From Machinery to Insights: A Comprehensive Data Acquisition Approach for Battery Cell Production

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dc.identifier.uri https://www.repo.uni-hannover.de/handle/123456789/15433
dc.identifier.uri https://doi.org/10.15488/15313
dc.contributor.author Kampker, Achim
dc.contributor.author Dorn, Benjamin
dc.contributor.author Ludwigs, Robert
dc.contributor.author Clever, Henning
dc.contributor.author Kirchmann, Felix
dc.contributor.editor Herberger, David
dc.contributor.editor Hübner, Marco
dc.date.accessioned 2023-11-15T19:16:21Z
dc.date.available 2023-11-15T19:16:21Z
dc.date.issued 2023
dc.identifier.citation Kampker, A.; Dorn, B.; Ludwigs, R.; Clever, H.; Kirchmann, F.: From Machinery to Insights: A Comprehensive Data Acquisition Approach for Battery Cell Production. In: Herberger, D.; Hübner, M. (Eds.): Proceedings of the Conference on Production Systems and Logistics: CPSL 2023 - 2. Hannover : publish-Ing., 2023, S. 234-244. DOI: https://doi.org/10.15488/15313
dc.description.abstract To ensure the widespread use of sustainably produced battery cells, further progress in research is needed. The transition to automated data acquisition is complicated by the technical complexity of industrial data acquisition. Existing software solutions also fall short in meeting usability, reproducibility, extensibility, and cost-effectiveness requirements for research-scale battery production lines. To address these gaps, this paper presents and evaluates a comprehensive data acquisition and collection solution for research-scale battery production lines. It offers a systematic overview of the industrial data acquisition process, focusing on gathering data from various existing machinery and utilizing the industry standard OPC UA protocol. Given the lack of existing solutions that meet the specified requirements, the paper introduces the "ProductionPilot" software as a solution. "ProductionPilot" is designed to provide an extensible platform with a user-friendly web interface. It enables users to select, structure, monitor, and export live production data delivered via OPC UA. The effectiveness of the proposed system is validated at the CELLFAB battery production research facility at eLab of RWTH Aachen university, demonstrating its capability for long-term data acquisition and the generation of digital shadows. By addressing the limitations of current data collection methods and providing a comprehensive solution, this research aims to facilitate the broader adoption of lithium-ion batteries in renewable energy applications. eng
dc.language.iso eng
dc.publisher Hannover : publish-Ing.
dc.relation.ispartof Proceedings of the Conference on Production Systems and Logistics: CPSL 2023 - 2
dc.relation.ispartof https://doi.org/10.15488/15326
dc.rights CC BY 3.0 DE
dc.rights.uri https://creativecommons.org/licenses/by/3.0/de/deed.de
dc.subject Battery Cell Production eng
dc.subject Digitalization eng
dc.subject Automated data acquisition eng
dc.subject OPC UA eng
dc.subject Industry 4.0 eng
dc.subject.classification Konferenzschrift ger
dc.subject.ddc 620 | Ingenieurwissenschaften und Maschinenbau
dc.title From Machinery to Insights: A Comprehensive Data Acquisition Approach for Battery Cell Production eng
dc.type BookPart
dc.type Text
dc.relation.essn 2701-6277
dc.bibliographicCitation.firstPage 234
dc.bibliographicCitation.lastPage 244
dc.description.version publishedVersion
tib.accessRights frei zug�nglich


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