Predictive Maintenance in Distributed Environments

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Abstract
In this paper we present a concept to implement predictive maintenance in distributed environments. A distributed environment can involve several problems to be solved such as the different speed and frequency of data, the different priorities of data sources, the different dimensions and data structures and also the volume of the data to be processed. There are software, frameworks, algorithms to work out these problems, however the interoperability is harder to maintain between these. Recently it become possible to use historical and real-time datasets of parameters and key performance indicators of environments in order to prevent failures and monitor the system state. The aim is to outline a solution, using open-source tools, to support the lifecycle from the data extraction, through the transformation and algorithmic steps, until the usage and visualization of the gained information and feedback of the data to the environment.- Title
- Predictive Maintenance in Distributed Environments
- Author
- Sik, Dávid
- Ekler, Péter
- Levendovszky, János
- Date of issue
- 2022
- Access level
- Open access
- Copyright owner
- Budapest University of Technology and Economics
- Conference title
- The First Conference on ZalaZONE Related R&I Activities of Budapest University of Technology and Economics 2022
- Conference place
- Budapest University of Technology and Economics
- Conference date
- 2022.03.31
- Language
- en
- Page
- 85 - 88
- Subject
- data lake, distributed environment, predictive maintenance, time series
- Version
- Kiadói változat
- Identifiers
- DOI: 10.3311/BMEZalaZONE2022-018
- Title of the container document
- Proceedings of The First Conference on ZalaZONE Related R&I Activities of Budapest University of Technology and Economics 2022
- ISBN, e-ISBN
- ISBN 978-963-421-873-9
- University
- Budapest University of Technology and Economics
- Faculty
- Faculty of Transportation Engineering and Vehicle Engineering
- Department
- Department of Automotive Technologies