Multi-objective optimization of tensile properties of additive/subtractive manufacturing based on genetic algorithm

The multi-objective optimization of the tensile properties of 316L composites was carried out by genetic algorithm. Taking the powder feeding rate, laser power and scanning speed as the investigation factors, taking the tensile strength, yield strength and elongation as evaluation indexes, the regression model of the evaluation index was established by using the least square method, and the multiple objective optimization of the regression model was carried out with the MATLAB genetic algorithm toolbox. The optimum process parameters are obtained: the optimum processing technology matching is the laser power 600 W, the powder feeding rate 7.23 g/min, the scanning speed 600 mm/min. Under this condition, the tensile strength is 763.981 4 MPa, the yield strength is 553.520 4 MPa, and the elongation is 0.701 540.