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

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Heqiang Tian ◽  
Jingbo Pan ◽  
Yu Gao ◽  
Xiaoqing Dang ◽  
Bin Tian ◽  
...  
Keyword(s):  
Prediction Model ◽  
Cortical Bone ◽  
Cancellous Bone ◽  
Bone Cells ◽  
Prediction Method ◽  
Milling Process ◽  
Milling Parameters ◽  
Cutting Surface ◽  
Milling Temperature ◽  
Cutting Modes

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.

Experimental Study on Thermal and Force Characteristics in the Dry Slotting of Cortical Bone

2016 ◽  
Vol 1136 ◽  
pp. 233-238
Author(s):  
Liang Wen ◽  
Zi Han Zhao ◽  
Jin Bang Song ◽  
De Dong Yu ◽  
Ming Chen ◽  
...  
Keyword(s):  
Cutting Force ◽  
Cortical Bone ◽  
Feed Rate ◽  
High Speed ◽  
Cutting Temperature ◽  
Growth Direction ◽  
Milling Process ◽  
Spindle Speed ◽  
Milling Force ◽  
Milling Temperature

Cutting force and temperature are the two chief factors affecting bone rehabilitation during bone cutting in many orthopedic surgeries. To reveal new knowledge of thermal and force when milling cortical bone, slotting experiments were carried on high-speed milling platform. Cutting force and temperature were measured during the milling process. The effects of cutting inputs on cutting thermal and force were researched in detail. The results showed that: feed rate and spindle speed had a great impact on the milling temperature, while the milling force was mainly influenced by spindle speed. A feed rate of 1.0-1.4 mm/s is recommended to obtain preferable milling force and temperature, and a larger feed rate of 1.2-1.4 mm/s is advised to use with a lower spindle speed (8000-20000 r/min), while a smaller feed rate of 1.0-1.2 mm/s should be chosen when spindle speed was between 20000-40000 r/min. Feeding parallel to the growth direction of the cortical bone can significantly reduce the milling temperature, but there was no obvious change in milling force. The lowest cutting temperature obtained during the experiment was around 50 °C without coolant, which was acceptable for orthopedic surgeries.

Study on 3D Temperature Distribution of Milling Insert With Complex Groove

2004 ◽  
Author(s):  
Guangyu Tan ◽  
Guangjun Liu ◽  
Guanghui Li ◽  
Yiming (Kevin) Rong
Keyword(s):  
Temperature Field ◽  
Density Function ◽  
Temperature Increase ◽  
Parametric Model ◽  
Milling Process ◽  
Element Analysis ◽  
Milling Parameters ◽  
Tool Surface ◽  
Milling Temperature ◽  
Correlative Relationship

About 90% energy generated in the milling process is transferred to heat which makes the temperature to increase. The temperature increase has a correlative relationship with the milling mechanism and milling parameters. The severe temperature increase results in the fracture of milling insert during milling process and reduces the life of the tool. Experiments of milling temperature measurement were conducted to study the temperature field in milling. The heating density function on the tool surface was established. The temperature profile and distribution were shown. A parametric model was established to represent the milling insert with 3D complex groove. Based on a finite element analysis, the temperature field on the milling insert was evaluated and the boundary condition was established by using the heating density function. The study provides a reference for the development and optimization of complex grooves of milling inserts.

scholarly journals Long-Term Use of Glucocorticoid Exacerbates Bone Lesions in Postmenopausal Women With Rheumatoid Arthritis

2021 ◽  
Author(s):  
Masaki Hatano ◽  
Izuru Kitajima ◽  
Masaki Nakamura ◽  
Kazuya Isawa ◽  
Tatsuya Suwabe ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Cortical Bone ◽  
Cancellous Bone ◽  
Structural Changes ◽  
Bone Cells ◽  
Bone Lesions ◽  
Marrow Cavity ◽  
Bone Marrow Cavity ◽  
The Common

Abstract Background Glucocorticoid-induced osteoporosis is osteoporosis arising due to long-term use of glucocorticoids. Current despite decades of intense research, the effects of long-term use of glucocorticoids in humans on bone cells and bone structural changes remain unclear. Methods We performed postmortem histomorphometric analysis of bone from two female patients with rheumatoid arthritis aged 64y and 85y. Our two patients had been treated with glucocorticoids for 19 years and 14 years, respectively. Results In case 1, all markers of cancellous bone volume were markedly decreased compared with the age-matched reference range. Connectivity of cancellous bone trabecula was absent. Only a few island bones were noted. There was prominent thinning of the cortical bone, and extension of the bone marrow cavity into the cortical bone with prominent cortical porosis. Cortical nodes between the endocortical surface and the trabecula disappeared due to endocortical resorption. Stoppage of lamellar structure was observed because the bone resorption by osteoclasts surpassed bone formation by osteoblasts. Empty lacunae characterized by disappearance of osteocytes were visible. In case 2, all volume markers of cancellous bone were decreased to the same extent as case 1. However, cortical porosis was more prominent than case 1. Conclusion These two cases suggest that use of glucocorticoid therapy > 10 y can induce severe osteoporosis in elderly RA women with higher disease activity, and that the disappearance of cancellous bone is the common characteristic. The 85 year-old woman was characterized by cortical porosis.

