Aiming at the problems of high carbon emission efficiency and poor surface quality caused by using unreasonable processing parameters during the working processes of CNC milling ma-chines,an optimization method of CNC milling machine processing parameters oriented to low carbon and high quality was proposed.Initially,carbon emission factors in the milling processes were ana-lyzed,and target functions of carbon emission efficiency,surface roughness,and processing time were defined.Prediction models for carbon emission efficiency and surface roughness for CNC milling ma-chines were subsequently established,utilizing the support vector regression improved by grey wolf optimizer.Then,with spindle speed,feed rate,and cutting width designated as optimization varia-bles,an improved egret swarm optimization algorithm was applied to optimize the cutting parameters.This resulted in obtaining Pareto front solutions for processing parameters that were low in carbon e-missions,high in quality and efficient.Suitable processing parameters were selected using the EW-TOPSIS method.Finally,an experimental platform for monitoring carbon emissions in CNC milling machines was established,and the feasibility and validity of the proposed method were verified by the experimental results.
关键词
低碳高质/改进支持向量回归/改进白鹭算法/熵权-逼近理想解排序法
Key words
low-carbon and high-quality/improved support vector regression/improved egret swarm optimization algorithm/entropy weight-technique for order preference by similarity to ideal so-lution(EW-TOPSIS)
维普
万方数据