This book presents a data-driven approach for continuous battery cell process steps.

This approach focuses on the optimization, monitoring and control of economical and environmental targets.

For this, it utilizes data-driven models which are able to describe sequential dependencies of the training data in order to extract temporal relationships out of large amounts of continuous production data.

Extracted relationships can then be used to support decision during production system planning or operation.

The approach is exemplary applied to a continuous mixing use case for anode slurry preparation.