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Process-driven and flow-based processing of industrial sensor data

Please always quote using this URN: urn:nbn:de:bvb:20-opus-213089
  • For machine manufacturing companies, besides the production of high quality and reliable machines, requirements have emerged to maintain machine-related aspects through digital services. The development of such services in the field of the Industrial Internet of Things (IIoT) is dealing with solutions such as effective condition monitoring and predictive maintenance. However, appropriate data sources are needed on which digital services can be technically based. As many powerful and cheap sensors have been introduced over the last years, theirFor machine manufacturing companies, besides the production of high quality and reliable machines, requirements have emerged to maintain machine-related aspects through digital services. The development of such services in the field of the Industrial Internet of Things (IIoT) is dealing with solutions such as effective condition monitoring and predictive maintenance. However, appropriate data sources are needed on which digital services can be technically based. As many powerful and cheap sensors have been introduced over the last years, their integration into complex machines is promising for developing digital services for various scenarios. It is apparent that for components handling recorded data of these sensors they must usually deal with large amounts of data. In particular, the labeling of raw sensor data must be furthered by a technical solution. To deal with these data handling challenges in a generic way, a sensor processing pipeline (SPP) was developed, which provides effective methods to capture, process, store, and visualize raw sensor data based on a processing chain. Based on the example of a machine manufacturing company, the SPP approach is presented in this work. For the company involved, the approach has revealed promising results.show moreshow less

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Metadaten
Author: Klaus Kammerer, Rüdiger Pryss, Burkhard Hoppenstedt, Kevin Sommer, Manfred Reichert
URN:urn:nbn:de:bvb:20-opus-213089
Document Type:Journal article
Faculties:Medizinische Fakultät / Institut für Klinische Epidemiologie und Biometrie
Language:English
Parent Title (English):Sensors
ISSN:1424-8220
Year of Completion:2020
Volume:20
Issue:18
Article Number:5245
Source:Sensors (2020) 20:18, 5245. https://doi.org/10.3390/s20185245
DOI:https://doi.org/10.3390/s20185245
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Tag:cyber-physical systems; data stream processing; processing pipeline; sensor networks
Release Date:2022/07/13
Date of first Publication:2020/09/14
Licence (German):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International