CNC machine tools play an important role in manufacturing and are characterized by high total energy consumption and low energy efficiency. The energy consumption characteristics of the machine tool itself determine the total energy consumption and pollutant emission during its service life. Therefore, it is particularly important to design machine tools with energy consumption as the optimization target to analyze the composition of energy consumption and related characteristics, build a corresponding model based on reliability verification, guide the structural design and optimization according to the model, and ultimately use the evaluation system to evaluate and judge the overall energy consumption. In this paper, from four perspectives—the composition of the energy consumption of machine tools, modeling methods, design and optimization methods, and evaluation methods—with energy consumption optimization as the entry point, we analyze the research on CNC machine tools based on energy consumption around the world. The research results indicate that we should look forward to the role of energy consumption in the design of machine tools.

Aiming at improving the structural performance of the high-precision turning-milling combined machine tool bed, a multi-objective collaborative optimization framework that integrates bionic design principles and the Taguchi method is developed in this study. This framework first extracts the static and dynamic characteristics of the bed structure through finite element simulation. Then, inspired by the honeycomb configuration as a bionic prototype, it innovatively redesigns the internal rib layout. Subsequently, systematic optimization of key dimensional parameters is conducted via Taguchi orthogonal experiments, ultimately establishing a mathematical model with the comprehensive objectives of mass reduction, deformation suppression, and natural frequency enhancement. The results show that the quality of the optimized bed is reduced by 6.7%, the maximum deformation is decreased by 6.15%, and the fourth-order natural frequency is increased by 2.8%. It achieves lightweighting while significantly enhancing the static and dynamic performance of the structure, providing a feasible path for the green design and performance improvement of high-precision machine tools.