Abstract
The changing industrial world in which we find ourselves has forced companies to evolve technologically, restructuring their processes and improving their human resources skills. The acceptance by management of a fourth industrial revolution in transition to a fifth has led them to look for an economical way to stay updated and with the necessary skills to optimize their production chain. This work presents the development of virtual reality (VR) system for training in detecting faults in three-phase electric motors. A sample of 30 people was used, homogeneously divided into a control group and an experimental group. To evaluate the VR systems usability, the System Usability Scale (SUS) was used, obtaining an average value of 73.33, classifying the system as efficient for the proposed task. On the other hand, in terms of time and knowledge retention, the performance of this system was compared with the execution of a conventional one. For the training time, an optimization of 57.73% was obtained, while through a p-value of 0.000003, it was confirmed that this VR system provides a novel teaching methodology for the instruction and retention of technical knowledge.
Original language | English |
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Title of host publication | 33rd European Modeling and Simulation Symposium, EMSS 2021 |
Editors | Michael Affenzeller, Agostino G. Bruzzone, Emilio Jimenez, Francesco Longo, Antonella Petrillo |
Publisher | Dime University of Genoa |
Pages | 199-207 |
Number of pages | 9 |
ISBN (Electronic) | 9788885741577 |
DOIs | |
State | Published - 2021 |
Event | 33rd European Modeling and Simulation Symposium, EMSS 2021 - Virtual, Online Duration: 15 Sep 2021 → 17 Sep 2021 |
Publication series
Name | 33rd European Modeling and Simulation Symposium, EMSS 2021 |
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Conference
Conference | 33rd European Modeling and Simulation Symposium, EMSS 2021 |
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City | Virtual, Online |
Period | 15/09/21 → 17/09/21 |
Bibliographical note
Funding Information:This work was financed in part by Universidad Tecnica de Ambato (UTA) and their Research and Development Department (DIDE) under project CONIN-P-256-2019.
Publisher Copyright:
© 2021 The Authors.
Keywords
- Induction Motors
- Industrial training
- Optimization
- System Usability Scale (SUS)
- Virtual reality