Amr Mohamed Ali, El-Adl Mohamed, Soumaya Yacout and Yasser Shaban
Article (2020)
|
Open Access to the full text of this document Published Version Terms of Use: Creative Commons Attribution Download (732kB) |
Abstract
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
| 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: | 11 Jan 2026 05:57 |
| 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 |
|---|---|
Statistics
Total downloads
Downloads per month in the last year
Origin of downloads
Dimensions
