Bode C, Götz S, Wartzack S (2024)
Publication Language: English
Publication Type: Conference contribution, Conference Contribution
Publication year: 2024
Publisher: Elsevier B.V.
Book Volume: 129
Pages Range: 151-156
Conference Proceedings Title: Procedia CIRP
DOI: 10.1016/j.procir.2024.10.027
The mechanical joining process clinching is becoming increasingly important, especially for multi-material car body elements enabling lightweight design. However, the design of these joining points is usually based on expert knowledge and time-consuming experiments. For this reason, simulations are used in combination with surrogate models to predict the characteristics of clinch points for specific process parameters. Thereby, the process parameters are assumed to be ideal, so that inherent uncertainties are currently neglected. In order to overcome this deficiency and ensure a realistic prediction of clinch point characteristics, a consideration of variations is inevitable. Therefore, this paper analyses the transferability or significance of the nominally predicted values of existing surrogate models for clinch joints, taking into account process parameters with unavoidable variations. This shows, that the nominal parameter configuration affects the scattering of joint characteristics when considering variations. Moreover, implications for the necessary additional sampling in order to increase the significance of existing (nominal) surrogate model predictions are given, while considering the additional computational effort involved.
APA:
Bode, C., Götz, S., & Wartzack, S. (2024). On the transferability of nominal surrogate models to uncertainty consideration of clinch joint characteristics. In Xiang Jiang, Paul J. Scott, Qunfen Qi (Eds.), Procedia CIRP (pp. 151-156). Huddersfield, GB: Elsevier B.V..
MLA:
Bode, Christoph, Stefan Götz, and Sandro Wartzack. "On the transferability of nominal surrogate models to uncertainty consideration of clinch joint characteristics." Proceedings of the 18th CIRP Conference on Computer Aided Tolerancing, CAT 2024, Huddersfield Ed. Xiang Jiang, Paul J. Scott, Qunfen Qi, Elsevier B.V., 2024. 151-156.
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