ForceNet: An offline cutting force prediction model based on neuro-physical learning approach

2021 ◽  
Vol 61 ◽  
pp. 1-15
Author(s):  
Ke Xu ◽  
Yingguang Li ◽  
Jiachen Zhang ◽  
Gengxiang Chen
Keyword(s):  
Prediction Model ◽  
Cutting Force ◽  
Learning Approach ◽  
Cutting Force Prediction ◽  
Force Prediction ◽  
Model Based

scholarly journals Cutting Force Modeling and Experimental Study for Ball-End Milling of Free-Form Surfaces

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Zhaozhao Lei ◽  
Xiaojun Lin ◽  
Gang Wu ◽  
Luzhou Sun
Keyword(s):  
Prediction Model ◽  
Cutting Force ◽  
Chip Thickness ◽  
Free Form ◽  
Force Model ◽  
Cutting Force Prediction ◽  
Force Prediction ◽  
Undeformed Chip Thickness ◽  
Free Form Surface ◽  
Free Form Surfaces

In order to improve the machining quality and efficiency and optimize NC machining programming, based on the existing cutting force models for ball-end, a cutting force prediction model of free-form surface for ball-end was established. By analyzing the force of the system during the cutting process, we obtained the expression equation of the instantaneous undeformed chip thickness during the milling process and then determined the rule of the influence of the lead angle and the tilt angle on the instantaneous undeformed chip thickness. It was judged whether the cutter edge microelement is involved in cutting, and the algorithm flow chart is given. After that, the cutting force prediction model of free-form surface for ball-end and pseudocodes for cutting force prediction were given. MATLAB was used to simulate the prediction force model. Finally, through the comparative analysis experiment of the measured cutting force and the simulated cutting force, the experimental results are basically consistent with the theoretical prediction results, which proves that the model established in this paper can accurately predict the change of the cutting force of the ball-end cutter in the process of milling free-form surface, and the error of the cutting force prediction model established in this paper is reduced by 15% compared with the traditional cutting force prediction model.

scholarly journals Using model based analytic cutting force prediction in CAM toolpath generation

Procedia CIRP ◽  
2019 ◽  
Vol 82 ◽  
pp. 467-472
Author(s):  
Steffen Braun ◽  
Michael Storchak ◽  
Hans-Christian Möhring
Keyword(s):  
Cutting Force ◽  
Cutting Force Prediction ◽  
Force Prediction ◽  
Model Based ◽  
Toolpath Generation

Research on Physical Simulation of Virtual CNC Turning

2012 ◽  
Vol 510 ◽  
pp. 50-53
Author(s):  
Chun Lei Li
Keyword(s):  
Steady State ◽  
Prediction Model ◽  
Cutting Force ◽  
Cutting Forces ◽  
Physical Simulation ◽  
Work Piece ◽  
Machining Error ◽  
Cutting Force Prediction ◽  
Force Prediction ◽  
Cnc Turning

Sources and measurement of cutting forces are studied to establish the steady-state cutting force prediction model. Modeling of work piece machining error is analyzed, a simplified process coordinate system is established, and the mathematical solving model of machining error within the work piece is given. The cutting force due to work piece bending deformation is studied, a work piece deformation factor error model is established based on steady-state cutting force and the prediction simulation of cutting forces and machining error is achieved.

scholarly journals Cutting Force Prediction Model for Elliptical Vibration Cutting SiCp/Al Based on Three-Phase Friction Theory

2021 ◽  
Vol 11 (22) ◽  
pp. 10737
Author(s):  
Yucheng Li ◽  
Xu Zhang ◽  
Cui Wang
Keyword(s):  
Prediction Model ◽  
Cutting Force ◽  
Cutting Forces ◽  
Volume Fraction ◽  
Cutting Speed ◽  
Contact Length ◽  
Cutting Force Prediction ◽  
Force Prediction ◽  
Elliptical Vibration ◽  
Three Phase

The friction behavior in the tool-chip interface is an essential issue in aluminum matrix composite material (AMCM) turning operations. Compared with conventional cutting, the elliptical vibration (EVC) cutting AMCM has attractive advantages, such as low friction, small cutting forces, etc. However, the friction mechanism of the EVC cutting AMCM is still inadequate, especially the model for cutting forces analyzing and predicting, which hinders the application of EVC in the processing of AMCM. In this paper, a cutting force prediction model for EVC cutting SiCp/Al is established, which is based on the three-phase friction (TPF) theory. The friction components are evaluated and predicted at the tool-chip interface (TCI), tool-particle interface (TPI) and tool-matrix (TMI), respectively. In addition, the tool-chip contact length and SiC particle volume fraction were defined strictly and the coefficient of friction was predicted. Based on the Johnson-Cook constitutive model, the experiment was conducted on SiCp/Al. The cutting speed and tool-chip contact length were used as input parameters of the friction model, and the dynamic changes of cutting force and stress distribution were analyzed. The results shown that when cutting speed reaches 574 m/min, the tool-chip contact length decreases to 0.378 mm. When the cutting speed exceeds 658 m/min, the cutting force decreases to a minimum of 214.9 N and remains stable. In addition, compared with conventional cutting, the proposed prediction model can effectively reduce the cutting force.

Modeling and investigation of cutting force for SiCp/Al composites during ultrasonic vibration-assisted turning

2021 ◽  
pp. 095440892110607
Author(s):  
Jieqiong Lin ◽  
Chao Wang ◽  
Mingming Lu ◽  
Jiakang Zhou ◽  
Shixin Zhao ◽  
...  
Keyword(s):  
Prediction Model ◽  
Cutting Force ◽  
Ultrasonic Vibration ◽  
Cutting Speed ◽  
Machining Process ◽  
Depth Of Cut ◽  
Cutting Force Prediction ◽  
Force Prediction ◽  
Depth Direction ◽  
Experimental Values

The machining process of SiCp/Al composites is considerably difficult because of the addition of ceramic particles. As an effective machining method, ultrasonic vibration-assisted turning is used to process SiCp/Al composites, which can effectively reduce the cutting force, improve the surface quality, and reduce the tool wear. This study developed a cutting force prediction model for ultrasonic vibration-assisted turning of SiCp/Al composites, which comprehensively considers the instantaneous depth of cut and the instantaneous shear angle. This model divides the cutting force into the chip formation force considering the instantaneous depth of cut, the friction force considering the influence of SiC particles at tool-chip interface, the particle fracture force, and the ultrasonic impact force in the cutting depth direction. By comparing the predicted value of the main cutting force with the experimental values, the results present the same trend, which verifies the feasibility of the cutting force prediction model. In addition, the influence of vibration amplitude, depth of cut, and cutting speed on the main cutting force is analyzed. The systematic cutting experiments show that ultrasonic vibration-assisted turning can significantly reduce the cutting force and improve the machinability of SiCp/Al composites.

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