The purpose of this project is to improve the optimization design of complex mechanical structure based on the combination of response surface model and multi-objective genetic algorithm (MOGA). First of all, we built the finite element model (FEM) for the printed electronics inkjet printer through experimental modal analysis (EMA) and finite element analysis (FEA). The analysis of the static and dynamic characteristics of the FEM confirms the weak points of the structure and its actual performance. Next, using central composite design (CCD) method, it selects sample points in the design space and carries out numerical simulation and establishes the initial second order response surface model with eight design variables to further determine the inkjet printer’s first order natural frequency, weight and maximum deformation of the inkjet head. Finally, it carries out an approximation optimization of response surface model using MOGA to obtain the Pareto optimal solution set. Our simulation results determine that the optimal solution can increase the first order natural frequency of the inkjet printer by 36.3 % to effectively avoid the resonance region caused by the servo motor excitation. The maximum deformation of inkjet head decreases by 33 % and the weight of the inkjet printer can be reduced by 19.5 %. We believe that optimization can improve the performance of the inkjet printer and reduce its weight at the same time. The method proposed in this study is suitable for multi-objective optimization of complex structures similar to the printed electronics inkjet printer
