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Vertical data continuity with lean edge analytics for industry 4.0 production

Title data

Küfner, Thomas ; Schönig, Stefan ; Jasinski, Richard ; Ermer, Andreas:
Vertical data continuity with lean edge analytics for industry 4.0 production.
In: Computers in Industry. Vol. 125 (February 2021) . - No. 103389.
ISSN 0166-3615
DOI: https://doi.org/10.1016/j.compind.2020.103389

Project information

Project financing: Bayerisches Staatsministerium für Wissenschaft, Forschung und Kunst

Abstract in another language

Industry 4.0 is characterized by the digitization and networking of machines and systems in production. The amount of data in production is increasing, providing information about processes and thus enables the autonomous monitoring, control and optimization of value creation processes. However, there have been several open challenges and current research questions identified. In particular, new solutions need to be scalable and high-performing to deal with the growing volumes of data close to real-time. The work at hand tackles these research gaps by presenting an approach to realize vertical data continuity by combining signal acquisition and simultaneous data evaluation in a decentralized system without the use of time-consuming external cloud solutions. The approach has been evaluated in laboratory as well as in industrial settings.

Further data

Item Type: Article in a journal
Refereed: Yes
Keywords: Edge analytics; Industry 4.0; Smart sensors; Machine learning
Institutions of the University: Faculties > Faculty of Engineering Science > Chair Manufacturing and Remanufacturing Technology > Chair Manufacturing and Remanufacturing Technology - Univ.-Prof. Dr.-Ing. Frank Döpper
Result of work at the UBT: Yes
DDC Subjects: 600 Technology, medicine, applied sciences > 620 Engineering
Date Deposited: 11 Jan 2021 13:10
Last Modified: 11 Jan 2021 13:10
URI: https://eref.uni-bayreuth.de/id/eprint/61549