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  4. Cause-Effect Relationships in Battery Cell Production - Data based validation of expert knowledge in electrode production
 
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2023
Journal Article
Title

Cause-Effect Relationships in Battery Cell Production - Data based validation of expert knowledge in electrode production

Abstract
The advancing climate change requires a shift from conventional energy sources to renewable ones, which is accompanied by the indispensability of an efficient and sustainable storage of electrical energy. The production of lithium-ion battery cells comprises an enormous complexity, as it consists of several interlinked process steps, each with different quality requirements for the (intermediate) products and the processes itself. This complexity means that a supposedly insignificant process parameter can lead to errors and deviations in the manufactured products via complex cause-effect relationships, that are not fully known. The missing knowledge of the processes and inter-process interdependencies lead to difficulties in the setup of a suitable quality assurance in battery cell production to reduce scrap rates. Beside these potentials in planning and optimizing the process chain of the battery cell factory of tomorrow are impeded.We developed a method to build up a relevant knowledge base on cause-effect relationships for battery cell production. Expert knowledge based on experience and intuition has been collected and quantitative cause-effect relationships are established. This knowledge is used to set up the initial data acquisition, ensuring relevant data being available for analysis. Afterwards, the data analysis, that validates and extends this expert knowledge, is defined. This approach is applied to real-world use-cases including machinery and laboratory equipment in battery cell production. The electrode production is selected as the basis for validation. The found inter-relationships either validate the qualitative expert knowledge, contradict this prior knowledge or else add new insights about the battery cell electrode production process that have not been considered in the qualitative expert knowledge. Methods used include correlations and a predictive power score for non-linear interdependencies. The cause-effect relationships are constantly updated by automatically analyzing the production data of the digital factory. These identified and validated cause effect relationships allow the planning of efficient and sustainable battery cell production and data-based process chain optimization.
Author(s)
Fitzner, Antje  orcid-logo
Fraunhofer-Einrichtung Forschungsfertigung Batteriezelle FFB  
Abramowski, Johann-Philip  
Fraunhofer-Institut für Produktionstechnologie IPT  
Schmetz, Arno
Fraunhofer-Einrichtung Forschungsfertigung Batteriezelle FFB  
Krauß, Jonathan  orcid-logo
Fraunhofer-Einrichtung Forschungsfertigung Batteriezelle FFB  
Borzutzki, Kristina
Fraunhofer-Einrichtung Forschungsfertigung Batteriezelle FFB  
Eckstein, Markus Christian
Fraunhofer-Einrichtung Forschungsfertigung Batteriezelle FFB  
Pouls, Kevin Bernard
Fraunhofer-Einrichtung Forschungsfertigung Batteriezelle FFB  
Baum, Christoph  
Fraunhofer-Institut für Produktionstechnologie IPT  
Schmitt, Robert H.  
TH Aachen -RWTH-, Laboratorium für Werkzeugmaschinen und Betriebslehre -WZL-  
Kampker, Achim
Fraunhofer-Einrichtung Forschungsfertigung Batteriezelle FFB  
Journal
Procedia CIRP  
Project(s)
FoFeBat - Research Fab Battery Cells  
FoFeBat - Research Fab Battery Cells  
FoFeBat - Research Fab Battery Cells  
Funder
Bundesministerium für Bildung und Forschung -BMBF-  
Bundesministerium für Bildung und Forschung -BMBF-
Bundesministerium für Bildung und Forschung -BMBF-
Conference
Conference on Manufacturing Systems 2023  
Open Access
DOI
10.1016/j.procir.2023.09.021
10.24406/publica-2526
File(s)
Fitzner, Abramowski et al 2023 - Cause-Effect Relationships in Battery Cell.pdf (687.76 KB)
Rights
CC BY-NC-ND 4.0: Creative Commons Attribution-NonCommercial-NoDerivatives
Language
English
Fraunhofer-Einrichtung Forschungsfertigung Batteriezelle FFB  
Fraunhofer-Institut für Produktionstechnologie IPT  
Fraunhofer Group
Fraunhofer-Verbund Produktion  
Keyword(s)
  • battery cell production

  • cause-effect relationships

  • digital factory

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