XR-based training for technical skills in manufacturing
Journal article, 2026

Manufacturing systems are undergoing rapid transformation driven by global, economic, and sustainability pressures, increasing the need for scalable training solutions to support technical skill development and faster industrialization. However, conventional training methods for manual operations often rely on materialintensive trial-and-error, resulting in material waste, long onboarding times, and dependence on expert supervision. While Extended Reality (XR) has shown strong potential for cognitive and procedural training, its effectiveness for technical, motor-skill-based tasks remain debated due to limited physical interaction, haptic realism, and support for precise tool handling. This study addresses this gap by investigating the use of Mixed Reality (MR) for early-stage technical skill training in manual sealant application within an automotive manufacturing context. An MR training system was developed, integrating physical tools and props to preserve eye-to-hand coordination and interaction fidelity. A lab experiment evaluating tool-tracking accuracy against robotic ground truth data showed an average deviation of 7.7 mm, indicating sufficient precision for early-stage technical skill development when compared to domain specific thresholds. Furthermore, an on-site user study with 45 professional sealant operators assessed usability and acceptance. The results demonstrate high usability and strong user acceptance, with operators reporting increased confidence and reduced reliance on traditional training materials. Additionally, the MR system enabled faster training iterations while reducing material waste and setup time. These findings suggest that XR-based training can effectively support early-stage technical skill development. While evaluated in an automotive sealant application, the approach shows potential for broader applicability to manufacturing tasks requiring tool handling and motor-skills.

Motor skills

Training

Extended reality

Technical skills

Production

Manufacturing

Author

Henrik Söderlund

Chalmers, Industrial and Materials Science, Production Systems

Dan Li

Volvo Cars

Omkar Salunkhe

Chalmers, Industrial and Materials Science, Production Systems

Puranjay Mugur

Volvo Cars

Björn Johansson

Chalmers, Industrial and Materials Science, Production Systems

Journal of Manufacturing Systems

0278-6125 (ISSN)

Vol. 88 424-440

PLENary multi-User developMent arena for industrial workspaces (PLENUM)

VINNOVA (2022-01704), 2022-09-15 -- 2025-09-14.

RILIK - Framework for Immersive learning in industrial settings

VINNOVA (2025-01072), 2025-08-01 -- 2027-12-31.

Subject Categories (SSIF 2025)

Production Engineering, Human Work Science and Ergonomics

Robotics and automation

Human Computer Interaction

DOI

10.1016/j.jmsy.2026.06.019

More information

Latest update

7/16/2026