The springback of a sheet metal part is the change of its shape after removing a forming tool. An accurate prediction of springback is very difficult because sheet metal undergoes a complicated deformation process during the forming process. These are the following types of springback when considering the geometry of the product and the forming regime: angular change, sidewall curl, and twist. The latter is the key issue of this paper. A new definition of twist springback is proposed having been tested on a referenced sheet metal part. An experimental device for twist springback testing has been designed and the effect of blank rolling direction on the twist was investigated for dual-phase (DP) sheet steel. Finite element method (FEM) results of twisting behaviour using AutoForm software for different material models were compared with the experimental and the correlation evaluation was performed.

New demands in the automotive industry have led to an increase in the use of Advanced High-Strength sheet metal materials. However, higher values of strength are usually achieved at the expense of reduced formability and increased sensitivity of the springback. Today, springback is one of the more important factors that influence the quality of sheet metal forming products. During the forming process, sheet metal undergoes a complicated deformation history, which is why the accurate prediction of the springback level can be very difficult. Today, a good compromise between the finite element method (FEM) simulation and the real stamping process can be achieved, but there is still limited reliability of the FEM springback prediction. In this paper, the machine learning (ML) approach was used to update the FEM for springback modelling. Combined models are tuned to better reflect the measured experimental data.

No abstract

No abstract

No abstract