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.

Committee Chair

Ning Zhang

Committee Members

Ning Zhang Steve Cole Chiamaka Asinugo

Comments

Permanent URL: https://doi.org/10.7936/tgzb-n655

Degree

Master of Science (MS)

Author's Department

Computer Science & Engineering

Author's School

McKelvey School of Engineering

Document Type

Thesis

Date of Award

Spring 5-15-2020

Language

English (en)

Author's ORCID

https://orcid.org/0000-0003-3639-3881

Share

COinS