From art to part: Learning from the traditional smith in developing flexible sheet metal forming processes

From art to part: Learning from the traditional smith in developing flexible sheet metal forming processes
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DOI:
10.1016/j.jmatprotec.2021.117337
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发表时间:
2022
影响因子:
6.3
通讯作者:
Daniel T. Bowen;Iacopo M. Russo;Christopher J. Cleaver;J. Allwood;E. Loukaides
Daniel T. Bowen;Iacopo M. Russo;Christopher J. Cleaver;J. Allwood;E. Loukaides
中科院分区:
材料科学1区
文献类型:
--
作者:
Daniel T. Bowen;Iacopo M. Russo;Christopher J. Cleaver;J. Allwood;E. Loukaides

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传统的金属铁匠具有非凡的能力,可以用几种通用工具从平板上形成各种形状的零件。这种多功能性对现在寻求多样化零件目录和降低模具成本的制造商越来越有吸引力。尽管如此,这些传统技术的费力和手工性质使它们无法满足现代的大批量需求。然而,一些技术已经成为发展新的柔性金属成形工艺的起点,要么通过创造新的工艺,密切复制传统技术,要么通过自动化手工过程。在这里,我们仔细研究了传统铁匠用来形成薄片的一些技术,并回顾了这些过程的自动化适应。我们发现,这些适应过程的决策元素还没有它们的手工对应程序那么有能力,这表明我们仍然可以从传统的铁匠那里学到很多东西。因此,我们着眼于金属成型领域内外的技术和方法,这些技术和方法可用于捕捉铁匠的熟练动作,以及如何使用所得数据来增强机械化变体的设计和操作。
The traditional metal smith has the remarkable capability to form a variety of part shapes from flat sheets using only a few universal tools. Such versatility is increasingly appealing to manufacturers who now seek to diversify part catalogues and reduce tooling costs. Despite this utility, the laborious, manual nature of these traditional techniques preclude them from meeting modern-day, high-volume demand. However, some techniques have served as starting points for the development of new flexible metal forming processes, either through creating new processes that closely replicate the traditional techniques or by automating the manual process. Here, we look closely at some of the techniques used by the traditional smith to form sheets and review automated adaptations of these processes. We find that decision-making elements of these adapted processes are not yet as capable as their manual counterparts, suggesting there is still a lot we can learn from the traditional smith. As such, we look both within and beyond the domain of metal forming at the technologies and the methods that can be used to capture the skilled actions of the smith and how the resulting data can be used to enhance the design and operation of mechanised variants.