Automated Part Numbering for 3D Printed Medical Devices for Covid-19 Response using Generative Design Methodologies

Thousands of 3D printers across Canada are producing PPE for frontline workers. Different printers and materials affect the quality and safe re-usability of parts. Trying to track down this information for every single one of millions of parts would be impossible. The purpose of this project is to improve the quality and safe re-use of 3D printed PPE by developing a system for printing a unique identification code onto every single part that will let end users know what type of material was used and how and when the part was printed.

Faculty Supervisor:

Keith Doyle

Student:

Richard Kennedy

Partner:

3DQue Systems

Discipline:

Medicine

Sector:

Manufacturing

University:

Emily Carr University of Art and Design

Program:

Accelerate

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