As an example of the current battery manufacturing modeling approaches, Figure shows an illustration of a simplified and experimentally validated PBM used for an electrode manufacturing pipeline. This model is being developed in the context of the ARTISTIC Digitalization Initiative, initially supported by a European Research Council project . The steps within this modeling framework involve the simulation of the electrode slurry followed by a homogenized drying and consequent calendering process at different compression degrees. Each step of this pipeline being carefully parametrized for different slurry and electrode properties (like density, porosity, and thickness). The final output are 3D electrode microstructures which are also characterized for structural effects like tortuosity factor. . Depending on the desired electrode material and experimental data, different types of particles can be considered inside the simulations (previous works include NMC , Graphite or even electrodes for ASSBs ). The additional electrochemically inactive materials such as the conductive additives and the binder can also be considered as a singular entity, named as Carbon Binder Domain (CBD) . The data generated at each step of the ARTISTIC pipeline are further utilized for formulation optimization via the use of various AI tools . In a nutshell, by leveraging pilot line experimental data, physics-based simulations at the mesoscale and AI/ML, this combined approach demonstrates a powerful tool for manufacturing optimization with the goal of reducing scrap rates at source.