Selection of laser bending process parameters for maximal deformation angle through neural network and teachinglearning-based optimization algorithm
The present study focused on selecting optimal factors combination that causes maximum bending angle in laser bending of AA6061-T6. For this purpose a L\(_{25}\) Taguchi orthogonal design (four factors-five levels) is used to design experiments. Here, the process main factors are laser power, spot diameter, pulse duration and scanning speed and the main response was bending angle. To correlate relationship between process factors and bending angle, a radial basis function neural network (RBFNN) was utilized. Then the developed RBFNN model was used as an objective function for maximizing deformation through teachinglearning-based optimization algorithm. Results indicated that the laser power of 3.6kW, spot diameter of 2 mm, pulse duration of 0.9 ms and scanning speed of 2 mm/s lead to maximal bending angle about 28.7\(^\circ \). Hereafter the optimal results have been verified by confirmatory experiments.
laser bending teachinglearning-based optimization algorithm l\(_{25}\) taguchi design radial basis network