Prediction of Bending Angle for Laser Forming of Tailor Machined Blanks by Neural Network

Abstract

Tailor-made blanks are sheet metal assemblies with different thicknesses and/or materials and/or surface coatings. A monolithic sheet can be machined to make the required thickness variations that is referred as tailor machined blanks. Due to the thickness variation in tailor machined blanks, laser bending of these blanks is more complicated than monolithic plates. In this article, laser forming of tailor machined blanks is investigated and an artificial neural network (ANN) will be configured to predict the bending angle of laser formed tailor machined blanks. The input parameters of neural network are selected as start point of scan path, laser irradiating method, laser beam diameter, laser output power and number of radiation passes. The results show that a 5×8×1 trained neural network can predict the bending angle with acceptable accuracy. Comparison of the randomly selected tests with experimental results shows 1.1% error in the prediction of bending angle by trained artificial neural network.