Simulation and optimization of continuous laser transmission welding between PET and titanium through FEM, RSM, GA and experiments

Abstract

An intelligent method for simulation and optimization of continuous laser transmission welding (LTW) and validated with experiments (EX) is investigated in this paper. Thermal model using finite element method (FEM) has been combined with response surface methodology (RSM) and genetic algorithm (GA) techniques to improve veracity of the model prediction with less time spending on the experiments. A three-dimensional axi-symmetric thermal model has been developed to simulate the continuous LTW process with a moving Super-Gaussian heat source. The model is confirmed with a series of experiments. A statistical technique RSM based mathematical model is proposed to establish relations between input variables (power, welding speed, stand-off-distance) and output variables (maximum temperature at the weld interface-Tmax, maximum temperature at the top surface of the transparent PET-Ttop, weld width-WW, and weld depth in the transparent PET-DT). The RSM models are trained and tested by using the data from the numerical (FEM) models. It turns out that the models are proposed to accurately predict the output variables with the corresponding input variables. Finally, the desirability function (DF) integrated with the developed non-dominating sorting genetic algorithm-II (NSGA-II) is used to find out the optimal variables that enhance the quality and efficiency of the welding. Experiments using the optimum parameters are carried out to verify the FEM and RSM models. Results show that the proposed integrated (FEM–RSM–GA–EX) approach performed very well in optimum performance of the continuous LTW process. In addition, this approach also presents the feasibility of the use of the FE simulation to guide the experiments.