Multi‑objective optimization of stainless steel 304 tube laser forming process using GA

Abstract

Laser forming is one of the most recent forming processes developed which uses a laser beam to induce a deliberate thermal stress on a workpiece to form a sheet metal. Accordingly, bending tubes using laser beam have attracted the attention of many engineers. In this paper, we studied the effects of various laser beam parameters on the tube bending process. To investigate the effects of all the parameters, we performed a large number of analyses and generated applicable tube laser bending data. We utilized Taguchi design of experiment method to manage the finite element simulation of the laser forming process. Subsequently, to have an easier, but more flexible and more complete laser forming data bank, we employed artificial neural networks to predict the required tube bending parameters for the proposed forming criteria. Finally, we used genetic algorithm programming to solve the multi-objective optimization with respect to the laser forming parameters. The objectives include maximum bending angle, minimum ovality, minimum thickening, and minimum forming energy consumption. The results from this study indicate that we can use applied data tables to find the optimum tube laser forming parameters. The outcome of the numerical experiments is consistent with the existing literature on the laser forming process.