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<p>The deep drawing process in the automotive industry generates up to 45% material waste. To address this issue, the folding–shearing process was developed as a drop-in solution, enabling the formation of parts in pure shear with minimal thickness variation. This process involves folding a blank while collecting the excess material in a region called the ‘beak’, which is subsequently sheared in-plane using a single set of tools moving in one forming direction. This paper investigates the extent to which the curvature of the geometry of the beak influences the resulting thickness distribution. A combination of physical and numerical trials demonstrates that a beak design with a negative Gaussian curvature reduces the maximum thickening by 65%. This reduction in thickening helps minimise the forming loads and tool wear, thereby improving the overall robustness of the process. An analytical model is proposed to predict the resulting thickness distribution and demonstrates accuracy within a 12.5% deviation from experimental results. Finally, a design map is proposed to instantly identify the optimal beak design parameters without the need for extensive numerical or physical validations while ensuring a minimal thickness change.</p>

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Shear dominated deformation with curved beaks in folding–shearing

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年6月11日

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  • Rishabh Arora,
  • Omer Music,
  • Julian M. Allwood

摘要

The deep drawing process in the automotive industry generates up to 45% material waste. To address this issue, the folding–shearing process was developed as a drop-in solution, enabling the formation of parts in pure shear with minimal thickness variation. This process involves folding a blank while collecting the excess material in a region called the ‘beak’, which is subsequently sheared in-plane using a single set of tools moving in one forming direction. This paper investigates the extent to which the curvature of the geometry of the beak influences the resulting thickness distribution. A combination of physical and numerical trials demonstrates that a beak design with a negative Gaussian curvature reduces the maximum thickening by 65%. This reduction in thickening helps minimise the forming loads and tool wear, thereby improving the overall robustness of the process. An analytical model is proposed to predict the resulting thickness distribution and demonstrates accuracy within a 12.5% deviation from experimental results. Finally, a design map is proposed to instantly identify the optimal beak design parameters without the need for extensive numerical or physical validations while ensuring a minimal thickness change.