The aim of the FRAME project is a paradigm shift from a conventional, resource-intensive, and largely human driven ramp-up and system integration process to human-centred automated assembly systems with self-awareness and self-learning capabilities enabled by the development of an integrated methodology and tools.
Developing new methods to achieve self-aware assembly systems.
Developing methods for human-centred automated ramp-up, system optimisation and adaptation.
Developing new ways to re-use ramp-up strategies and experience in a self-learning production environment.
Supporting the step-change from purely human-driven ramp-up and system integration to proactive self-adaptive human-machine environments.
Integrating and enhancing state-of-the-art machines and production systems with sensor capabilities and metrology as a basis for real-time system awareness.
Current manufacturing systems rely on intensive human interactions and expert knowledge during the ramp-up process and in the event of fluctuations in the production process. Furthermore, self-learning mechanisms and re-use of experience are not being applied to speed-up system integration or for product-process optimisation. FRAME will address these gaps through the development of a Self-Adaptive Assembly System that will support the shift from manual ramp-up and rigid volume production to automated, self-learning and self-aware production systems that adapt autonomously to disruptions.
The FRAME outcomes will target the creation of a new generation of self-aware, self-learning and self-adapting assembly systems that are much easier to deploy, can proactively cooperate with human operators and machines to adapt during ramp-up and can react faster to fluctuations and disruptive events. This will drastically decrease system ramp-up times and downtimes, leading to increasing productivity and yield.
Developing behaviour models at station and system levels enhancing Self-Awareness.