TY - THES

T1 - Digital Shadow for condition monitoring of a tool machine frame with specific load conditions

AU - Skall, Benjamin Emil

N1 - embargoed until 02-12-2027

PY - 2022

Y1 - 2022

N2 - Digitalization provides new possibilities to generate, process and analyze data. One tool is the so-called Digital Shadow, a pre-step of the Digital Twin. Both represent a digital entity of a real physical system. The main task of the Digital Shadow in this work is the condition monitoring of a tool machine frame under specific load conditions. The Shadow receives the process parameters consisting of process force, tool length and tool position and computes the partial damage for each process run. Through linear damage accumulation, these partial damages are summed and reflect the current damage state of the machine. With stress data, determined by multiple simulations of individual small tools along the machine table, it is possible to compute the stress data of load cases that have not been specifically simulated. This is possible because of the superposition principle, which is applicable due to the linear-elastic material deformations occurring in this work. The applicability of this principle is proved in this work. The result of this work is a Digital Shadow in the form of several Python scripts communicating with each other. It is possible to compute the damage progress for each process step based on the already mentioned process parameters. In addition, it is possible to process previously determined load spectra or load scenarios and thus analyze different frame designs, more precisely their hot-spot areas, which are defined during the simulation modeling, for their structural durability and their behavior under specific load conditions. The Digital Shadows algorithm is designed in such a way that it is possible to process improved simulation models and different frame designs of machines with the same process conditions, as long as the naming rules for datasets, defined in this thesis, are respected.

AB - Digitalization provides new possibilities to generate, process and analyze data. One tool is the so-called Digital Shadow, a pre-step of the Digital Twin. Both represent a digital entity of a real physical system. The main task of the Digital Shadow in this work is the condition monitoring of a tool machine frame under specific load conditions. The Shadow receives the process parameters consisting of process force, tool length and tool position and computes the partial damage for each process run. Through linear damage accumulation, these partial damages are summed and reflect the current damage state of the machine. With stress data, determined by multiple simulations of individual small tools along the machine table, it is possible to compute the stress data of load cases that have not been specifically simulated. This is possible because of the superposition principle, which is applicable due to the linear-elastic material deformations occurring in this work. The applicability of this principle is proved in this work. The result of this work is a Digital Shadow in the form of several Python scripts communicating with each other. It is possible to compute the damage progress for each process step based on the already mentioned process parameters. In addition, it is possible to process previously determined load spectra or load scenarios and thus analyze different frame designs, more precisely their hot-spot areas, which are defined during the simulation modeling, for their structural durability and their behavior under specific load conditions. The Digital Shadows algorithm is designed in such a way that it is possible to process improved simulation models and different frame designs of machines with the same process conditions, as long as the naming rules for datasets, defined in this thesis, are respected.

KW - Digitalization

KW - Digital Shadow

KW - FEM

KW - Object-Oriented-Programming

KW - Principle of Superposition

KW - Python

KW - Structural Durability

KW - Betriebsfestigkeit

KW - Digitaler Schatten

KW - Digitalisierung

KW - FEM

KW - Objektorientierte Programmierung

KW - Python

KW - Superpositionsprinzip

M3 - Master's Thesis

ER -