Multi-scale friction modeling for sheet metal forming

Finite element (FE) formability analyses are everyday practice in the metal-forming industry to reduce costs and lead time of new metal products. Although the predictive capabilities of FE software codes have improved significantly over the years, unfortunately, the experimental trial-and-error process can still not be entirely replaced by virtual design. The simplistic handling of friction in FE software is one of the main reasons for this. In this thesis, friction mechanisms in metal forming are addressed and a physical based friction model is proposed to improve the description of friction in metal forming processes. As an input, the model requires the properties of the metal-lubricant combination used and the surface characteristics of the tooling and the workpiece material. As an output, the friction conditions are predicted in both the boundary and mixed lubrication regime, including the effect of surface changes due to normal loading, sliding and straining the underlying bulk material. Adhesion and ploughing effects are accounted for to characterize friction conditions on the micro scale. To account for lubrication effects, special hydrodynamic contact elements have been developed. The boundary friction model and the hydrodynamic friction model have been coupled to describe friction in the mixed lubrication regime. The friction model has been implemented in an FE software code to model boundary and mixed lubrication friction in metal forming simulations, while minimally influencing the computation time. FE simulations have been carried out using the advanced friction model for 2 sheet metal forming processes, i.e. the forming of a top hat section and a cross-die product. In addition, experimental validation of the numerical results was performed. The computed local friction coefficients show a dependency on the punch stroke, punch speed and location in the product. A comparison between numerically and experimentally obtained results demonstrated a good correspondence. Also for varying process settings, the advanced friction model enables the accurate prediction of experimental results.