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Mastering complexity is a growing challenge in production. From the design of a device to the manufacturing process, new degrees of freedom are created that often cannot be adequately grasped by humans. In most practical applications today, a full-factor experimentation across all possible combinations has been replaced by "Design of Experiments" (DoE) methods. In addition, methods based on Monte Carlo simulations enable constant progress in speed and reliability of virtual experimentation. Machine learning (ML) as a precursor of artificial intelligence has already demonstrated its capabilities in this area for logistics and finance.