A high-fidelity simulation of double-sided incremental forming: Improving the accuracy by incorporating the effects of machine compliance
Newell Moser, Dohyun Leem, Kornel Ehmann, Jian Cao
Double-Sided Incremental Forming (DSIF) is a technology for the rapid, flexible manufacturing of sheet metal parts. DSIF is highly nonlinear, requiring the use of complex finite element (FE) models to optimize and control the process in order to meet geometric accuracy and sheet thinning design criteria. Current FE models do not properly take into account the effects of machine compliance, which reduces their accuracy and hinders their use for optimization and control. The aim of this work is to create a greatly improved FE model of DSIF by taking a novel approach of modeling the aggregate effects of machine and tool compliance. The accuracy of the new model was extensively validated using the local geometry, thickness distribution, principal strains, and forming forces from a funnel experiment. The validated model was used to accurately predict the spatial distribution and time-histories of the equivalent plastic strain, von Mises equivalent stress, stress triaxiality, and Lode angle parameter across and along the sheet metal. The stress state was found to rapidly change through the sheet thickness, from highly compressive between the tools and the sheet, to a mixture of generalized shear and plane strain elsewhere. Moreover, the compressive regions between the two DSIF tools created a constrained deformation zone, which likely aids in prolonging the onset of excessive thinning. This improved FE model can now be used to quantitatively characterize the nonlinear local deformation mechanisms inherent to the DSIF process, thereby providing a solid foundation for future advances in process control.
, Leem, D.
, Ehmann, K.
and Cao, J.
A high-fidelity simulation of double-sided incremental forming: Improving the accuracy by incorporating the effects of machine compliance, Journal of Materials Processing Technology, [online], https://doi.org/10.1016/j.jmatprotec.2021.117152, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=930951
(Accessed September 21, 2021)