Continuously growing demand of high quality, customised and sustainable products, requires more and more self-adaptive, flexible and efficient productions systems. Therefore, intelligent production processes are of crucial relevance for the future of all production machinery and their next development steps in automation technology. Such production processes will properly integrate artificial intelligence (AI) and particularly Machine Learning (ML) heuristic methodologies, besides traditional formal modelling and control techniques.

To increase under all conditions the autonomy of machines, their self-tuning capacities, and to correct faults and uncertainties of raw materials and complex processes, hybrid intelligent production systems, integrating heuristic and formal methods, are regarded as the means of choice. This assessment is supported by the awareness that all modeling attempts of processes and machines to predict and control their behavior are limited in accuracy, on the one hand, and that more and more data and analytics instruments are available, on the other hand. Thus, the research in this field focuses on the combination of deterministic modeling with ML and AI solutions, which promises to be the optimal trade-off between data processing technologies and previously gained human knowledge on the considered production processes.