Intelligent Production Systems
Intelligent, Reconfigurable, Distributed Cyber-Physical Production Systems
Description
Due to the ever-increasing complexity and dimensions in industrial automation, the distribution of intelligence and automation tasks among system components is necessary. The research topic’s main challenge is to explore the advantages of distributed systems such as enhanced reliability, reusability and modularity contrary to the main disadvantages e.g. the extended need of communication. Current researches deal with the implementation and optimization of distributed systems itself regarding functional and non-functional requirements. Several aspects of distributed systems are addressed.
At AIS, notations, methods and tools are developed for the design of agent-oriented automation software for machines and production plants in both the manufacturing and process automation domain. By that, the design, implementation and operation of distributed, intelligent cyber-physical production systems can be simplified, comprehensibility can be increased and, thus, acceptance in industry can be enhanced.
In 2014, AIS was able to establish a joined demonstrator “myJoghurt” that shows the capabilities of agent-based approaches in the context of Industrie 4.0. In collaboration with 5 German institutes, this open research demonstrator has been developed and established. Together with international robot companies the same architecture and platform was applied for a collaborative production. Using simple scenarios, the coupling of locally distributed production systems in an automatic and dynamic manner can be demonstrated.
MyJoghurt - Industrie-4.0-Demonstrator
RIAN - Industrie 4.0 und Roboter – Robot Integrated Agent Network
OR.NET - Sichere dynamische Vernetzung in Operationssaal und Klinik
CAR@TUM - Energiemanagement III
TDebituM - Technical Debt Identification and Assessment in Mechatronic Systems Using Indicators, Patterns and Metrics
InSeLDiP - Intensification of separation processes in the food industry through digital twins and intelligent process control