The aim of the FRAME project is a paradigm shift from the conventional human-driven ramp-up and system integration process to fully automated, self-learning and self-aware production systems. In particular, the project will deliver new methods to represent structure, capability and behaviour not only on machine level, but from a holistic point-of-view. This overall view allows the production system to actually understand the effects of process to the others, thereby allowing the development of novel methods to automatically detect bottlenecks, errors and potential for system optimisations with regards to the fine-tuning of processes. Furthermore, the project will integrate time-compressed simulation sandpits with a self-learning manufacturing environment that allows to automatically propose strategies to fine-tune processes during the ramp-up or in response to changes or disruptive events. The outcomes of the project will therefore facilitate the development of self-learning production systems that are easy to deploy and can react to fluctuations and disruptive events. This in turn, will drastically decrease system ramp-up times and down-times for European industrial sectors and thereby increasing productivity and yield. For system integrators it will particular lay the foundation for the successful system-to-service transformation from static capital-intensive production lines towards using dynamic manufacturing services on demand. The project aim is supported by the following key objectives: • Developing self-aware manufacturing systems enable by sensor enhanced machines • New self-learning strategies to accelerate the ramp-up, system optimisation and reaction to disruptive events • Supporting the system-to-service transformation in manufacturing by automating the deployment of manufacturing services into the line