3D FEM Simulation of Milling Force in Corner Machining Process

Yue, Caixu; Huang, Cui; Liu, Xianli; Hao, Shengyu; Liu, Jun

doi:10.1007/s10033-017-0088-2

Cited by 10 publications

(3 citation statements)

References 20 publications

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“…Additionally, this approach eliminates the influence of the machining precision on the obtained results, which can have a crucial impact on the experimental test results. In the literature, multiple examples of FEA for punching [ 8 , 9 , 10 , 11 ], drilling [ 12 , 13 ], milling [ 14 , 15 ] or cutting processes [ 16 , 17 ] can be found.…”

Section: Methodsmentioning

confidence: 99%

A Coupled Eulerian-Lagrangian Simulation and Tool Optimization for Belt Punching Process with a Single Cutting Edge

et al. 2021

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The objective of this paper is to analyze the belt punching process with the use of a single cutting edge and discuss the influence of geometrical features of the piercing punch on the perforation force. Two basic shapes of the piercing punch with a single cutting edge were tested: tools with the blade pointing inside or pointing outside. The analytical models of the stress distribution in the shearing cross sections were derived for both punches. The presented model, along with the series of empirical tests and Coupled Eulerian-Lagrangian simulation, was used for finding the effective geometry of the piercing punch with a single cutting edge for the belt perforation. The geometrical parameters taken into consideration for the tool optimization were the following: angle of the blade, thickness of the wall and diameter of the piercing punch cutting edge. The obtained results show that changing these parameters has a significant influence on the perforation force necessary to execute the machining process and affects the quality of the holes in the perforated belts. The most important geometrical features of the hollow sharpened punch are the angle and the direction of the blade, which change the force distribution and, as a result, the mechanics of the process.

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Section: Methodsmentioning

confidence: 99%

A Coupled Eulerian-Lagrangian Simulation and Tool Optimization for Belt Punching Process with a Single Cutting Edge

et al. 2021

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“…Wibowo also studied [8] the optimal combination of cutting parameters during the pocket mill process of plastic mold steels material, and Arruda [9] focused on studying the optimization of the finishing milling process using ball nose end mill. Other research belongs to Rathod [10], Liu [11], Binder [12], Lofti [13], Attanaio [14], and Yue [15], who addressed the issue of tool wear and chip formation using FEA. Also, Lofti and Farid, in their study [16], address chip breaker geometry on chip shape and the forces that appeared in the cutting process.…”

Section: Introductionmentioning

confidence: 99%

Study about the chip formation in the turning process using the finite element analysis

Pop

Țîțu

2022

IOP Conf. Ser.: Mater. Sci. Eng.

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At this time, there is a significant interest in the chip shape and formation at the international level, an issue studied based on mathematical calculations, experiments, and finite element analysis. The analysis of the chip formation process showed that the thickness of the undetached chip also varies according to the rake angle of the cutting tool, and using 3D models to analyze the chip formation process demonstrates this fact. Following the research, a study was conducted in which an analysis of the chip morphology is presented. Using Deform 2D application, a finite element simulation - a comparative analysis of the chip formation was performed when the value of the clearance angle varies. The increasing variety of cutting radius values has an influence on the way the chips are formed in terms of thickness, which generate differences in its shape. Following the study, a series of conclusions and own findings emerged that with the increase of the cutting-edge radius, the stress distribution is radial over a greater area of the part, reason for which the deformation of the chip is smaller. Arguments have also been made on distribution of the temperature, which is directly influenced by the shape of the tool, influencing the temperature of the generated chip. The results also show that with the increase of the cutting-edge radius of the tool, there is a tendency for the detached chip to settle.

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“…Valarmathi et al (2015) used response surface methodology to establish a mathematical model that predicted the influence of input control parameters on the cutting force generated during the medium density fiberboard (MDF) drilling. Yue et al (2017) developed serials of 3D FEM models for the corner milling process based on DEFORM software. Tool curved trajectory was achieved by tool location with milling time, and the results provided a guide for optimizing cutting parameters in the cutting process.…”

Section: Introductionmentioning

confidence: 99%

Prediction of straight tooth milling of Scots pine wood by shank cutter based on neural net computations and regression analysis

Cao

2022

BioRes

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Regression models and a neural net approach were used to predict the cutting performance during milling of Scots pine (Pinus sylvestris L.) by shank cutter. The influence of rake angle, spindle speed, and milling depth on surface roughness of the workpiece, as well as the connection between the milling force and the surface roughness, were thoroughly considered. Four approaches were used to predict the workpiece’s surface roughness based on the experimental data: Back Propagation Neural Network (BPNN), Radial Basis Function Neural Network (RBFNN), Support Vector Machines (SVM), and multiple linear regression. The comparative analysis of the predictive models showed that Neural Network (NN) had preferable performance for prediction of machined surface roughness, with an R2 of 0.98. The SVM had certain fluctuations and the R2 of the multiple linear regression was just 0.87, indicating that they did not fit well for prediction machined surface roughness. In summary, the effective trend of milling parameters on the machined surface roughness of Scots pine was similar to multiple nonlinear regression, and the accurate prediction by BPNN model can provide technical support for the surface roughness of the Scots Pine and enhance shank cutter performance.

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3D FEM Simulation of Milling Force in Corner Machining Process

Cited by 10 publications

References 20 publications

A Coupled Eulerian-Lagrangian Simulation and Tool Optimization for Belt Punching Process with a Single Cutting Edge

A Coupled Eulerian-Lagrangian Simulation and Tool Optimization for Belt Punching Process with a Single Cutting Edge

Study about the chip formation in the turning process using the finite element analysis

Prediction of straight tooth milling of Scots pine wood by shank cutter based on neural net computations and regression analysis

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