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

• DOI: 10.1016/j.procir.2023.09.021
• Publication Date: 2024-01-12T09:08:17Z
• Authors: A. Fitzner; J.-P. Abramowski; A. Schmetz; J. Krauß; K. Borzutzki; M. Eckstein; K. Pouls; C. Baum; R.H. Schmitt; A. Kampker
• Keywords: Scrap

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 electrical energy. production lithium-ion battery cells comprises enormous complexity, as it consists several interlinked process steps, each with different quality requirements for (intermediate) products processes itself. This complexity means that supposedly insignificant parameter can lead errors deviations in manufactured via complex cause-effect relationships, are not fully known. missing knowledge inter-process interdependencies difficulties setup suitable assurance cell reduce scrap rates. Beside these potentials planning optimizing chain factory tomorrow impeded. We developed method build up relevant base on relationships production. Expert based experience intuition has been collected quantitative established. used set initial data acquisition, ensuring being available analysis. Afterwards, analysis, validates extends this expert knowledge, defined. approach applied real-world use-cases including machinery laboratory equipment electrode selected basis validation. found inter-relationships either validate qualitative contradict prior or else add new insights about have considered knowledge. Methods include correlations predictive power score non-linear interdependencies. constantly updated automatically analyzing digital factory. These identified validated allow data-based optimization.