Prediction of Milling Deformation for Frame-Type Thin-Walled Parts Considering Workblank Initial Residual Stress and Milling Force

Machining deformation is a key bottleneck that restricts the improvement of manufacturing accuracy of aviation thin-walled structural components, such as frames, beams, and wall panels. The initial residual stress of the workblank and the cutting load are the direct factors leading to machining deformation. Based on the initial residual stress measurement and the milling force test, a finite element prediction model for milling deformation of frame-type thin-walled parts with integrated consideration of initial residual stress and the milling force was established and experimentally verified in this study. Then, the influence of milling process factors, such as the frame processing sequence (FPS), the cutting path, and the single frame one-time removal depth (SFORD), on the milling deformation of frame-type parts was studied. The results showed that the established prediction model had high reliability and the prediction accuracy was improved by 6.7% compared with that when only considering the initial residual stress. A smaller machining deformation can be achieved through the use of the FPS to prioritize the width, direction, and symmetrical milling, as well as the inner loop cutting path, and the smaller SFORD. This study can provide a technical reference for the prediction and control of milling deformation of aviation thin-walled structural parts, especially frame-type thin-walled parts.

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Publication Details

Journal
Journal of Manufacturing and Materials Processing
Published
2025-04-29
DOI
https://doi.org/10.3390/jmmp9050146
Citations
4
Primary Topic
Advanced machining processes and optimization
Type
article
Field-Weighted Citation Impact
2.85

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article

Prediction of Milling Deformation for Frame-Type Thin-Walled Parts Considering Workblank Initial Residual Stress and Milling Force

Leyang Li, Fei Gao, Lijie Ma, Faping Zhang et al.
4 citations
Journal of Manufacturing and Materials Processing
Advanced machining processes and optimization
2.85
article

Prediction of Milling Deformation for Frame-Type Thin-Walled Parts Considering Workblank Initial Residual Stress and Milling Force

Leyang Li, Fei Gao, Lijie Ma, Faping Zhang, Yu Zhang, Hongwen Liu, Junjin Ma, Shijie Ba
article en
4 citations

Abstract

Machining deformation is a key bottleneck that restricts the improvement of manufacturing accuracy of aviation thin-walled structural components, such as frames, beams, and wall panels. The initial residual stress of the workblank and the cutting load are the direct factors leading to machining deformation. Based on the initial residual stress measurement and the milling force test, a finite element prediction model for milling deformation of frame-type thin-walled parts with integrated consideration of initial residual stress and the milling force was established and experimentally verified in this study. Then, the influence of milling process factors, such as the frame processing sequence (FPS), the cutting path, and the single frame one-time removal depth (SFORD), on the milling deformation of frame-type parts was studied. The results showed that the established prediction model had high reliability and the prediction accuracy was improved by 6.7% compared with that when only considering the initial residual stress. A smaller machining deformation can be achieved through the use of the FPS to prioritize the width, direction, and symmetrical milling, as well as the inner loop cutting path, and the smaller SFORD. This study can provide a technical reference for the prediction and control of milling deformation of aviation thin-walled structural parts, especially frame-type thin-walled parts.

Journal of Manufacturing and Materials ProcessingVol. 9(5)
Beijing Institute of Technology (CN), Henan Institute of Technology (CN), Henan Institute of Science and Technology (CN), Henan Polytechnic University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 10%
Advanced machining processes and optimization
2.85
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