Status
In Progress
Material Class
Polymers / E-Scrap
specific materials
23-01-RM-6016

Image-Based Machine Learning for Component Identification for Remanufacturing

NODE
Technical Thrust
Remanufacturing & EOL Reuse
Robust Non-destructive Inspection/Evaluation Technologies
About

This project proposes to develop an automated image-based part type identification in the production environment. The goal is to implement the process at CoreCentric’s remanufacturing floor and demonstrate a 50% increase in processing speed and a 20% yield increase. Additionally, this project aims to remove subjectivity from the process of identification and inspection.

Upon completion, this project expects to reduce primary feedstock by 67,000 metric tons (MMT) of metals, polymers, and e-waste, reduce energy consumption by 13 PJ, and decrease emissions by 1.5 MMCO2e.

project Members
Corecentric solutions logo
Rochester institute of technology logo

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