About this Abstract |
Meeting |
2025 AWS Professional Program
|
Symposium
|
2025 AWS Professional Program
|
Presentation Title |
Improving Welding Efficiency With AI-Powered Vision
|
Author(s) |
Zongyao Chen, Charles Caristan, Steve Mize, Bryan Fory, Ian Unkle |
On-Site Speaker (Planned) |
Zongyao Chen |
Abstract Scope |
AI-powered machine vision is revolutionizing welding efficiency by addressing several key challenges in the manufacturing industry. This presentation outlines our solution for leveraging machine vision to enhance welding efficiency in both collaborative robot and manual welding processes.
Vision-equipped collaborative robots can identify inconsistencies in fit-up and adjust their path before welding, thereby preventing potential quality problems. Furthermore, vision-powered software analyzes weld quality post-welding, providing quantitative assessments based on spatter count and weld size. This approach ensures more consistent and dependable quality control compared to traditional manual inspection methods. |
Proceedings Inclusion? |
Undecided |