A Stress-Sensitivity-Based Process Optimization Method for Machining Thin-Walled Parts

Thin-walled partition frame parts are key load-bearing components in aerospace structures. Machining deformation directly affects assembly accuracy and service reliability. During milling, the release of residual stress caused by material removal is one of the main factors leading to deformation of thin-walled parts. To address this problem, aluminum alloy thin-walled partition frame parts are taken as the research object. A machining accuracy control method based on stress-sensitive region analysis is proposed. Key machining accuracy is used as the constraint condition. The concepts of stress-sensitive regions and sensitive directions are introduced. A coupled analysis model of residual stress and machining deformation is established. Residual stress is applied to element meshes in a finite element analysis platform and released under a free state. The influence of residual stress in different regions on part deformation is qualitatively identified. The dominant deformation directions are also determined. Based on these results, the milling tool path is specifically optimized. Strategies are adopted to avoid highly stress-sensitive regions or to control residual stress release by region. Overall machining deformation is effectively reduced. Experimental results show that the optimized tool path significantly suppresses part deformation compared with the conventional tool path. The flatness of the bottom surface is improved by up to 25.33%. The proposed method provides a feasible approach for machining process optimization of aerospace thin-walled parts with high precision.

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Publication Details

Journal
Lubricants
Published
2026-02-26
DOI
https://doi.org/10.3390/lubricants14030101
Primary Topic
Advanced machining processes and optimization
Type
article
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article

A Stress-Sensitivity-Based Process Optimization Method for Machining Thin-Walled Parts

Aimin Wang, Qibo Li, Haili Jia, Wu Xiong et al.
Lubricants
Advanced machining processes and optimization
article

A Stress-Sensitivity-Based Process Optimization Method for Machining Thin-Walled Parts

Aimin Wang, Qibo Li, Haili Jia, Wu Xiong, Long Wu
article en

Abstract

Thin-walled partition frame parts are key load-bearing components in aerospace structures. Machining deformation directly affects assembly accuracy and service reliability. During milling, the release of residual stress caused by material removal is one of the main factors leading to deformation of thin-walled parts. To address this problem, aluminum alloy thin-walled partition frame parts are taken as the research object. A machining accuracy control method based on stress-sensitive region analysis is proposed. Key machining accuracy is used as the constraint condition. The concepts of stress-sensitive regions and sensitive directions are introduced. A coupled analysis model of residual stress and machining deformation is established. Residual stress is applied to element meshes in a finite element analysis platform and released under a free state. The influence of residual stress in different regions on part deformation is qualitatively identified. The dominant deformation directions are also determined. Based on these results, the milling tool path is specifically optimized. Strategies are adopted to avoid highly stress-sensitive regions or to control residual stress release by region. Overall machining deformation is effectively reduced. Experimental results show that the optimized tool path significantly suppresses part deformation compared with the conventional tool path. The flatness of the bottom surface is improved by up to 25.33%. The proposed method provides a feasible approach for machining process optimization of aerospace thin-walled parts with high precision.

LubricantsVol. 14(3)
Beijing Institute of Technology (CN), Tianjin University of Technology and Education (CN), Shandong Jianzhu University (CN)
Openalex Percentile: Top 43%
Advanced machining processes and optimization
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A Stress-Sensitivity-Based Process Optimization Method for Machining Thin-Walled Parts — Aimin Wang, Qibo Li, et al. · Lubricants (2026) | TGRS Research Map | TGRS