Big Data architecture for intelligent maintenance: a focus on query processing and machine learning algorithms

Big Data architecture for intelligent maintenance: a focus on query processing and machine learning algorithms

Abstract Exploiting available condition monitoring data of industrial machines for intelligent maintenance purposes has been attracting attention in various application fields. Machine learning algorithms for fault detection, diagnosis and prognosis are popular and easily accessible. However, our ex...

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Bibliographic Details
Main Authors: Claude Lehmann, Lilach Goren Huber, Thomas Horisberger, Georg Scheiba, Ana Claudia Sima, Kurt Stockinger
Format: Article
Language:English
Published: SpringerOpen 2020-08-01
Series:Journal of Big Data
Subjects:
Prognostics and health management
Intelligent maintenance
Big data architecture
Heterogeneous data integration
Stream processing
Query processing
Online Access:http://link.springer.com/article/10.1186/s40537-020-00340-7

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http://link.springer.com/article/10.1186/s40537-020-00340-7

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