Optimization of Fine Milling Process Parameters for Small Impeller

Addressing the issues of surface machining quality and residual stress in small impellers, the outward opening integral small impeller was selected as the key research object, and the main evaluation indicators of the surface quality of the experiment were set as the surface roughness and residual stress. The finite element simulation technology was used to analyze how the process parameters can affect the residual stress and outer surface roughness of the small impeller. After obtaining the results, the genetic algorithm was used to optimize it to obtain the optimal combination of process parameters. The surface roughness is reduced by 34.2%, and the residual stress is reduced by 28.6%, and at the same time, proved the feasibility of the optimization of the process parameters. The numerical control machining test of the small impeller was carried out to verify the feasibility and accuracy of the process parameter optimization.

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Publication Details

Journal
Processes
Published
2025-10-27
DOI
https://doi.org/10.3390/pr13113449
Primary Topic
Advanced machining processes and optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

Optimization of Fine Milling Process Parameters for Small Impeller

Leijie Fu, Yueqi Chen, Xiaotong Gao, Yachen Zhang et al.
Processes
Advanced machining processes and optimization
article

Optimization of Fine Milling Process Parameters for Small Impeller

Leijie Fu, Yueqi Chen, Xiaotong Gao, Yachen Zhang, Li Zhou, Hui Yao, Hu Qiao
article en

Abstract

Addressing the issues of surface machining quality and residual stress in small impellers, the outward opening integral small impeller was selected as the key research object, and the main evaluation indicators of the surface quality of the experiment were set as the surface roughness and residual stress. The finite element simulation technology was used to analyze how the process parameters can affect the residual stress and outer surface roughness of the small impeller. After obtaining the results, the genetic algorithm was used to optimize it to obtain the optimal combination of process parameters. The surface roughness is reduced by 34.2%, and the residual stress is reduced by 28.6%, and at the same time, proved the feasibility of the optimization of the process parameters. The numerical control machining test of the small impeller was carried out to verify the feasibility and accuracy of the process parameter optimization.

ProcessesVol. 13(11)
Xi'an Technological University (CN), Guangxi Research Institute of Chemical Industry (CN)
Xi'an Municipal Bureau of Science and Technology
Openalex Percentile: Top 68%
Advanced machining processes and optimization
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