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Authors: Ozan Yesilyurt 1 ; David Brandt 1 ; Julian Joël Grimm 1 ; Kamal Husseini 2 ; Aleksandra Naumann 3 ; 4 ; Julia Meiners 3 ; 4 and David Becker-Koch 5

Affiliations: 1 Fraunhofer Institute for Manufacturing Engineering and Automation IPA Nobelstraße 12, 70569 Stuttgart, Germany ; 2 Karlsruhe Institute of Technology, Kaiserstraße 12, 76131 Karlsruhe, Germany ; 3 Technische Universität Braunschweig, Battery LabFactory Braunschweig, Langer Kamp 8, 38106 Braunschweig, Germany ; 4 Technische Universität Braunschweig, Institute of Machine Tools and Production Technology, Langer Kamp 19b, 38106 Braunschweig, Germany ; 5 The Centre for Solar Energy and Hydrogen Research Baden-Württemberg, Lise-Meitner-Straße 24, 89081 Ulm, Germany

Keyword(s): Battery Cell Manufacturing, Database Model, Semantic Model Description.

Abstract: The global demand for batteries is increasing worldwide. To cover this high battery demand, optimizing manufacturing productivity and improving the quality of battery cells are necessary. Digitalization promises to offer great potential to address these challenges. Through data collection along the manufacturing processes, hidden correlations can be identified. However, data is highly diverse in battery cell manufacturing, complicating data analysis. A semantic data storage can increase the understanding of the relationships between the datasets, facilitating the identification of the causes of defects in manufacturing processes. To structure heterogeneous data in a semantically understandable and analyzable form, this paper presents the development of a semantic database model. The realization of this model enables structuring various datasets for simplified access and usage for increasing productivity and battery cell quality in battery cell manufacturing.

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Paper citation in several formats:
Yesilyurt, O., Brandt, D., Grimm, J. J., Husseini, K., Naumann, A., Meiners, J. and Becker-Koch, D. (2022). Development of a Semantic Database Model to Facilitate Data Analytics in Battery Cell Manufacturing. In Proceedings of the 11th International Conference on Data Science, Technology and Applications - DATA; ISBN 978-989-758-583-8; ISSN 2184-285X, SciTePress, pages 13-20. DOI: 10.5220/0011139500003269

@conference{data22,
author={Ozan Yesilyurt and David Brandt and Julian Joël Grimm and Kamal Husseini and Aleksandra Naumann and Julia Meiners and David Becker{-}Koch},
title={Development of a Semantic Database Model to Facilitate Data Analytics in Battery Cell Manufacturing},
booktitle={Proceedings of the 11th International Conference on Data Science, Technology and Applications - DATA},
year={2022},
pages={13-20},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011139500003269},
isbn={978-989-758-583-8},
issn={2184-285X},
}

TY - CONF

JO - Proceedings of the 11th International Conference on Data Science, Technology and Applications - DATA
TI - Development of a Semantic Database Model to Facilitate Data Analytics in Battery Cell Manufacturing
SN - 978-989-758-583-8
IS - 2184-285X
AU - Yesilyurt, O.
AU - Brandt, D.
AU - Grimm, J.
AU - Husseini, K.
AU - Naumann, A.
AU - Meiners, J.
AU - Becker-Koch, D.
PY - 2022
SP - 13
EP - 20
DO - 10.5220/0011139500003269
PB - SciTePress

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