| About this Abstract |
| Meeting |
2024 AWS Professional Program
|
| Symposium
|
2024 AWS Professional Program
|
| Presentation Title |
Process Control of a Custom Designed Adaptive Weld Head |
| Author(s) |
Dylan S. Lewis, Bradley Jared, Shems Eddine Belhout, Jon Tatman, Darren Barborak |
| On-Site Speaker (Planned) |
Dylan S. Lewis |
| Abstract Scope |
With the age of the average welder approaching fifty-five, the welding industry is facing a shortage of workers estimated to be on the scale of four hundred thousand men and women by 2024. This workforce gap has created an ever-growing need for automated machines that can perform complex welding processes for industries like power generation. For many of these welding applications, gas tungsten arc welding (GTAW) is the preferred method for its precise heat control, cleanliness, and consistent weld quality. The University of Tennessee, Knoxville (UTK) and the Electric Power Research Institute (EPRI) have collaborated to develop an automated welding system specifically designed for GTAW welding research in the nuclear power industry. The end goal for this machine is to develop a control system and accompanying algorithms to perform multi-pass welds without any user interactions after initial system setup. The research platform is designed with five degrees of freedom, with three axes dedicated to tungsten position and two axes dedicated to wire position. Weld state monitoring is performed using a Cavitar C300 weld camera and a Keyence LJ-V7080 laser profilometer as LabVIEW performs data acquisition to both record and manage data. Algorithms for fully autonomous multi-pass welding are being developed using this system. The end goal is to create a system that is able to compute suitable process parameters and torch locations based on retrieved data pertaining to the groove geometry and previous bead geometry to automatically fill deep groove without the need for user input. |
| Proceedings Inclusion? |
Undecided |