Mechanism of material removal in orthogonal cutting of cortical bone

Author(s):  
Wei Bai ◽  
Liming Shu ◽  
Ronglei Sun ◽  
Jianfeng Xu ◽  
Vadim V. Silberschmidt ◽  
...  
2013 ◽  
Vol 17 (4) ◽  
pp. 637-649 ◽  
Author(s):  
Jianbo Sui ◽  
Naohiko Sugita ◽  
Kentaro Ishii ◽  
Kanako Harada ◽  
Mamoru Mitsuishi

Author(s):  
Wei Bai ◽  
Liming Shu ◽  
Ronglei Sun ◽  
Jianfeng Xu ◽  
Vadim V. Silberschmidt ◽  
...  

2011 ◽  
Vol 223 ◽  
pp. 101-110
Author(s):  
Ferdinando Salvatore ◽  
Tarek Mabrouki ◽  
Hédi Hamdi

The present work deals with the presentation of analytical methodology allowing the modeling of chip formation. For that a “decomposition approach”, based on assuming that the material removal is the summation of two contributions, ploughing and pure cut was adopted. Moreover, this analytical model was calibrated by a finite element model and experimental data in terms of temperature and applied forces evolutions. The global aim is to propose to the industrial community, an efficient rapid-execution analytical model concerning the material removal in the case of an orthogonal cutting process.


Author(s):  
Ilige S. Hage ◽  
Ramsey F. Hamade

The finite element method at the micro scale (mFEM) has been gaining in popularity to simulate biomechanical effects. In this paper, a 3D mFEM model is developed to simulate sawing of cortical bone under 2D orthogonal cutting conditions. The aim of the research was to develop a predictive model of the sawing forces and to report them as a function of depth of cut. To obtain the micro geometric input, a heterogeneous anisotropic model was created from several images taken via an optical microscope of the cortex of adult mid-diaphysal bovine femur. In order to identify the various regions representing the micro-architecture of cortical bone, such as osteons, Haversian canals, lamellae and lacunae, MATLAB was utilized for intelligent image processing based on pulsed coupled neural networks. After each micro-phase in the image was assigned the proper mechanical properties, these material-tagged micro-features were imported into the finite element method (FEM) solver. Results from the simulation were correlated to cutting force data that was determined experimentally. Experiments were conducted with individual stainless steel saw blade teeth that were removed from a typical surgical saw blade. The teeth were 0.64 mm thick, with a rake and clearance angle of −10 and 60 degrees, respectively. Representative of clinical conditions for power bone sawing, depths of cut per tooth between 2.5 micrometer and 10 micrometer were investigated. The simulated cutting forces from the mFEM model compared favorably to the experimental data.


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