Abstract
A common process for automotive body component manufacturing is deep drawing. Launching and reworking of deep drawing tools is known as tryout process. In order to distinguish between stochastic changes and deterministic deviations already during the tool tryout, both simulated and measured data sets are required. However, especially with measured components, large data sets are generated. These often make a comparison difficult due to high computation times. In this paper, a method for reverse engineering is introduced, which allows representing complex three-dimensional component surfaces using B-Splines. The advantage here is a reduction of memory required and straightforward processing. The approach enables the comparison of numerous data sets, a springback compensation for measured, simulated or even combined data sets, as well as a separation of deterministic and stochastic deviations. Since this surface description is widely spread in the CAD world, the approach further enables a direct derivation of a new tool geometry.
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Acknowledgements
The authors would like to thank the European Research Association for Sheet Metal Processing (Europäische Forschungsgesellschaft für Blechverarbeitung e.V.) for supporting this research by funding the research project IGF 21467N-EFB 10/218.
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Maier, L., Hartmann, C., Ünver, B., Volk, W. (2022). Three-Dimensional Control Point Based Surface Description for Data Reduction, Reverse Engineering and Springback Compensation in Sheet Metal Forming. In: Inal, K., Levesque, J., Worswick, M., Butcher, C. (eds) NUMISHEET 2022. The Minerals, Metals & Materials Series. Springer, Cham. https://doi.org/10.1007/978-3-031-06212-4_24
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DOI: https://doi.org/10.1007/978-3-031-06212-4_24
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