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Abstract

Abstract

Residual compressive stress can effectively improve fatigue the life of aerospace thin-walled parts. In this study, residual compressive stress control is taken as the target. Firstly, a surface residual stress prediction model is proposed, which considers both machining parameters and milling force heat. The model of the relationship between milling force, thermal load, and residual stress is established, which quantifies the effects of mechanical and thermal loads on the formation of residual compressive stresses. The results show that the feed rate of each tooth and the cutting-edge radius play an important role in the residual compressive stress of the milling surface. The prediction models of surface residual stress for thermal load, mechanical load, feed per tooth, and radius are established. Secondly, the ratio α of the feed rate per tooth fz to the cutting-edge radius r is quantified. When αxx = 0.42–0.65 and αyy = 0.36–0.7, the surface residual compressive stress in the x and y directions of the workpiece reaches the maximum value. Thus, the ratio of the feed rate per tooth fz to the cutting-edge radius r is optimized to control the mechanical and thermal load quantization. It realizes active control of residual compressive stress on the workpiece surface.

Details

Title
Residual compressive stress prediction determined by cutting-edge radius and feed rate during milling of thin-walled parts
Author
Jiang, Xiaohui 1 ; Cai, Yan 1 ; Liu, Weiqiang 2 ; Guo, Miaoxian 1 ; Zhou, Hong 3 ; Xu, Zhou 3 ; Kong, Xiangjing 1 ; Ju, Pengfei 3 

 University of Shanghai for Science and Technology, School of Mechanical Engineering, Shanghai, China (GRID:grid.267139.8) (ISNI:0000 0000 9188 055X) 
 Jinggangshan University, School of Mechanical and Electrical Engineering, Ji’an, China (GRID:grid.440809.1) (ISNI:0000 0001 0317 5955) 
 Shanghai Aerospace Equipment Manufacturing Company Limited, Shanghai, China (GRID:grid.267139.8) 
Pages
773-788
Publication year
2023
Publication date
Jan 2023
Publisher
Springer Nature B.V.
ISSN
02683768
e-ISSN
14333015
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2761431607
Copyright
© The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.