Prediction Modeling and Sensitivity Analysis of Robot Bone Milling Temperature Operated by a Doctor

Bone milling is a common method in robot orthopedic surgery. However, excessive milling temperature will cause thermal necrosis of bone cells and tissues. It is necessary to carry out further research and analysis on the robot bone milling process considering the lamina milling skills of spinal surgeons and clinical practice to reduce the damage to bone cells and nearby tissues and obtain good cutting surface quality. Considering the randomness of milling parameters during operation, a prediction method of milling temperature model for ball milling cutter considering the doctor’s surgical skills was proposed based on response surface method. Because of material anisotropy and microstructure difference between the cortical bone and cancellous bone, this paper would analyze the influencing factors in different bone layers to establish the prediction model of milling temperature in the segments of cortical bone and cancellous bone. Also, the influence and distribution of milling parameters on temperature in three cutting modes such as parallel cutting mode, cross cutting mode, and vertical cutting mode in the cortical bone region were analyzed. The parameter sensitivity of the milling temperature prediction model was analyzed by the Sobol method, and the influence of the input parameters on the output milling temperature was analyzed quantitatively.

Temperature Distribution Simulation, Prediction and Sensitivity Analysis of Orthogonal Cutting of Cortical Bone

Bone cutting plays an important role in spine surgical operations. The power devices with high speed employing in bone cutting usually leads to high cutting temperature of the bone tissue. This high temperature control is important in improving cutting surface quality and optimizing the cutting parameters. In this paper, the bone-cutting model was appropriately simplified for finite element (FE) based modeling of 2D orthogonal cutting to discuss the change law of cutting temperature of cortical bones for cervical vertebra, and to study the orthogonal cutting mechanism of the anisotropic cortical bone, a 3D FE simulation model had been also established in which longitudinal, vertical, and transversal cutting types were accomplished to investigate the effect of osteons orientation. Secondly, this response surface method was used to regress the simulation results, and establishes the prediction model of maximum temperature on cutting depth, cutting speed, and feed speed. Then, the Sobol method was used to analyze the sensitivity of the milling temperature prediction mathematical model parameters, in order to clarify and quantitatively analyze the influence of input milling parameters on the output milling temperature. Finally, the cutting temperatures obtained with the simulations were compared with the corresponding experimental results obtained from the bone milling tests. This study verifies the influence of key variables and the cutting parameters on thermo mechanical behavior of the bone cutting. The obtained cutting temperature distribution for the bone surfaces could be employed to establish a theoretical foundation for research on thermal damage control of bone tissues.

Optimization of Milling Parameters of Unmodified Calotropis Procera Fiber-Reinforced PLA Composite (UCPFRPC)

This study involves the optimization of the milling parameters of unmodified Calotropis Procera fiber-reinforced PLA composite (UCPFRPC). The material is prepared from the combination of 20% Calotropis-Procera and 80% of PLA by weight. The experiments are designed using the Taguchi methodology, where 16 experiments are obtained using the spindle rotational speed, depth of cut, and feed rate as the parameters. These experiments were conducted while obtaining thermal images using an infrared camera and recording the machining time. The change in mass was then determined and the material removal rate computed. The machined workpieces were then investigated for surface roughness. The study shows that the optimal milling parameters in the machining of UCPFRPC for the lowest surface roughness are 400 rpm, 400 mm/min, and 0.2 mm, for the rotational spindle speed, feed rate, and depth of cut. The parameters were 400 rpm, 100 mm/min, and 1.2 mm for the largest MRR, and 400 rpm, 400 mm/min, and 0.2 mm for the least average milling temperature. In all the responses, the depth of cut is the most significant factor.

Effect of Milling Vibration on The Machining Performance of 7075-T651 Aluminum Alloys

Milling of 7075-T651 is widely used in aerospace industry, however the process vibration restricts the machining performance in milling process. This paper puts forward a study on the effect of vibration on machining performance in milling to improve the machining quality. According to the characteristics of end milling, the process vibration is calculated and added based on the unformed chip thickness model of milling, and a milling simulation model considering vibration is established. Applying the finite element model and milling experiments, the simulation model is verified, the results proves the accuracy of the FEM models in predicting the milling force and milling temperature. Furthermore, the effect of milling vibration on machining performance is studied by numerical simulation, in which the relationship between amplitude-frequency characteristics and milling force-temperature fluctuation.

