The EASY project aims at the energy-efficient analysis and execution of manufacturing and control processes in the context of dynamic industrial manufacturing. In an edge-cloud continuum, transitionless and low-threshold industrial manufacturing is monitored in a process-based manner and controlled in a resource-optimized manner. A dynamic interoperable runtime environment incorporates customizable AI value-added services combined with expert knowledge for analysis and in turn uses these for optimization of manufacturing planning and control.
In the manufacturing organization following the guiding principle of Industrie 4.0 (I4.0), edge computing enables data sovereign, near-real-time processing of data directly at the place of generation. The significant reduction in latency resulting from edge computing will drive the production-oriented use of industrial AI applications in the analysis and control of manufacturing processes. This promises to increase productivity and resource efficiency for the entire manufacturing process. Up to now, technical barriers, in particular the integration of IT (Information Technology) and OT (Operational Technology), have made it impossible to utilize the benefits of edge computing.
Manufacturing companies are enabled to process their custom data both locally on distributed edge nodes and on central cloud servers. Dynamic AI-based scheduling of manufacturing services incorporating experiential knowledge ensures optimized execution and utilization of compute resources within the network, reduced latency and constant data transfer rates. Within this continuum, a scalable and high-performance infrastructure enables dynamic execution of compute processes between centralized cloud and decentralized edge instances.
The EASY project is being implemented by a consortium of leading research institutions and companies and is funded by the German Federal Ministry of Economics and Climate Protection.
Partners
- Empolis Information Management GmbH
- Deutsches Forschungszentrum für Künstliche Intelligenz GmbH
- Robert Bosch GmbH
- Fraunhofer IOSB-INA
- Hochschule Trier – Umwelt-Campus Birkenfeld
- ArtiMinds Robotics GmbH
- coboworx GmbH
