Qualitätsüberwachung mit Generative Adversarial Networks als Alternative zur Angussprobe für den Großguss

paper-conference
Quality monitoring using Generative Adversarial Networks as an alternative to test coupons in large-scale casting.
Authors

Felix Weber

Yao Yao

Lutz Horbach

Andrés Felipe Posada Moreno

Alexander Bezold

Christoph Broeckmann

Published

January 1, 2023

Doi

10.48447/WP-2023-266

Abstract

This paper investigates the use of Generative Adversarial Networks (GANs) for quality monitoring in large-scale casting as an alternative to the traditional test coupon approach. The proposed method leverages GANs to model the expected quality characteristics and detect deviations, enabling non-destructive quality assessment in the casting process.

Citation

@inproceedings{weber2023qualitaetsueberwachung,
 author = {Weber, Felix and Yao, Yao and Horbach, Lutz and Posada Moreno, Andrés Felipe and Bezold, Alexander and Broeckmann, Christoph},
 booktitle = {Tagung Werkstoffprüfung 2023},
 date = {2023},
 doi = {10.48447/WP-2023-266},
 title = {Qualitätsüberwachung mit Generative Adversarial Networks als Alternative zur Angussprobe für den Großguss}
}