3.8 Proceedings Paper

Increasing flexibility of self-pierce riveting using numerical and statistical methods

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.promfg.2019.02.137

关键词

Self-pierce riveting; Sensitivity analyses; Tool optimization

资金

  1. Federal Ministry of Economic Affairs and Energy
  2. AiF [AiF 19190 BR]

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Self-pierce riveting with semi-tubular rivets (SPR-ST) is currently the most important joining technology for modern mixed-material car body constructions. In these body designs a multitude of material and thickness combinations occurs and for many of these combinations individual parameters of the SPR-ST process like the rivet length and die geometry have to be determined. This paper shows an approach to increase the flexibility of the SPR-ST process by the determination of the process parameters using FEM simulations in combination with statistical methods. In the described investigations one parameter set is derived for the SPR-ST process from seven different material combinations with steel and aluminum materials. For each material combination a simulation model is validated by the comparison of the joint geometry and force-stroke diagram from the experimental reference joints with the results from the process simulation. On the basis of the validated simulation models, numerical sensitivity analyses are carried out for each material combination to investigate the correlations between the process parameters die geometry and rivet length with important quality characteristics of the joint like interlock, minimal thickness of the die-sided sheet and joining force. With the knowledge of these studies computed process optimizations are carried out, in order to define one die geometry to join all seven material combinations in good quality, so a tool changing is no longer required. The reduction from seven to only one optimized SPR-ST tool saves costs as well as processing time and production space. (C) 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Selection and peer-review under responsibility of the organizing committee of SHEMET 2019.

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