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 |
|