Neuro-Fuzzy Modeling and Optimization of the Parameters of Laser Forming of Composite Laminated Sheets

In this paper, laser forming of two-layered laminated sheets (SUS304L stainless steel/C11000 copper) and three-layered laminated sheets (SUS430 stainless steel/C11000 copper/SUS430 stainless steel) was investigated. These sheets have high thermal conductivity and resistance to chemical attack due to their combined properties of copper and stainless steel. The effects of independent parameters such as laser power, beam diameter, scan speed and number of passes on the bending angle are evaluated in the laser forming of these two types of composites. During several experiments, 147 output data were obtained for the two-layered sheet and 168 data for the three- layered sheet. These experimental data have been applied to modeling using the Adaptive Neuro-Fuzzy Inference System (ANFIS) toolbox in Matlab software. Modeling is performed with all membership functions to find the best one for input variables. After considering all the models, the Gaussian membership function is selected for the optimization model. Finally, using multi-objective genetic algorithm, the optimal values of input parameters for different bending angles were obtained. A graphical user interface (GUI) is designed in Matlab for both modeling and optimization steps.