Abstract
In the production chain of Lithium-ion battery (LIB) cells, various processes influence intermediate product features, which then influence the LIB performance. It is important to know these influences in order to improve product quality and to control the production. This paper presents a concept for a data-driven cyber-physical system based on quality gates in LIB cell manufacturing. The concept utilizes data-driven modelling in order to predict the performance of future LIB cells by using quality gates of intermediate product features. This prediction of product performance enables a better assessment of intermediate product quality and helps deriving recommendations for latter processes.
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