Support vector regression and genetic-algorithm-based multiobjective optimization of mesoscopic geometric characteristic parameters of ball-end milling tool

2020 ◽  
Vol 234 (10) ◽  
pp. 1333-1345 ◽  
Author(s):  
Xin Tong ◽  
Xianli Liu ◽  
Song Yu
Keyword(s):  
Genetic Algorithm ◽  
Titanium Alloys ◽  
Support Vector Regression ◽  
End Milling ◽  
Geometric Characteristic ◽  
Support Vector ◽  
Characteristic Parameters ◽  
Ball End Milling ◽  
Milling Tool

The poor machinability of titanium alloys results in the serious wear of the rake face of a ball-end milling tool. Previous studies indicated that the mesoscopic geometric characteristics of the tool can effectively improve the wear resistance. Therefore, in this thesis, a milling force model and a milling temperature model of a ball-end milling tool were established to verify the effect of the blunt and negative chamfer tool edges. Setting up a test platform for milling titanium alloy, the influence of mesoscopic geometric characteristic parameters on cutting performance of the ball-end milling tool was analyzed. In addition, based on the support vector regression and genetic algorithm, the optimal mesoscopic geometric characteristic parameters were obtained, which were under the four evaluation indices, such as mechanical–thermal characteristics, tool wear, and surface quality of the workpiece. It was verified experimentally that the tool life of the optimized micro-textured tools with the blunt and chamfer tool edges were improved by 33% and 25%, respectively, and the surface roughness was reduced by 26% and 23%, respectively, which were compared to the non-optimized tools. This thesis provides a reference for improving the processing efficiency and the quality of titanium alloys.

Improvement of Surface Roughness in End Milling of Ti6Al4V by Coupling RSM with Genetic Algorithm

2011 ◽  
Vol 264-265 ◽  
pp. 1154-1159
Author(s):  
Anayet Ullah Patwari ◽  
A.K.M. Nurul Amin ◽  
S. Alam
Keyword(s):  
Genetic Algorithm ◽  
Surface Roughness ◽  
Titanium Alloys ◽  
End Milling ◽  
Fitness Function ◽  
Cutting Speed ◽  
Weight Ratio ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Resistance Surface

Titanium alloys are being widely used in the aerospace, biomedical and automotive industries because of their good strength-to-weight ratio and superior corrosion resistance. Surface roughness is one of the most important requirements in machining of Titanium alloys. This paper describes mathematically the effect of cutting parameters on Surface roughness in end milling of Ti6Al4V. The mathematical model for the surface roughness has been developed in terms of cutting speed, feed rate, and axial depth of cut using design of experiments and the response surface methodology (RSM). Central composite design was employed in developing the surface roughness models in relation to primary cutting parameters. The experimental results indicate that the proposed mathematical models suggested could adequately describe the performance indicators within the limits of the factors that are being investigated. The developed RSM is coupled as a fitness function with genetic algorithm to predict the optimum cutting conditions leading to the least surface roughness value. MATLAB 7.0 toolbox for GA is used to develop GA program. The predicted results are in good agreement with the experimental one and hence the model can be efficiently used to achieve the minimum surface roughness value.

Experimental Investigation of the Effect of the Machine Kinematic Behavior on the Surface Topography and Roughness in High Speed Ball end Milling of the AISI4142 Steel

2021 ◽  
Author(s):  
Sai Lotfi ◽  
Belguith Rami ◽  
Baili Maher ◽  
Desseins Gilles ◽  
Bouzid Wassila
Keyword(s):  
Surface Topography ◽  
High Speed ◽  
End Milling ◽  
Experimental Investigations ◽  
Ball End Milling ◽  
Tool Paths ◽  
Stationary Zone ◽  
Machining Errors ◽  
Kinematic Behavior ◽  
Milling Tool

Abstract The analysis of the surface topography in ball end milling is an objective studied by many researchers, several methods were used and many combinations of cutting conditions and machining errors are considered. In the milling tool paths the trajectories presents a points of changing direction where the tool decelerates before and accelerates after respecting the velocity profiles of the machine. In this paper, we propose experimental investigations of the effect of the kinematic behavior of the machine tool on the surface quality. A poor topography and roughness are remarked on the deceleration and the acceleration zones compared to the stationary zone.

scholarly journals Optimization of Texture Density Distribution of Carbide Alloy Micro-Textured Ball-End Milling Cutter Based on Stress Field

2020 ◽  
Vol 10 (3) ◽  
pp. 818
Author(s):  
Minli Zheng ◽  
Chunsheng He ◽  
Shucai Yang
Keyword(s):  
Wear Resistance ◽  
Stress Field ◽  
Density Distribution ◽  
Titanium Alloys ◽  
Contact Area ◽  
End Milling ◽  
Variable Density ◽  
Milling Cutter ◽  
Ball End Milling ◽  
Texture Density

The insertion of micro-textures plays a role in reducing friction and increasing wear resistance of the cutters, which also has a certain impact on the stress field of the cutter during milling. Therefore, in order to study the mechanisms of friction reduction and wear resistance of micro-textured cutters in high speed cutting of titanium alloys, the dynamic characteristics of the instantaneous stress field during the machining of titanium alloys with micro-textured cutters were studied by changing the distribution density of the micro-textures on the cutter. First, the micro-texture insertion area of the ball-end milling cutter was theoretically analyzed. Then, variable density micro-textured ball-end milling cutters and non-texture cutters were used to cut titanium alloy, and the mathematical model of milling force and cutter-chip contact area was established. Then, the stress density functions of different micro-texture density cutters and non-texture cutters were established to simulate the stress fields of variable density micro-textured ball-end milling cutters and non-texture cutters. Finally, the genetic algorithm was used to optimize the variable density distribution of micro-textured cutters in which the instantaneous stress field of the cutters was taken as the optimization objective. The optimal solution for the variable density distribution of the micro-textured cutter in the cutter-chip tight contact area was obtained as follows: the texture distribution densities in the first, second, and third areas are second, and third areas are 0.0905, 0.0712, and 0.0493, respectively.

scholarly journals Applying hybrid support vector regression and genetic algorithm to water alternating CO 2 gas EOR

2020 ◽  
Vol 10 (3) ◽  
pp. 613-630 ◽  
Author(s):  
Menad Nait Amar ◽  
Noureddine Zeraibi ◽  
Ashkan Jahanbani Ghahfarokhi
Keyword(s):  
Genetic Algorithm ◽  
Support Vector Regression ◽  
Support Vector

Comprehensive Evaluation of Wind Turbine Type Selection Based on GA-SVR Model

2012 ◽  
Vol 468-471 ◽  
pp. 579-582
Author(s):  
Wei Sun ◽  
Le Shen
Keyword(s):  
Genetic Algorithm ◽  
Global Optimization ◽  
Wind Turbine ◽  
Support Vector Regression ◽  
Empirical Analysis ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
High Accuracy ◽  
Support Vector ◽  
Type Selection

Aiming at the current situation of wind turbine type selection in China, this paper has built a more scientific and systematic index system for comprehensive evaluation of wind turbine type selection, and also applied the Support Vector Regression machine evaluation model with parameters optimized by Genetic Algorithm. Through automatic global optimization for parameters, this model has reached an extremely high accuracy required for evaluation of type selection. Empirical analysis shows that the application of this model has a realistic popularized significance for improving the method of the wind turbine type selection and enhancing its efficiency.

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