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

Juan Wei; Yaxin Wei; Mengdi Wei; Simin Ren

doi:doi:10.11648/j.jeee.20231103.12

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

Juan Wei, Yaxin Wei, Mengdi Wei, Simin Ren

Published in Journal of Electrical and Electronic Engineering (Volume 11, Issue 3)

Received: 10 April 2023 Accepted: 17 June 2023 Published: 27 June 2023

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Abstract

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.

Published in	Journal of Electrical and Electronic Engineering (Volume 11, Issue 3)
DOI	10.11648/j.jeee.20231103.12
Page(s)	77-81
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2023. Published by Science Publishing Group

Keywords

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

References

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APA Style

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. https://doi.org/10.11648/j.jeee.20231103.12

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ACS Style

Juan Wei; Yaxin Wei; Mengdi Wei; Simin Ren. Research on Optimization of CNC Milling Process Parameters Based on Carbon Emission. J. Electr. Electron. Eng. 2023, 11(3), 77-81. doi: 10.11648/j.jeee.20231103.12

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AMA Style

Juan Wei, Yaxin Wei, Mengdi Wei, Simin Ren. Research on Optimization of CNC Milling Process Parameters Based on Carbon Emission. J Electr Electron Eng. 2023;11(3):77-81. doi: 10.11648/j.jeee.20231103.12

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@article{10.11648/j.jeee.20231103.12,
  author = {Juan Wei and Yaxin Wei and Mengdi Wei and Simin Ren},
  title = {Research on Optimization of CNC Milling Process Parameters Based on Carbon Emission},
  journal = {Journal of Electrical and Electronic Engineering},
  volume = {11},
  number = {3},
  pages = {77-81},
  doi = {10.11648/j.jeee.20231103.12},
  url = {https://doi.org/10.11648/j.jeee.20231103.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jeee.20231103.12},
  abstract = {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.},
 year = {2023}
}

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TY  - JOUR
T1  - Research on Optimization of CNC Milling Process Parameters Based on Carbon Emission
AU  - Juan Wei
AU  - Yaxin Wei
AU  - Mengdi Wei
AU  - Simin Ren
Y1  - 2023/06/27
PY  - 2023
N1  - https://doi.org/10.11648/j.jeee.20231103.12
DO  - 10.11648/j.jeee.20231103.12
T2  - Journal of Electrical and Electronic Engineering
JF  - Journal of Electrical and Electronic Engineering
JO  - Journal of Electrical and Electronic Engineering
SP  - 77
EP  - 81
PB  - Science Publishing Group
SN  - 2329-1605
UR  - https://doi.org/10.11648/j.jeee.20231103.12
AB  - 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.
VL  - 11
IS  - 3
ER  -

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Author Information

Juan Wei

School of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an, China
Yaxin Wei

School of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an, China
Mengdi Wei

School of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an, China
Simin Ren

School of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an, China

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Plain Text BibTeX RIS

APA Style

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. https://doi.org/10.11648/j.jeee.20231103.12

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ACS Style

Juan Wei; Yaxin Wei; Mengdi Wei; Simin Ren. Research on Optimization of CNC Milling Process Parameters Based on Carbon Emission. J. Electr. Electron. Eng. 2023, 11(3), 77-81. doi: 10.11648/j.jeee.20231103.12

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AMA Style

Juan Wei, Yaxin Wei, Mengdi Wei, Simin Ren. Research on Optimization of CNC Milling Process Parameters Based on Carbon Emission. J Electr Electron Eng. 2023;11(3):77-81. doi: 10.11648/j.jeee.20231103.12

Copy | Download

@article{10.11648/j.jeee.20231103.12,
  author = {Juan Wei and Yaxin Wei and Mengdi Wei and Simin Ren},
  title = {Research on Optimization of CNC Milling Process Parameters Based on Carbon Emission},
  journal = {Journal of Electrical and Electronic Engineering},
  volume = {11},
  number = {3},
  pages = {77-81},
  doi = {10.11648/j.jeee.20231103.12},
  url = {https://doi.org/10.11648/j.jeee.20231103.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jeee.20231103.12},
  abstract = {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.},
 year = {2023}
}

Copy | Download

TY  - JOUR
T1  - Research on Optimization of CNC Milling Process Parameters Based on Carbon Emission
AU  - Juan Wei
AU  - Yaxin Wei
AU  - Mengdi Wei
AU  - Simin Ren
Y1  - 2023/06/27
PY  - 2023
N1  - https://doi.org/10.11648/j.jeee.20231103.12
DO  - 10.11648/j.jeee.20231103.12
T2  - Journal of Electrical and Electronic Engineering
JF  - Journal of Electrical and Electronic Engineering
JO  - Journal of Electrical and Electronic Engineering
SP  - 77
EP  - 81
PB  - Science Publishing Group
SN  - 2329-1605
UR  - https://doi.org/10.11648/j.jeee.20231103.12
AB  - 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.
VL  - 11
IS  - 3
ER  -

Copy | Download