Prediction of Belt Drive Faults in Case of Predictive Maintenance in Industry 4.0 Platform
Continuous production maintenance cost is among one of the highest operational expenses for manufacturing companies. Proper planning of maintenance interventions results in optimized equipment use, higher product quality, and reduced costs. For a belt drive usefulness, it is important that it is pro...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-11-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/11/21/10307 |
| _version_ | 1797512772698767360 |
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| author | Artur Pollak Sebastian Temich Wojciech Ptasiński Jacek Kucharczyk Damian Gąsiorek |
| author_facet | Artur Pollak Sebastian Temich Wojciech Ptasiński Jacek Kucharczyk Damian Gąsiorek |
| author_sort | Artur Pollak |
| collection | DOAJ |
| description | Continuous production maintenance cost is among one of the highest operational expenses for manufacturing companies. Proper planning of maintenance interventions results in optimized equipment use, higher product quality, and reduced costs. For a belt drive usefulness, it is important that it is properly stretched and has no defects. However, manual condition assessment requires a production line stop, which in turn causes production to stop with associated consequences. Continuous fault diagnosis for anomalies is a fundamental step in estimating a component’s remaining service life and then obtaining a reliable predictive maintenance system that reduces production costs. The presented work presents an approach to anomaly detection based on the vibrations obtained from the operation of the belt transmission. |
| first_indexed | 2024-03-10T06:06:25Z |
| format | Article |
| id | doaj.art-4acd168c4a8945aab35f5a0c4343a601 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T06:06:25Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-4acd168c4a8945aab35f5a0c4343a6012023-11-22T20:30:52ZengMDPI AGApplied Sciences2076-34172021-11-0111211030710.3390/app112110307Prediction of Belt Drive Faults in Case of Predictive Maintenance in Industry 4.0 PlatformArtur Pollak0Sebastian Temich1Wojciech Ptasiński2Jacek Kucharczyk3Damian Gąsiorek4APA Group, Tarnogórska 251 Street, 44-105 Gliwice, PolandAPA Group, Tarnogórska 251 Street, 44-105 Gliwice, PolandAPA Group, Tarnogórska 251 Street, 44-105 Gliwice, PolandAPA Group, Tarnogórska 251 Street, 44-105 Gliwice, PolandFaculty of Mechanical Engineering, Silesian University of Technology, Konarskiego 18A Street, 44-100 Gliwice, PolandContinuous production maintenance cost is among one of the highest operational expenses for manufacturing companies. Proper planning of maintenance interventions results in optimized equipment use, higher product quality, and reduced costs. For a belt drive usefulness, it is important that it is properly stretched and has no defects. However, manual condition assessment requires a production line stop, which in turn causes production to stop with associated consequences. Continuous fault diagnosis for anomalies is a fundamental step in estimating a component’s remaining service life and then obtaining a reliable predictive maintenance system that reduces production costs. The presented work presents an approach to anomaly detection based on the vibrations obtained from the operation of the belt transmission.https://www.mdpi.com/2076-3417/11/21/10307Industry 4.0mechanical engineeringbelt drive faultspredictive maintenance |
| spellingShingle | Artur Pollak Sebastian Temich Wojciech Ptasiński Jacek Kucharczyk Damian Gąsiorek Prediction of Belt Drive Faults in Case of Predictive Maintenance in Industry 4.0 Platform Applied Sciences Industry 4.0 mechanical engineering belt drive faults predictive maintenance |
| title | Prediction of Belt Drive Faults in Case of Predictive Maintenance in Industry 4.0 Platform |
| title_full | Prediction of Belt Drive Faults in Case of Predictive Maintenance in Industry 4.0 Platform |
| title_fullStr | Prediction of Belt Drive Faults in Case of Predictive Maintenance in Industry 4.0 Platform |
| title_full_unstemmed | Prediction of Belt Drive Faults in Case of Predictive Maintenance in Industry 4.0 Platform |
| title_short | Prediction of Belt Drive Faults in Case of Predictive Maintenance in Industry 4.0 Platform |
| title_sort | prediction of belt drive faults in case of predictive maintenance in industry 4 0 platform |
| topic | Industry 4.0 mechanical engineering belt drive faults predictive maintenance |
| url | https://www.mdpi.com/2076-3417/11/21/10307 |
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