The overall objective addressed is the improvement of the testing and thus the overall production efficiency, while simultaneously further raising the quality rate of finished products by autonomously adapting quality-relevant production parameters. This shall be achieved via the digital twin for products and production, by which the production system will be enabled to close control loops and thus establish and advanced ZDM approach incorporating the whole process chain. Data from test steps throughout the manufacturing lines are to be collected and analyzed utilizing data mining and machine learning techniques, allowing to systematically identifying faulty products and the respective failure causes, providing the base for the intended improvements. By means of quality forecasting and simulation, (production) control decisions shall be derived at an early stage if quality deviations occur, thus avoiding further added value in ok products.