Interaktive Analyse und Optimierung Digitaler Zwillinge

Dissertation, Rheinisch-Westfälische Technische Hochschule Aachen, 2022; Aachen : RWTH University Aachen 1 Online-Ressource : Illustrationen, Diagramme (2022). = Dissertation, Rheinisch-Westfälische Technische Hochschule Aachen, 2022
In the course of the fourth industrial revolution (“Industry 4.0”), a vast variety of novel concepts and technologies are emerging: smart factories and products, cyber-physical systems and autonomous robots, networked sensors and cloud computing in the Internet of Things, as well as Digital Twins—mostly defined as the “virtual digital representation of physical assets”. All of these developments are motivated by desired productivity gains, achieved through the optimization of plants, processes, and products. When used as basis for the optimization process, Digital Twins offer a promising approach. Once developed, they can be used without risk where alternatives are dangerous, impractical or expensive, because as virtual objects in the digital world they are subject to special laws: their data is available at all times, thus perfect copies can be made instantaneously and with virtually no cost. In order to harness Digital Twins for prediction and optimization, realistic simulation models are required, which can then be combined with methods of simulation-based optimization. This thesis provides the design and implementation of a modular architecture for interactive analysis and optimization of Digital Twins. The developed methodology for simulation-based decision support can be used to answer specific questions about the modeled systems, such as “Where should the robotic arm and sensors of a manufacturing cell be mounted for optimal energy efficiency?”, “How does the landing gear of a Mars rover behave on difficult terrain?”, or “How can imminent collisions of autonomously driving vehicles be detected and prevented?”. Another important contribution of this work is the novel formalism for describing the analysis and optimization capabilities of Digital Twins. Multiple reference implementations from industrial, space, and underwater robotics as well as from the automotive sector and forestry demonstrate the viability of the developed concept.
Published by RWTH University Aachen, Aachen