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)

Research output: Conference contribution › peer-review

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
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	https://doi.org/10.1007/978-3-031-24327-1_5
Publication status	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
Volume	607 LNNS

Conference

Conference	8th International Conference on Science, Technology and Innovation for Society, CITIS 2022
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.

Access to Document

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

Cite this

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. In 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.",

keywords = "Augmented reality, Internet of things (IoT), Weibull, WSN",

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",

language = "English",

isbn = "9783031243264",

series = "Lecture Notes in Networks and Systems",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "47--57",

editor = "Vladimir Robles-Bykbaev and Josefa Mula and Gilberto Reynoso-Meza",

booktitle = "Intelligent Technologies",

address = "Germany",

}

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. in 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).

Research output: Conference contribution › peer-review

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.

KW - Augmented reality

KW - Internet of things (IoT)

KW - Weibull

KW - WSN

UR - https://www.scopus.com/pages/publications/85151047558

U2 - 10.1007/978-3-031-24327-1_5

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

M3 - Conference contribution

AN - SCOPUS:85151047558

SN - 9783031243264

T3 - Lecture Notes in Networks and Systems

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

T2 - 8th International Conference on Science, Technology and Innovation for Society, CITIS 2022

Y2 - 22 June 2022 through 24 June 2022

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. In Robles-Bykbaev V, Mula J, Reynoso-Meza G, editors, 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

Abstract

Publication series

Conference

Bibliographical note

Access to Document

Other files and links

Fingerprint

Cite this