Case Study:
How Photoneo's 3D Vision Powers Elementiam's Adaptive Welding Automation
Traditional welding robots are built for high-volume, low-variation production. In custom fabrication, every pipe spool and weld groove is different. One-off programming often costs more than manual welding. Download the full case study to find out how Photoneo helped Elementiam develop an adaptive robotic welding solution powered by 3D vision.
Download the full case study to discover:
- ~80% Faster Robot Programming: Spool welding path programming dropped from roughly 8–9 minutes to 142 seconds.
- Welding That Adapts Like a Human: See how the Photoneo scan data is fitted to a CAD model, a CAM model, or a nominal mesh built from the scan itself.
- Make it run in 5 button clicks: Discover the ABSA-certified spool welding cell. Machine learning identifies the weld area and generates a full procedure.
- Accuracy at Every Scale: Learn why the accuracy of Photoneo's structured light scanning and its range of scanning volumes were critical.
- Proven ROI and Safer Work: Understand the payback window of 10–12 months for high-volume shops and 12–24 months for most others.