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Abstract
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Focusing on upcoming challenges ln lightweight design, such as lncreasing emission targets or novel multi-material connections, versatile applicable and environmentally friendly production technologies are becoming more and more relevant. ln this context, the mechanical joining technology clinching offers a fast and energy-efficient procedure for assembling sheet metals. Thus, it is a proper alternative to established joining methods, such as spot welding. However, since achieving satisfying clinch joint characteristics mainly relies on the precise generation of geometrical joint characteristics (e.g., interlock and neck thickness), lt is crucial to gain a deep understanding of the joining process. While the definition of optimal tool dimensions has been lnvestigated in several contributions, the focus on varying material and process conditions and their lmpact on resulting joint connections was only slightly covered; although it has a significant lmpact on the costs and quality of clinch points, especially in the case of safety-relevant components, such as in car body designs. ln order to close this gap and support the design process of mechanical joining assemblies, this contribution proposes an efficient meta-model-based variation simulation procedure enabling the quantification of the effect of uncertain parameters on the resulting joint characteristics, taking different tool designs into account. This fosters the understanding of the clinching process in an uncertain environment and the proper tool and tolerance design for a reliable virtual joining point design without extensive lterations and physical tests.
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