Innovating Casting Quality Control Through Robotics and Artificial Vision

Ensuring product quality in steel continuous casting is crucial for meeting industry standards. Traditional methods focus on molten steel, overlooking issues during solidification and billet production. This paper proposes a comprehensive monitoring approach using robotic systems with computer vision to measure billet shapes and identify defects such as surface cracks, inclusions, and dimensional deviations in real time. Advanced robotics also enhance product labeling reliability. This technology improves quality control efficiency, reduces downtime and waste, and supports more sustainable, cost-effective steel production.

Authors:

Mr. Rafael Jacob | Polytec USA Corp.
 

Session Chairs:

Jim Gilmore | Shinagawa Advanced Materials Americas, Inc.
 

Dan Green | Nucor Steel Tuscaloosa, Inc.