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Cloud computing based unsupervised fault diagnosis system in the context of Industry 4.0

Amr Mohamed Ali, El-Adl Mohamed, Soumaya Yacout and Yasser Shaban

Article (2020)

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New online fault monitoring and alarm systems, with the aid of Cyber-Physical Systems (CPS) and Cloud Technology (CT), are examined in this article within the context of Industry 4.0. The data collected from machines is used to implement maintenance strategies based on the diagnosis and prognosis of the machines' performance. As such, the purpose of this paper is to propose a Cloud Computing Platform containing three layers of technologies forming a Cyber-Physical System which receives unlabelled data to generate an interpreted online decision for the local team, as well as collecting historical data to improve the analyzer. The proposed troubleshooter is tested using unlabelled experimental data sets of rolling element bearing. Finally, the current and future Fault Diagnosis Systems and Cloud Technologies applications in the maintenance field are discussed.

Uncontrolled Keywords

Remote Fault Diagnosis System (RFDS); Logical Analysis of Data (LAD); Cyber-Physical System (CPS); Pattern recognition; Industry 4.0; Cloud computing; Sistema de diagnóstico remoto de falhas (RFDS); Análise lógica de dados (LAD); Sistema físico cibernético (CPS); Reconhecimento de padrões; Indústria 4.0; Computação em nuvem

Subjects: 2700 Information technology > 2702 Computer systems organization
2700 Information technology > 2714 Mathematics of computing
Department: Department of Mathematics and Industrial Engineering
Funders: CAPES
PolyPublie URL: https://publications.polymtl.ca/10596/
Journal Title: Gestão & Produção (vol. 27, no. 3)
Publisher: Scientific Electronic Library Online
DOI: 10.1590/0104-530x5378-20
Official URL: https://doi.org/10.1590/0104-530x5378-20
Date Deposited: 18 Jul 2023 15:44
Last Modified: 05 Apr 2024 13:54
Cite in APA 7: Ali, A. M., Mohamed, E.-A., Yacout, S., & Shaban, Y. (2020). Cloud computing based unsupervised fault diagnosis system in the context of Industry 4.0. Gestão & Produção, 27(3), 19 pages. https://doi.org/10.1590/0104-530x5378-20


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