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Research on Optimization of CNC Milling Process Parameters Based on Carbon Emission

In order to achieve the low carbon and efficient working effect of CNC machine tools, this paper takes the 2243 VMC machining centre as the research object to study the problem between carbon emission and time, cost and process parameters in the machining process of machining centre machine tools, and establish the optimization model of CNC milling process parameters based on carbon emission. Carbon emissions, machining cost and machining time are taken as the optimisation objectives, tool life, roughness and machine power are taken as constraints, and spindle speed, feed per tooth, cutting width and depth of cut are taken as optimisation variables. The model is solved using a particle swarm algorithm (PSO) to produce a Pareto solution set for multi-objective optimisation. Finally, the optimisation results were compared with the calculated results for the empirical parameters to verify the feasibility of the model. The results show that the calculated results for the optimised parameters provide a 19.53% reduction in carbon emissions, a 12.96% reduction in processing costs and a 13.72% reduction in processing time after optimisation by the algorithm compared to the calculated results for the empirical parameters, indicating that the algorithm provides a better optimisation than the empirical parameters.

Carbon Emissions, CNC Milling, Process Parameter, Adaptive Grid Particle Swarm Algorithm

Juan Wei, Yaxin Wei, Mengdi Wei, Simin Ren. (2023). Research on Optimization of CNC Milling Process Parameters Based on Carbon Emission. Journal of Electrical and Electronic Engineering, 11(3), 77-81.

Copyright © 2023 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License ( which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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