Stormwater inflow prediction using radar rainfall data compressed by principal component analysis

2006 ◽  
Vol 1 (1) ◽  
Author(s):  
K. Katayama ◽  
K. Kimijima ◽  
O. Yamanaka ◽  
A. Nagaiwa ◽  
Y. Ono
Keyword(s):  
Principal Component Analysis ◽  
Prediction Model ◽  
Principal Components ◽  
Prediction Method ◽  
Principal Component ◽  
Component Analysis ◽  
Rainfall Data ◽  
Radar Rainfall ◽  
Input Variables ◽  
Inflow Prediction

This paper proposes a method of stormwater inflow prediction using radar rainfall data as the input of the prediction model constructed by system identification. The aim of the proposal is to construct a compact system by reducing the dimension of the input data. In this paper, Principal Component Analysis (PCA), which is widely used as a statistical method for data analysis and compression, is applied to pre-processing radar rainfall data. Then we evaluate the proposed method using the radar rainfall data and the inflow data acquired in a certain combined sewer system. This study reveals that a few principal components of radar rainfall data can be appropriate as the input variables to storm water inflow prediction model. Consequently, we have established a procedure for the stormwater prediction method using a few principal components of radar rainfall data.

scholarly journals Nickel-Based Alloy Dry Milling Process Induced Material Softening Effect

Materials ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 3758 ◽  
Author(s):  
Jun Zha ◽  
Zelong Yuan ◽  
Hangcheng Zhang ◽  
Yipeng Li ◽  
Yaolong Chen
Keyword(s):  
High Speed ◽  
Softening Temperature ◽  
Milling Process ◽  
Dry Milling ◽  
Milling Force ◽  
Softening Effect ◽  
Milling Temperature ◽  
Nickel Based Alloy ◽  
Alloy Softening ◽  
Milling Forces

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.

scholarly journals Developing an Enhanced Short-Range Railroad Track Condition Prediction Model for Optimal Maintenance Scheduling

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Peng Xu ◽  
Chuanjun Jia ◽  
Ye Li ◽  
Quanxin Sun ◽  
Rengkui Liu
Keyword(s):  
Prediction Model ◽  
Short Range ◽  
Prediction Method ◽  
Maintenance Scheduling ◽  
Railroad Track ◽  
Track Geometry ◽  
Track Maintenance ◽  
Track Condition ◽  
Optimal Maintenance ◽  
Process Work

As railroad infrastructure becomes older and older and rail transportation is developing towards higher speed and heavier axle, the risk to safe rail transport and the expenses for railroad maintenance are increasing. The railroad infrastructure deterioration (prediction) model is vital to reducing the risk and the expenses. A short-range track condition prediction method was developed in our previous research on railroad track deterioration analysis. It is intended to provide track maintenance managers with two or three months of track condition in advance to schedule track maintenance activities more smartly. Recent comparison analyses on track geometrical exceptions calculated from track condition measured with track geometry cars and those predicted by the method showed that the method fails to provide reliable condition for some analysis sections. This paper presented the enhancement to the method. One year of track geometry data for the Jiulong-Beijing railroad from track geometry cars was used to conduct error analyses and comparison analyses. Analysis results imply that the enhanced model is robust to make reliable predictions. Our in-process work on applying those predicted conditions for optimal track maintenance scheduling is discussed in brief as well.

Study on CNC Milling Heat and Residual Stress Relationship Model

2016 ◽  
Vol 693 ◽  
pp. 900-905
Author(s):  
W.W. Song ◽  
J.L. Wang ◽  
H.F. Wang ◽  
Dun Wen Zuo
Keyword(s):  
Residual Stress ◽  
Deformation Theory ◽  
Metal Cutting ◽  
Milling Process ◽  
Cnc Milling ◽  
Theoretical Support ◽  
Cutting Heat ◽  
Relationship Model ◽  
Milling Temperature ◽  
Problem Solving Process

