Low-Cost Fault Prediction System for a Rolling System on an Augmented Reality Platform with Cloud Communication

Andrés Carvajal Andrade; Kevin Pazmiño Tintín; Johanna Celi; William Montalvo

doi:10.1007/978-3-031-24327-1_5

Low-Cost Fault Prediction System for a Rolling System on an Augmented Reality Platform with Cloud Communication

Andrés Carvajal Andrade
, Kevin Pazmiño Tintín
, Johanna Celi
, William Montalvo

Grupo de Investigación en Electrónica Control y Automatización (GIECA)

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución de conferencia › revisión exhaustiva

Resumen

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.

Idioma original	Inglés
Título de la publicación alojada	Intelligent Technologies
Subtítulo de la publicación alojada	Design and Applications for Society - Proceedings of CITIS 2022
Editores	Vladimir Robles-Bykbaev, Josefa Mula, Gilberto Reynoso-Meza
Editorial	Springer Science and Business Media Deutschland GmbH
Páginas	47-57
Número de páginas	11
ISBN (versión impresa)	9783031243264
DOI	https://doi.org/10.1007/978-3-031-24327-1_5
Estado	Publicada - 2023
Evento	8th International Conference on Science, Technology and Innovation for Society, CITIS 2022 - Guayaquil, Ecuador Duración: 22 jun 2022 → 24 jun 2022

Serie de la publicación

Nombre	Lecture Notes in Networks and Systems
Volumen	607 LNNS

Conferencia

Conferencia	8th International Conference on Science, Technology and Innovation for Society, CITIS 2022
País/Territorio	Ecuador
Ciudad	Guayaquil
Período	22/06/22 → 24/06/22

Nota bibliográfica

Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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10.1007/978-3-031-24327-1_5

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Carvajal Andrade, A., Pazmiño Tintín, K., Celi, J., & Montalvo, W. (2023). Low-Cost Fault Prediction System for a Rolling System on an Augmented Reality Platform with Cloud Communication. En V. Robles-Bykbaev, J. Mula, & G. Reynoso-Meza (Eds.), Intelligent Technologies: Design and Applications for Society - Proceedings of CITIS 2022 (pp. 47-57). (Lecture Notes in Networks and Systems; Vol. 607 LNNS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-24327-1_5

Carvajal Andrade, Andrés ; Pazmiño Tintín, Kevin ; Celi, Johanna et al. / Low-Cost Fault Prediction System for a Rolling System on an Augmented Reality Platform with Cloud Communication. Intelligent Technologies: Design and Applications for Society - Proceedings of CITIS 2022. editor / Vladimir Robles-Bykbaev ; Josefa Mula ; Gilberto Reynoso-Meza. Springer Science and Business Media Deutschland GmbH, 2023. pp. 47-57 (Lecture Notes in Networks and Systems).

@inproceedings{fddc65b2f732400091aef5a730e9069b,

title = "Low-Cost Fault Prediction System for a Rolling System on an Augmented Reality Platform with Cloud Communication",

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.",

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author = "\{Carvajal Andrade\}, Andr{\'e}s and \{Pazmi{\~n}o Tint{\'i}n\}, Kevin and Johanna Celi and William Montalvo",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 8th International Conference on Science, Technology and Innovation for Society, CITIS 2022 ; Conference date: 22-06-2022 Through 24-06-2022",

year = "2023",

doi = "10.1007/978-3-031-24327-1\_5",

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series = "Lecture Notes in Networks and Systems",

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Carvajal Andrade, A, Pazmiño Tintín, K, Celi, J & Montalvo, W 2023, Low-Cost Fault Prediction System for a Rolling System on an Augmented Reality Platform with Cloud Communication. En V Robles-Bykbaev, J Mula & G Reynoso-Meza (eds.), Intelligent Technologies: Design and Applications for Society - Proceedings of CITIS 2022. Lecture Notes in Networks and Systems, vol. 607 LNNS, Springer Science and Business Media Deutschland GmbH, pp. 47-57, 8th International Conference on Science, Technology and Innovation for Society, CITIS 2022, Guayaquil, Ecuador, 22/06/22. https://doi.org/10.1007/978-3-031-24327-1_5

Low-Cost Fault Prediction System for a Rolling System on an Augmented Reality Platform with Cloud Communication. / Carvajal Andrade, Andrés; Pazmiño Tintín, Kevin; Celi, Johanna et al.
Intelligent Technologies: Design and Applications for Society - Proceedings of CITIS 2022. ed. / Vladimir Robles-Bykbaev; Josefa Mula; Gilberto Reynoso-Meza. Springer Science and Business Media Deutschland GmbH, 2023. p. 47-57 (Lecture Notes in Networks and Systems; Vol. 607 LNNS).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución de conferencia › revisión exhaustiva

TY - GEN

T1 - Low-Cost Fault Prediction System for a Rolling System on an Augmented Reality Platform with Cloud Communication

AU - Carvajal Andrade, Andrés

AU - Pazmiño Tintín, Kevin

AU - Celi, Johanna

AU - Montalvo, William

PY - 2023

Y1 - 2023

N2 - 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.

AB - 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.

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KW - Internet of things (IoT)

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DO - 10.1007/978-3-031-24327-1_5

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AN - SCOPUS:85151047558

SN - 9783031243264

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SP - 47

EP - 57

BT - Intelligent Technologies

A2 - Robles-Bykbaev, Vladimir

A2 - Mula, Josefa

A2 - Reynoso-Meza, Gilberto

PB - Springer Science and Business Media Deutschland GmbH

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ER -

Carvajal Andrade A, Pazmiño Tintín K, Celi J , Montalvo W. Low-Cost Fault Prediction System for a Rolling System on an Augmented Reality Platform with Cloud Communication. En Robles-Bykbaev V, Mula J, Reynoso-Meza G, editores, Intelligent Technologies: Design and Applications for Society - Proceedings of CITIS 2022. Springer Science and Business Media Deutschland GmbH. 2023. p. 47-57. (Lecture Notes in Networks and Systems). doi: 10.1007/978-3-031-24327-1_5

Low-Cost Fault Prediction System for a Rolling System on an Augmented Reality Platform with Cloud Communication

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