iRVision Applications for Welding

In this Tech Transfer, Ian Chaykowski from FANUC’s Material Joining Group demonstrates how to apply iRVision in arc welding applications. The video explores how iRVision can be used for inspection, offset detection, and process verification, offering a faster alternative to traditional methods such as touch sensing. The tutorial begins with a discussion on the importance of lighting in vision applications. Proper lighting—such as red LED lights and filters—is essential for reliable image capture, especially in environments affected by overhead lights, welding arcs, or sunlight. IRVision and touch sensing are compared, highlighting iRVision’s speed and suitability for thin materials and error-proofing tasks like clamp checking. He presents examples of effective iRVision applications, including closed-shape detection, tab-in-slot joints, and cope welds, where consistent geometry and lighting ensure accurate results. The video then walks through a real-world example using iRVision to verify a clamp’s position, locate a plug weld using 2D vision, and verify weld completion using inverse logic. Viewers see how geometric pattern matching and score thresholds are used to determine part alignment and weld success. Next, Ian demonstrates iRVision in a cutting application. Using histogram tools, he shows how to detect whether a slug has dropped post-cut by analyzing pixel brightness. He also introduces AI error proofing, where the system is trained with pass/fail examples to identify defects. The video concludes with practical advice: protect cameras in harsh welding environments, use lighting to enhance edge detection, and consider a feasibility study using ROBOGUIDE and virtual cameras to test setups before implementation. Watch for a comprehensive look at how iRVision enhances welding and cutting processes through fast, reliable, and intelligent visual inspection.