Face milling commonly generates surface quality of roughness or variation, especially severe for the milling of large-scale components with complex surface geometry such as cylinder block, engine head, and valve body. Thus surface variation serves as an important indicator both for machining parameter selection and components’ service performance. Conversely the optimization of machining process is a vital objective to improve the surface quality and its service life of machined components. Many researchers have dedicated to the prediction of machined surface variation generated by face milling using numerical or experimental methods. However, the numerical methods based on finite element analysis (FEA) are good at predicting local deformation of workpiece under instantaneous milling force, particularly applied for online compensation in face milling. Whereas experimental methods can only be used to estimate whole surface variation through reverse correlation analysis of measured data and processing variables. Therefore, an efficient and comprehensive numerical model is highly desired for the prediction of surface variation of entire surface. This study proposes a coupled numerical simulation method, updating FE model literarily based on the integration of data from ABAQUS and MATLAB, to predict surface variation induced by the face milling of large-scale components with complex surfaces. Using the coupled model, the 3D variation of large-scale surface can be successfully simulated by considering face milling process including dynamic milling force, spiral curve of milling trajectory, and intermittently rotating contact characteristics. Surface variation is finally represented with point cloud from totally iterative FE analysis and verified by face milling experiment. Result shows that the new prediction method can simulate surface variation of complex components. Based on the verified model, a set of numerical analyses are conducted to evaluate the effects of local stiffness non-homogenization and milling force variation on machined surface variation. It demonstrates that surface variation with surface peaks and concaves is strongly correlated with local stiffness non-homogenization especially in feed direction. Thus the coupled prediction method provides a theoretical and efficient way to study surface variation induced by face milling of large-scale complex components.
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ASME 2018 13th International Manufacturing Science and Engineering Conference
June 18–22, 2018
College Station, Texas, USA
Conference Sponsors:
- Manufacturing Engineering Division
ISBN:
978-0-7918-5138-8
PROCEEDINGS PAPER
Coupled Predicting Surface Variation by Face Milling of Engine Block/Head
Shun Liu,
Shun Liu
Shanghai Jiao Tong University, Shanghai, China
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Sun Jin,
Sun Jin
Shanghai Jiao Tong University, Shanghai, China
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Xueping Zhang,
Xueping Zhang
Shanghai Jiao Tong University, Shanghai, China
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Changhui Liu,
Changhui Liu
Shanghai Jiao Tong University, Shanghai, China
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Fuyong Yang,
Fuyong Yang
Shanghai Jiao Tong University, Shanghai, China
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Jiamin Chen
Jiamin Chen
Shanghai Jiao Tong University, Shanghai, China
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Shun Liu
Shanghai Jiao Tong University, Shanghai, China
Sun Jin
Shanghai Jiao Tong University, Shanghai, China
Xueping Zhang
Shanghai Jiao Tong University, Shanghai, China
Changhui Liu
Shanghai Jiao Tong University, Shanghai, China
Fuyong Yang
Shanghai Jiao Tong University, Shanghai, China
Jiamin Chen
Shanghai Jiao Tong University, Shanghai, China
Paper No:
MSEC2018-6327, V004T03A020; 11 pages
Published Online:
September 24, 2018
Citation
Liu, S, Jin, S, Zhang, X, Liu, C, Yang, F, & Chen, J. "Coupled Predicting Surface Variation by Face Milling of Engine Block/Head." Proceedings of the ASME 2018 13th International Manufacturing Science and Engineering Conference. Volume 4: Processes. College Station, Texas, USA. June 18–22, 2018. V004T03A020. ASME. https://doi.org/10.1115/MSEC2018-6327
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