Macro-structured Deep Drawing of Steel Alloys - Influenceability on Thinning and Drawing Forces

Wolf, A.; Tulke, M.; Brosius, A.

doi:10.1007/978-3-031-47394-4_66

Cited by 1 publication

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“…Nevertheless, uncertainties remain that can influence the manufacturing process and result in out-of-tolerance parts. Deep drawing with macro-structured tools can offer a solution to this challenge, as the process is very tolerant of known influencing factors such as friction conditions in the flange area, shape of the blank, and the resulting thickness [26] and offers a robust process despite alternating conditions.…”

Section: Process Robustness and Influencing Parametersmentioning

confidence: 99%

Robustness of macro-structured deep drawing process

Wolf,

Tulke,

Brosius

2024

IOP Conf. Ser.: Mater. Sci. Eng.

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Reaching robustness of forming processes is one of the main challenges in manufacturing technologies. Volatile material properties [1] and fluctuations in process parameters often result in insufficient part quality and rising production costs, especially in production chains [2]. As a common solution for this problem, numerical simulations are used to consider scattering of material parameters and define a useable process window with a specified safety margin. A new approach is the use of macro-structured tools. Result shown here indicate, in addition to the general enlargement of the useable process window [3], a high tolerance toward volatile material properties and variations of the blank. The produced parts show consistent quality with a reduction in residual stresses [4]. To examine the robustness in particular, virtual studies for steel alloy DX54 with varying alignment of the blank were performed. The resulting properties, such as the blank draw-in, thinning and springback, were examined in predefined positions on the blank to compare the experiments. The enlarged process window will be analysed and a strategy for a deeper understanding of the forming process will be generated, which will sustain the design of robust tools and processes.

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Section: Process Robustness and Influencing Parametersmentioning

confidence: 99%