Virtual Reality Opportunities in the Reduction of Occupational Hazards in Industry 4.0
Author(s): |
David Checa Cruz
Kim Martinez Roque Alfredo Osornio Rios Andres Bustillo |
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Medium: | journal article |
Language(s): | Spanish |
Published in: | DYNA, 1 November 2021, n. 6, v. 96 |
Page(s): | 620-626 |
DOI: | 10.6036/10241 |
Abstract: |
This work discuss the possibilities of Immersive Virtual Reality (iVR) environments in occupational risk prevention in the manufacturing industry. Firstly, a framework for iVR experiences design is presented. Secondly, two examples to demonstrate the usefulness of this scheme for the detection of occupational hazards are discussed. In the first one, the worker controls an overhead crane in a realistic iVR environment. Realism is searched to intensify user´s presence in the iVR and, therefore, learning effectiveness. Visual quality is maximized and natural movements and load´s inertias are programmed with this objective. The user performs different critical operations in this application. The tasks becomes more complex while the user gets used to the iVR serious game: noise level, bad lighting, presence of other workers in the working area and, especially, load unbalance. Under these conditions, the user must carry out different common tasks while avoiding accidents. In the second one, the worker moves through a factory and identifies different risk situations, taking the corresponding corrective measures. While in the first application, the user interacts with the virtual environment using a real overhead crane keypad to increase his immersion, in the second one a standard iVR interface is used, because it simulates in a natural way the interaction with virtual objects. In both cases, a data acquisition system, including positioning and eyetracking, allows the trainer to directly provide feedback to the user on his performance. Keywords: Virtual Reality; Occupational Risk Prevention; Industry 4.0; Overhead crane; Educational Games |
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data sheet - Reference-ID
10641189 - Published on:
30/11/2021 - Last updated on:
30/11/2021