Abstract
Industry 4.0 has gained drive in the last few years since most companies at the industrial level need to update and optimize their production chain. Restructuring their processes and improving their human resources skills is imperative if they want to remain competitive. This research presents the development of a virtual reality system for induction motor troubleshooting training. Two sample groups were taken as references. The first one was trained with the VR system, while the second group worked with a conventional methodology. With the use of the proposed system, there was a time reduction of 57.73%. In terms of knowledge acquisition, it was possible to confirm, with a p-value lower than 0.05, that the VR system is more efficient than the conventional methodology. Finally, the system’s usability was evaluated utilizing the System Usability Scale (SUS), obtaining an average value of 73.33.
Original language | English |
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Title of host publication | Augmented Reality, Virtual Reality, and Computer Graphics - 8th International Conference, AVR 2021, Proceedings |
Editors | Lucio Tommaso De Paolis, Pasquale Arpaia, Patrick Bourdot |
Publisher | Springer Science and Business Media Deutschland GmbH |
Pages | 499-510 |
Number of pages | 12 |
ISBN (Print) | 9783030875947 |
DOIs | |
State | Published - 2021 |
Event | 8th International Conference on Augmented Reality, Virtual Reality and Computer Graphics, AVR 2021 - Virtual, Online Duration: 7 Sep 2021 → 10 Sep 2021 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 12980 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 8th International Conference on Augmented Reality, Virtual Reality and Computer Graphics, AVR 2021 |
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City | Virtual, Online |
Period | 7/09/21 → 10/09/21 |
Bibliographical note
Funding Information:The authors recognize the supported bringing by Universidad Tecnica de Ambato (UTA) and their Research and Development Department (DIDE) under project CONIN-P-256-2019.
Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
Keywords
- Induction motors
- Industrial training
- Optimization
- Virtual reality