In this paper, the effect of the cutting heat on the workpiece in the processing was studied. Its essence is to study relationship between the workpiece temperature variation and internal residual stress distribution. In the specific problem-solving process, the metal cutting theory, finite element related knowledge and metal elastoplastic deformation theory were combined, and established a mathematical model which was suitable for the model of the milling temperature and residual stress in the milling process. It would provide theoretical support for future study on milling deformation mechanism.

scholarly journals Osteopontin Deficiency Induces Parathyroid Hormone Enhancement of Cortical Bone Formation

Endocrinology ◽  
2003 ◽  
Vol 144 (5) ◽  
pp. 2132-2140 ◽  
Author(s):  
Keiichiro Kitahara ◽  
Muneaki Ishijima ◽  
Susan R. Rittling ◽  
Kunikazu Tsuji ◽  
Hisashi Kurosawa ◽  
...  
Keyword(s):  
Bone Mineral Density ◽  
Bone Formation ◽  
Bone Mass ◽  
Cortical Bone ◽  
Cancellous Bone ◽  
Wild Type ◽  
Mineral Density ◽  
Cortical Bone Mass ◽  
Intermittent Pth

Intermittent PTH treatment increases cancellous bone mass in osteoporosis patients; however, it reveals diverse effects on cortical bone mass. Underlying molecular mechanisms for anabolic PTH actions are largely unknown. Because PTH regulates expression of osteopontin (OPN) in osteoblasts, OPN could be one of the targets of PTH in bone. Therefore, we examined the role of OPN in the PTH actions in bone. Intermittent PTH treatment neither altered whole long-bone bone mineral density nor changed cortical bone mass in wild-type 129 mice, although it enhanced cancellous bone volume as reported previously. In contrast, OPN deficiency induced PTH enhancement of whole-bone bone mineral density as well as cortical bone mass. Strikingly, although PTH suppressed periosteal bone formation rate (BFR) and mineral apposition rate (MAR) in cortical bone in wild type, OPN deficiency induced PTH activation of periosteal BFR and MAR. In cancellous bone, OPN deficiency further enhanced PTH increase in BFR and MAR. Analysis on the cellular bases for these phenomena indicated that OPN deficiency augmented PTH enhancement in the increase in mineralized nodule formation in vitro. OPN deficiency did not alter the levels of PTH enhancement of the excretion of deoxypyridinoline in urine, the osteoclast number in vivo, and tartrate-resistant acid phosphatase-positive cell development in vitro. These observations indicated that OPN deficiency specifically induces PTH activation of periosteal bone formation in the cortical bone envelope.

Milling Force Prediction for Circular Contour Machining

2014 ◽  
Vol 800-801 ◽  
pp. 243-248
Author(s):  
Kai Zhao ◽  
Zhan Qiang Liu
Keyword(s):  
Prediction Model ◽  
Milling Process ◽  
Machining Process ◽  
Curvature Radius ◽  
Force Model ◽  
Milling Force ◽  
Circular Contour ◽  
The Mean ◽  
Contour Machining ◽  
Matlab Programming

When machining the complex parts of aircraft engines, the milling force for the circular contour must be accurately predicted to reduce machining vibration. In this paper, the prediction model of the mean milling force per tooth during machining circular contour is developed. Firstly, the formulas of the entry angle, the exit angle and the equivalent feed per tooth are established through the analysis of circular contour milling process. Then, the equation of the mean milling force per tooth is deduced based on mechanistic force model during the circular contour machining process. Finally, the prediction model of mean milling force per tooth during machining circular contour is developed using MATLAB programming. The relationship between the milling force per tooth and surface curvature radius of the machined workpiece is also analyzed in this paper.

Research on Combined Prediction Model for Busy Telephone Traffic

2014 ◽  
Vol 610 ◽  
pp. 789-796
Author(s):  
Jiang Bao Li ◽  
Zhen Hong Jia ◽  
Xi Zhong Qin ◽  
Lei Sheng ◽  
Li Chen
Keyword(s):  
Prediction Model ◽  
Prediction Accuracy ◽  
Low Frequency ◽  
Prediction Method ◽  
Pso Algorithm ◽  
Frequency Component ◽  
Least Square ◽  
High Frequency Component ◽  
Support Vector ◽  
Telephone Traffic

In order to improve the prediction accuracy of busy telephone traffic, this study proposes a busy telephone traffic prediction method that combines wavelet transformation and least square support vector machine (lssvm) model which is optimized by particle swarm optimization (pso) algorithm. Firstly, decompose the pretreatment of busy telephone traffic data with mallat algorithm and get low frequency component and high frequency component. Secondly, reconfigure each component and use pso_lssvm model predict each reconfigured one. Then the busy telephone traffic can be achieved. The experimental results show that the prediction model has higher prediction accuracy and stability.

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