- text of AM-specific geometric-modification attacks, and an automated tool for 3D printed part verification will be presented. This work will cover: 1) the impacts of malicious attacks on AM using geometrically-modified 3D models, 2) a 3D part reconstruction approach from medical imaging scans, 3) a mesh alignment technique based on point set registration, de- signed to handle abnormal part geometries, and 4) an automatic error detection and defect visualization tool for comparing the geometric similarity of 3D printed parts to their intended geometries.
Language
English (en)
Chair
Ning Zhang
Committee Members
Ning Zhang Steve Cole Chiamaka Asinugo
Included in
Computer-Aided Engineering and Design Commons, Graphics and Human Computer Interfaces Commons, Information Security Commons, Molecular, Cellular, and Tissue Engineering Commons, Other Biomedical Engineering and Bioengineering Commons, Other Computer Sciences Commons
Comments
Permanent URL: https://doi.org/10.7936/tgzb-n655