Enhancing Manufacturing Training Through Augmented Situated VisualizationShow others and affiliations
2026 (English)In: Human-Computer Interaction – INTERACT 2025 - 20th IFIP TC 13 International Conference, 2025, Proceedings, Springer Nature , 2026, p. 66-71Conference paper, Published paper (Refereed)
Abstract [en]
Traditional training methods in industrial environments often lack real-time guidance and interactive feedback, which can make knowledge sharing challenging. Augmented Situated Visualization (SV) can improve industrial training by providing in-depth, spatially relevant instructions, which are particularly valuable when safety procedures are crucial. This work describes a tool for SV deployed on a commercial headset and investigates how two different SV patterns, 2D labels and 3D ghosts, impact user experience, workload, discomfort, task completion time, and memory recall in a training scenario for machine maintenance.
Place, publisher, year, edition, pages
Springer Nature , 2026. p. 66-71
Keywords [en]
AR, HCI, Industrial Training, Situated Visualization
National Category
Human Computer Interaction Production Engineering, Human Work Science and Ergonomics Computer Sciences Computer Systems
Identifiers
URN: urn:nbn:se:kth:diva-371719DOI: 10.1007/978-3-032-05008-3_14Scopus ID: 2-s2.0-105016569722OAI: oai:DiVA.org:kth-371719DiVA, id: diva2:2008231
Conference
20th IFIP TC 13 International Conference on Human-Computer Interaction, INTERACT 2025, Belo Horizonte, Brazil, Sep 8 2025 - Sep 12 2025
Note
Part of ISBN 9783032050076
QC 20251022
2025-10-222025-10-222025-10-22Bibliographically approved