The optimization of the electrode manufacturing process is critical to ensure high-quality lithium-ion battery (LIB) cells, particularly for automotive applications. LIB electrode manufacturing is a complex process involving multiple steps and parameters. In this work, we aim to achieve an innovative computational approach able to optimize the battery lifespan simultaneously and evaluate the process parameters to be adopted to manufacture them. we simulate the aging curves of 200 different batteries based on their manufacturing parameters and electrode properties using PyBaMM (a Python-based modeling toolbox). Then, based on the aging curves, we optimize the corresponding battery manufacturing parameters.