Multi-Objective Optimization of Laser Cladding Parameters Based on RSM and NSGA-II Algorithm

In order to obtain the best technological parameters of laser cladding FeCrNiSi powder on Q690, an optimization method of laser cladding parameters based on response surface method (RSM) and second generation non-dominated sorting genetic algorithm (NSGA-II) algorithm is proposed. By designing the Box-Benhnken experiment scheme in response surface method, the proxy model between the input variables (laser power, scanning speed, and powder feeding rate) and the response values (dilution, heat affected zone depth, and microhardness) is established, and the process parameters were optimized by NSGA-II. The results show that the optimal parameters are obtained when the laser power is 1950 W, the scanning speed is 19 mm/s, and the powder feeding rate is 2.4 r/min. Under these conditions, the dilution rate of the cladding specimen decreases by 22.4%, the depth of the heat affected zone decreases by 17.9%, and the microhardness increases by 4.2%.