New technology in machine learning first surpassed human performance in classifying objects in 2012. As the capacity of production lines increases, purely data-based procedures for production control are gaining in importance, which can be implemented very efficiently with this technology. As part of its digitalization initiative, Fraunhofer ISE is addressing the transfer of deep learning procedures to various links of the PV value chain. To evaluate multicrystalline silicon wafers, a sufficiently broad range of data was gathered in the »Q-Wafer«A and »Q-Crystal«B projects to allow the expected solar cell quality to be predicted already from inline measurements before solar cell production.