Collecting environmental and production data such as temperature, operating noise from systems and machines, air humidity or quality locally, processing and evaluating it using artificial intelligence (AI), and optimizing production by comparing it with quality and productivity parameters - that doesn't sound new, more like implementing industry 4.0. But using this approach to track process and product quality in manufacturing operations at different companies doesn't exist yet. However, it would be a game changer: component suppliers, technology providers, system integrators, even end users would receive additional information and transparency. The AdaPEdge project ventures the step from "manufacturing 4.0" to "manufacturing 4.0++" and promises more resilience and productivity.
Inferior or counterfeit materials are to be detectable, disruptions in the course of the entire value chain are to be transparent, and the production process is to be continuously adapted. The open architecture RISC-V is also used, which not only enables use in all areas of industry, but also brings high economic potential for Germany. Sensorik-Bayern GmbH is developing a sensor mesh for this purpose. The Secure Smart Sub-Edge Modules (S³EM) collect and condense AI-based freely available data and provide information on the status of the entire production line.
Project partners: 
(assoziiert:) 
English 
German