WeldAR: Augmenting Live Hands-On Training with In-Situ Guidance for Novice Learners

TL;DR

WeldAR, an Augmented Reality (AR) system with five learning modules that overlays real-time guidance during live welding using a headset integrated into a welding helmet and a torch attachment, is presented.

Abstract

Extended Reality (XR) systems for physical skill training have largely emphasized simulation rather than real-time in-situ instruction. We present WeldAR, an Augmented Reality (AR) system with five learning modules that overlays real-time guidance during live welding using a headset integrated into a welding helmet and a torch attachment. We conducted an in-situ within-subjects study with 24 novices, comparing AR guidance to video instruction for live welding across practice and unassisted tests. AR improved performance in both assisted practice and unassisted tests, primarily driven by gains in travel speed and work angle. By offering real-time feedback on four performance measures, AR supported novices in carrying embodied knowledge into independent tasks. Our contributions include: (1) WeldAR for in-situ physical skill training; (2) empirical evidence that AR enhances composite welding performance and key physical skills; and (3) implications for the development of AR systems that support in-situ, embodied skill training in welding and related trades.

Figures (19)

• Figure 1: Left: A student performs live welding with a customized helmet integrating a Meta Quest 3; WeldAR provides in-helmet guidance. Right: WeldAR’s interface displays real-time feedback during live welding on travel speed, standoff (CTWD), and work/travel angles to suggest technique adjustments.
• Figure 2: A novice student is learning how to weld in the welding booth by learning fundamental skill parameters, including (a) Contact Tip to Work Distance (CTWD), (b) Travel angle, (c) Work angle, and (d) Travel speed.
• Figure 3: Welding coupons that students use to train on welding. (a) shows broken weld lines and (b) shows ideal welded lines. Image (b) indicates that the novice student stayed within the acceptable range of the welding parameters, including CTWD, Travel Speed, Travel Angle, and Work Angle. While (a) indicates that the novice student performed outside the acceptable range.
• Figure 4: The images on the right show the 3D-printed hardware components of WeldAR: (a) Customized 3D-printed welding helmet equipped with a Meta Quest 3 headset (b) Customized 3D-printed controller bracket attached to the welding torch (c) Customized 3D-printed calibration station attached to the workbench. The systems diagram on the left shows a student learning MIG welding with the setup, and how all these components are connected.
• Figure 5: System workflow diagram showing sound trigger and performance data collection.