Zirngibl C, Schleich B (2021)
Publication Language: German
Publication Type: Conference contribution, Conference Contribution
Publication year: 2021
Publisher: Trans Tech Publications Ltd
Book Volume: 883
Pages Range: 105 - 110
Conference Proceedings Title: Key Engineering Materials
Event location: Virtuell
DOI: 10.4028/www.scientific.net/KEM.883.105
Due to their cost-efficiency and environmental friendliness, the demand of mechanical joining processes is constantly rising. However, the dimensioning and design of joints and suitable processes are mainly based on expert knowledge and few experimental data. Therefore, the performance of numerical and experimental studies enables the generation of optimized joining geometries. Nevertheless, the manual evaluation of the results of such studies is often highly time-consuming. As a novel solution, image segmentation and machine learning algorithms provide methods to automate the analysis process. Motivated by this, the paper presents an approach for the automated analysis of geometrical characteristics using clinching as an example.
APA:
Zirngibl, C., & Schleich, B. (2021). Approach for the Automated Analysis of Geometrical Clinch Joint Characteristics. In Merklein M, Duflou J, Fratini L, Hagenah H, Martins P, Meschut G, Micari G (Hrg.), Key Engineering Materials (S. 105 - 110). Virtuell: Trans Tech Publications Ltd.
MLA:
Zirngibl, Christoph, and Benjamin Schleich. "Approach for the Automated Analysis of Geometrical Clinch Joint Characteristics." Tagungsband 19th International Conference on Sheet Metal (SheMet 2021), Virtuell Hrg. Merklein M, Duflou J, Fratini L, Hagenah H, Martins P, Meschut G, Micari G, Trans Tech Publications Ltd, 2021. 105 - 110.
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