Sauer C, Schleich B, Wartzack S (2020)
Publication Type: Journal article
Publication year: 2020
Book Volume: 91
Pages Range: 905-910
URI: https://www.archiv.mfk.tf.fau.de?file=pubmfk_5f6c5c26a86d0
DOI: 10.1016/j.procir.2020.02.247
Sheet-bulk metal forming (SBMF) is an emerging manufacturing technology that offers vast potential for lightweight design and functional integration. However, product designers often lack information about the required manufacturing parameters for their specific design. This problem is currently tackled by a knowledge acquisition process from manufacturing experts in combination with meta-modelling techniques. These meta-models predict resulting manufacturing parameters for given part design properties. When employing this design-for-manufacturing approach, it is key for product designers to evaluate many design alternatives that are all manufacturable with given forming machines. This is currently done by a genetic algorithm-based optimization of the meta-models with regard to manufacturing features. This papers proposes a novel approach for generating many design alternatives based on the meta-models and gathering them in a solution space. In doing so it is possible to review all manufacturable sheet-bulk metal forming part variants and let the product designers decide which part design fits best. The approach is applied to a locking teeth part, which highlights the usability of the new method.
APA:
Sauer, C., Schleich, B., & Wartzack, S. (2020). Meta-model based generation of solution spaces in sheet-bulk metal forming. Procedia CIRP, 91, 905-910. https://doi.org/10.1016/j.procir.2020.02.247
MLA:
Sauer, Christopher, Benjamin Schleich, and Sandro Wartzack. "Meta-model based generation of solution spaces in sheet-bulk metal forming." Procedia CIRP 91 (2020): 905-910.
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