Modellbasierte Zustands- und Prozessüberwachung auf Basis sozio-cyber-physischer Systeme

Description

Within the scope of the fourth industrial revolution, Industry 4.0, the manufacturing industry is trying to optimize the traditional target figures of quality, costs and time as well as resource efficiency, flexibility, adaptability and resilience in volatile global markets. The focus is on the development of smart factories, in which relevant objects and humans are interconnected . Cyber-physical systems (CPS) are used as sensorized and actuatorized, resilient and intelligent overall systems to control production processes, machines and product quality . The technical complexity of production systems and their associated maintenance processes are rising due to the demands on their adaptability and the increasing automation. Challenges in the development and implementation of CPS include the lack of interoperability and reference architecture concepts as well as the insufficiently defined interaction of people and CPS.

Socio-cyber-physical systems (Socio-CPS) focus on bidirectional interaction of humans and CPS to address this problem. The scope and objective of this dissertation is to define Socio-CPS in the condition and process monitoring of smart factories. This dissertation utilizes scenarios of Socio-CPS, holistically defines system architectures and validates the solutions developed in industrial applications. The successful implementation of Socio-CPS in three heterogeneous validation scenarios proves the correctness and applicability of the solutions.