Optimization of milling parameters considering high efficiency and low carbon based on gravity search algorithm

Abstract

According to the characteristics of NC milling, an approach for optimization of milling parameters considering high efficiency and low carbon based on gravity search algorithm is proposed. Taking the carbon emission and processing time as the objectives, the cutting rate, feed per tooth, and cutting width as the optimization variables. A multi-objective optimization model of NC milling parameters is established. An non-dominated sorting gravity search algorithm (NSGSA) is used to solve the multi-objective model, and the position update backoff operation is introduced. Finally, taking NC machining process as an example, the multi-objective optimization results and the single objective optimization results are compared respectively, the actual data show that when the optimization objective is high efficiency and low carbon, the processing time and carbon emissions are 173 and 192 respectively. The comparison results show that the combination of processing parameters obtained by multi-objective optimization is the best, the optimal parameter combination obtained by NSGSA algorithm is verified by grey correlation analysis, and the grey correlation degree of the optimal solution set is 0.81, which is the largest in all solution sets. This approach can help the decision-makers flexibly select the corresponding milling parameters, and provide decision-makers with flexible selection decisions suitable for various scenarios.