Virtual Reality System for training in the detection and solution of failures in induction motors

Gustavo Caiza, Marco Riofrio-Morales, C. Veronica Gallo, T. Santiago Alvarez, Wilson O. Lopez, Marcelo V. Garcia

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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 languageEnglish
Title of host publication33rd European Modeling and Simulation Symposium, EMSS 2021
EditorsMichael Affenzeller, Agostino G. Bruzzone, Emilio Jimenez, Francesco Longo, Antonella Petrillo
PublisherDime University of Genoa
Pages199-207
Number of pages9
ISBN (Electronic)9788885741577
DOIs
StatePublished - 2021
Event33rd European Modeling and Simulation Symposium, EMSS 2021 - Virtual, Online
Duration: 15 Sep 202117 Sep 2021

Publication series

Name33rd European Modeling and Simulation Symposium, EMSS 2021

Conference

Conference33rd European Modeling and Simulation Symposium, EMSS 2021
CityVirtual, Online
Period15/09/2117/09/21

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

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