Computational Mechanics

, Volume 47, Issue 5, pp 573–590

Forming forces in single point incremental forming: prediction by finite element simulations, validation and sensitivity


    • ArGEnCoUniversité de Liège
    • Samtech S.A.
  • C. Bouffioux
    • ArGEnCoUniversité de Liège
  • P. Eyckens
    • MTMKatholieke Universiteit Leuven
  • H. Sol
    • MEMCVrije Universiteit Brussel
  • J. R. Duflou
    • PMAKatholieke Universiteit Leuven
  • P. Van Houtte
    • MTMKatholieke Universiteit Leuven
  • A. Van Bael
    • MTMKatholieke Universiteit Leuven
    • KHLim (Limburg Catholic University College)
  • L. Duchêne
    • ArGEnCoUniversité de Liège
  • A. M. Habraken
    • ArGEnCoUniversité de Liège
Original Paper

DOI: 10.1007/s00466-010-0563-4

Cite this article as:
Henrard, C., Bouffioux, C., Eyckens, P. et al. Comput Mech (2011) 47: 573. doi:10.1007/s00466-010-0563-4


The aim of this article is to study the accuracy of finite element simulations in predicting the tool force occurring during the single point incremental forming (SPIF) process. The forming of two cones in soft aluminum was studied with two finite element (FE) codes and several constitutive laws (an elastic–plastic law coupled with various hardening models). The parameters of these laws were identified using several combinations of a tensile test, shear tests, and an inverse modeling approach taking into account a test similar to the incremental forming process. Comparisons between measured and predicted force values are performed. This article shows that three factors have an influence on force prediction: the type of finite element, the constitutive law and the identification procedure for the material parameters. In addition, it confirms that a detailed description of the behavior occurring across the thickness of the metal sheet is crucial for an accurate force prediction by FE simulations, even though a simple analytical formula could provide an otherwise acceptable answer.


Single point incremental formingFinite element modelingForce predictionMaterial parameters identificationInverse modeling

Copyright information

© Springer-Verlag 2010