Effects of milling temperature and time on phase evolution of Ti-based alloy

Ti50Cu25Ni20Sn5 (at.%) powder was subjected to high-energy ball milling at room temperature and -78?C. As a function of the milling time, evaluation of phases, morphology and the refinement of grain size were investigated by scanning electron microscopy (SEM) and X-ray diffraction analysis (XRD), differential scanning calorimetry (DSC), transmission electron microscopy (TEM), and laser-diffraction particle size analysis (PSA). The transformation of the crystalline structure into an amorphous structure and then the transformation into a nanocrystalline structure during further milling was detected. The stress-induced martensitic transformation has taken place after 30 min milling time at both temperatures, the cubic Cu(Ni,Cu)Ti2 phase transforms into the orthogonal structure. The hardness value of powders after 150 min milling time increases from 506 to 780 HV0.01. The milling temperature does not significantly influence the amount of amorphous fraction (33-36 wt.%) but the composition of amorphous content is more influenced by temperature. The interval of crystallite size was between 1.2 and 11.7 nm after 180 min of milling. The amount and the cell parameters of the Sn-containing phases are different between the two milling experiments, owing to the diffusion coefficients of the Sn atom differ to a large extent.

Research on Finite Element Simulation and Parameters Optimization of Milling 7050-T7451 Aluminum Alloy Thin-walled Parts

Background: Thin-walled parts of aluminum alloy are easy to occur machining deformation duo to the characteristics of thin wall, low rigidity, and complex structure. Objective: To reduce and control the machining deformation, it is necessary to select reasonable machining parameters. Method: The influence of milling parameters on the milling forces, milling temperature, and machining deformation was analyzed through the established model based on ABAQUS. Then, the corresponding empirical formula was obtained by MATLAB, and parameters optimization was carried out as well. Besides, a lot of patents on machining thin-walled parts were studied. Results: The results shown that the prediction error of milling forces is about 15%, and 20% of milling temperature. In this case, the optimized milling parameters are as follows: ap=1 mm, ae=0.1 mm, n=12 000 r/min, and f=400 mm/min. It is of great significance to reduce the machining deformation and improve the machining quality of thin-walled parts.

Nickel-Based Alloy Dry Milling Process Induced Material Softening Effect

Improving the cutting efficiency is the major factor for improving the processing of nickel-based alloys. The novelty of this research is the calibrated SiAlON ceramic tool dry milling nickel-based alloy process. Firstly, the nickel-based alloy dry milling process was analyzed through the finite element method, and the required milling force and temperature were deduced. Then, several dry milling experiments were conducted with the milling temperature, and the milling force was monitored. The change in cutting speeds was from 400 m/min to 700 m/min. Experimental results verified the reduction of the dry milling force hypothesized by the simulation. The experiment also indicated that with a cut depth of 0.3 mm, cut width of 6 mm, and feed per tooth of 0.03 mm/z, when milling speed exceeded 527.52 m/min, the milling force began to decrease, and the milling temperature exceeded the nickel-based alloy softening temperature. This indicated that easy cutting could be realized under high-speed dry milling conditions. The interpolation curve about average temperature and average milling forces showed similarity to the tensile strength reduction with the rise of temperature.

Temperature modeling during the processing of a compressor monowheel

A mathematical model and methodology for calculating the temperature during mechanical processing of the compressor monowheel are developed. The calculation results according to the developed algorithm are presented. Keywords modeling, monowheel, milling, temperature. [email protected]

Preparation of Nanocrystalline Fe2O3 Powder by Cryomilling with Liquid Nitrogen and its Magnetic Property

Rapid preparation of nanocrystalline γ-Fe2O3 powder with superparamagnetism was realized by cryomilling commercial Fe2O3 powder using liquid nitrogen. The effects of milling temperature and duration on the grain size, phase and microstructure of the nanocrystalline Fe2O3 powder were analyzed. Magnetic property of the nanocrystalline γ-Fe2O3 powder was also tested by magnetometer at room temperature. The results demonstrate that nanocrystalline γ-Fe2O3 powder with single phase can be prepared rapidly by cryomilling with liquid nitrogen. The mean particle size of γ-Fe2O3 powder can be reduced from 300 nm to 13 nm by cryomilling at −130 °C within 3 hours. The nanocrystalline γ-Fe2O3 powder shows superparamagnetism at room temperature.