Abstract
The application of Augmented Reality (AR) technologies within the industry has allowed for improving preventive and predictive maintenance techniques, thanks to the fact that they allow information to be presented in real time and in the same analyzed environment, which ensures that maintenance operational processes improve. This work presents the development of a predictive system for thermal stress failures, by applying the analysis of the Weibull statistical model and the use of free AR tools and cloud technology, which allow determining the reliability and average lifetime of induction coils in real time of a rolling system. The temperature data were obtained through a wireless sensor network (WSN) that sends the data to an embedded system (Raspberry Pi 4), which behaves as the communication channel (Gateway) between the sensors and the cloud, through the MQTT server. The results are presented in graphs and are promised under the Weibull model.
Original language | English |
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Title of host publication | Intelligent Technologies |
Subtitle of host publication | Design and Applications for Society - Proceedings of CITIS 2022 |
Editors | Vladimir Robles-Bykbaev, Josefa Mula, Gilberto Reynoso-Meza |
Publisher | Springer Science and Business Media Deutschland GmbH |
Pages | 47-57 |
Number of pages | 11 |
ISBN (Print) | 9783031243264 |
DOIs | |
State | Published - 2023 |
Event | 8th International Conference on Science, Technology and Innovation for Society, CITIS 2022 - Guayaquil, Ecuador Duration: 22 Jun 2022 → 24 Jun 2022 |
Publication series
Name | Lecture Notes in Networks and Systems |
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Volume | 607 LNNS |
ISSN (Print) | 2367-3370 |
ISSN (Electronic) | 2367-3389 |
Conference
Conference | 8th International Conference on Science, Technology and Innovation for Society, CITIS 2022 |
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Country/Territory | Ecuador |
City | Guayaquil |
Period | 22/06/22 → 24/06/22 |
Bibliographical note
Publisher Copyright:© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Keywords
- Augmented reality
- Internet of things (IoT)
- Weibull
- WSN