Requirements of smart CPS environments
The 4th industrial revolution is characterized by self-optimization, -coordination, and -configuration of its processes. It is expected to revolutionize various domains, ranging from Smart Factories to Healthcare, Energy, Mobility, Buildings and Cities. The Industry-of-the Future is characterized by a strong interaction between the physical and the virtual surroundings of its Cyber-Physical Systems (CPS) that form the basis for intelligent connected production systems.
The SCHEIF project will investigate requirements of smart CPS environments for supporting diverse lesser controlled interactions between CPSs and human workers. SCHEIF targets enabling an evolution of CPSs making them capable of autonomously apprehending and understanding their environments. SCHEIF aims to design a hardware and software reference architecture, decision flows, and additional technical enablers for smart Decentralized Cyber-Physical Environments (D-CPE). As core concept, the project will integrate intelligent, context-aware, connected and responsive agents.
#IoT #Industry 40 #Security
The key to the 4th Factory Revolution is the convergence of Internet of Things, Industrial Robotics and Artificial Intelligence.
- Decentralized Production Control: Locally optimized decision-making agents are capable of gathering all required information for taking decisions autonomously, as well as autonomously evolving and adapting according to the environment. SCHEIF will enable Objective-oriented Production, allowing agents to autonomously design, control, and contribute to a production line;
- Plug-and-Produce: Highly flexible production lines are implemented using standardized Internet technologies and agile agents on constrained devices. SCHEIF will enable Adaptable Factories, capable of rapidly evolving their production lines to fast evolving demands;
- Hybrid-level Cooperation: Agents being an integral and autonomous part of a production line will cooperate with each other and with humans. SCHEIF will enable Hybrid Teams, where team members, irrespectively being human or robots will distribute their roles according to their capabilities and maximize the efficiency and effectiveness of the production line.