The application of abductive networks and FEM to predict the limiting drawing ratio in sheet metal forming processes

Abstract

The deep drawing process, one of the sheet metal forming methods, is very useful in the industrial field because of its efficiency. The limiting drawing ratio (LDR) is affected by many material and process parameters, such as the strain-hardening exponent, the plastic strain ratio, friction and lubrication, the blank holder force, the presence of drawbeads, the profile radius of the die and punch, etc. In order to verify the finite element method (FEM) simulation results of the LDR, the experimental data are compared with the results of the current simulation. The influences of the process parameters such as the blank holder force, the profile radius of the die, the clearance between the punch and the die, and the friction coefficient on the LDR are also examined. The abductive network was then applied to synthesize the data sets obtained from the numerical simulation. The predicted results of the LDR from the prediction model are in good agreement with the results obtained from the FEM simulation. By employing the predictive model, it can provide valuable references to the prediction of the LDR under a suitable range of process parameters.