Hybrid artificial intelligence for intelligent sensors and actuators in production (KISA)

In the context of Industry 4.0, reliability, flexibility and adaptability are important requirements for sensors and actuators (such as motors, valves, pumps, etc.) in the entire production process. So-called self-x capabilities allow a system to independently derive actions and make adjustments. The aim of the project is to develop self-x capabilities for intelligent sensors and actuators. To this end, various artificial intelligence approaches are being combined: While data-based machine learning methods are designed to learn effectively from data but are difficult to comprehend, knowledge-based methods are based on a more comprehensible approach through logical reasoning but are more difficult to build. Both methods are combined in the project and complemented by classical approaches based on technical-mathematical models. The combination allows the advantages of the different methods to be combined and weaknesses to be compensated for. The implementation takes place as an energy-efficient, data-saving edge AI solution.