Processing parameters (spindle speed

feed per tooth

radial depth

axial depth) have an important role in the process. The purpose in this study is to reduce energy consumption

improve energy utilization efficiency

reduce milling heat and improve processing quality and tool life. The research process optimizes the processing parameters from both energy consumption and milling heat

with spindle speed

feed per tooth

radial and axial cutting depth as optimization variables

the value range of machine tool equipment performance and processing parameters are taken as constraints

optimizing the processing parameters for energy saving and low milling heat

the model is solved with the non-dominant ranked genetic algorithm (NSGA-Ⅱ) with the elite strategy. Finding the optimal solution to the Pareto solution set with the hierarchical analysis

the optimal results were verified with the orthogonal experimental response surface method

finally

the optimal machining parameters and the empirical machining parameters are used for experimental comparative analysis

the results show that the optimal processing parameters are very effective in energy saving and low milling heat.