Rapid Changeover and Energy Optimisation System (WP4)
This work package will devise the main algorithms and agent models to realise the cloud-based environment based on the monitoring framework and information service bus of WP3. While WP3 will provide the infrastructure, WP4 will provide the agent representation of the P&P devices and use the data captured by the agents to apply advanced algorithms that influence the self-* behaviour of the agents and consequently the system as a whole. The work to be developed will cover monitoring and regulation of the distributed environment as well as traceability aspects. More specifically WP4 will develop algorithms for: characterizing the self-organizing behaviour of the system and its trend therefore enhancing system’s visibility and debugging, reducing the ramp-up times by a proactive identification and prioritization of ramp-up tasks, dynamic product routing as a reaction to runtime system changes (plug and produce) and disturbances, improving the energy efficiency of the overall system by detecting production patterns for inactivity and high demand and relating product quality with distinct production even such as failures, system modification, self-reconfiguration and adjustment.
These algorithms will have a corresponding agent behaviour that will implement them and will be designed to work as a whole. For example active reduction of power consumption will guide dynamic routing decisions so that the most efficient routes are always chosen and the characterization of these self-organizing dynamic will identify points that require immediate action (modules that need to be replaced or reconfigured and the most favourable time frame to do so).
These algorithms are therefore centred on the agents that abstract the mechatronic environment and their interactions (virtually