The existing nine-axis five-linkage CNC slow-feed grinder has many motion links, which may cause many problems during the working process such as insufficient rigidity, deformation of castings like lathe bed and in? accurate machining accuracy. In this work, the maximum deformation of the grinder and the first-order natural fre? quency under the modal analysis are taken as the main optimization goal and the overall quality as the secondary goal. ANSYS Workbench is used to analyze and optimize the grinder, and the original structure is then improved by the sensitivity analysis, finally obtaining the new design scheme for each key part. When the quality of the whole grinder is improved to a certain extent, the maximum static deformation and first-order natural frequency of the grinder is greatly improved. Besides, the extreme learning machine network model (Extreme Learning Machine) opti? mized by genetic algorithm is combined with genetic algorithm to optimize some main parameters of the improved structure of the nine-axis five-linkage grinder. Firstly, the whole machine mass, maximum static deformation and first-order natural frequency of grinding machine are transformed into comprehensive target grey correlation degree via grey correlation analysis. Then, the network model of the extreme learning machine (Genetic Algorithm-Extreme Learning Machine) optimized by the genetic algorithm is used to fit the nonlinear coupling relationship between the main parameters of the grinder and the gray correlation degree of the comprehensive target. Finally, GA′s powerful optimization ability is used to find the optimal process parameters in the trained GA-ELM network model. After opti? mization, the overall quality of the nine-axis five-linkage grinding machine, the reduction of the maximum static de? formation and the first-order natural frequency are optimized when compared with the improved scheme. This method provides a certain theoretical support and reference value for the subsequent technicians to optimize the structure and parameters of the grinder.