Abstract
Lithium-ion-batteries (LIBs) play a key role in determining the environmental impacts of future mobility technologies. In particular, the production of LIBs has a strong environmental impact as it is characterized by high scrap rates. In addition to existing expert-based approaches for the identification of quality drivers in production, a trend towards data-driven methods is discernible. Nevertheless, most approaches show shortcomings in the involvement of multi-criteria optimization. Therefore, this paper uses desirability functions to jointly optimize several quality parameters. Validation was conducted based on the data of an assembly line for prismatic LIBs.
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