An integrated FEM-ANN model for laser bending process with inverse estimation of absorptivity

Abstract

Absorption of laser energy into the worksheet surface during laser bending process is an important and critical factor for accurate computation of the bend angle. This paper presents an integrated FEM-ANN approach to compute accurate value of bend angle during laser bending process.

Initially, a finite element method (FEM) based three-dimensional nonlinear transient thermo-mechanical numerical model is developed using ABAQUS package. Using FEM model and data obtained in actual experiments, the proper values of absorptivity for various sets of process conditions are computed by inverse analysis technique. Based on the proper values of absorptivity, an artificial neural network (ANN) model is developed for accurate and quick prediction of absorptivity for given input process conditions. The predicted absorptivity is then employed in the FEM model for accurate computation of bend angle.

The performance of the integrated approach is verified by conducting experiments.

The verification results showed that the proposed approach is able to compute the bend angle with a very good accuracy (average prediction error of 4.14?%). The proposed approach can also be suitable for the numerical simulations of other laser based manufacturing processes.