Cutting Force Prediction in Drilling of Anisotropic Materials

2012 ◽  
Vol 504-506 ◽  
pp. 1365-1370
Author(s):  
Takashi Matsumura ◽  
Shoichi Tamura ◽  
Pedro José Arrazola
Keyword(s):  
Shear Stress ◽  
Cutting Force ◽  
Orthogonal Cutting ◽  
Anisotropic Materials ◽  
Force Model ◽  
Cutting Force Prediction ◽  
Force Prediction ◽  
Cutting Energy ◽  
Chip Flow ◽  
Stress Changes

The paper presents a predictive cutting force model in drilling of anisotropic materials. Three dimensional chip flow in drilling is interpreted as a piling up of the orthogonal cuttings in the planes containing the cutting velocities and the chip flow velocities. The cutting models in the chip flow are determined to calculate the cutting energy using the orthogonal cutting data. Then, the chip flow direction is determined to minimize the cutting energy. The cutting force can be predicted in the determined chip flow model. The cutting force with anisotropy in the material is modeled as the change in the shear stress on the shear plane. The shear stress changes with the rotation angle of the cutter. The cutting force prediction is verified in drilling of a titanium alloy. The anisotropic parameters are identified to minimize the model error between the measured and the predicted cutting forces. The periodical oscillation of the cutting force is also predicted by anisotropy in the shear stress.

scholarly journals Adaptive Cutting Force Prediction in Milling Processes

2010 ◽  
Vol 4 (3) ◽  
pp. 221-228 ◽  
Author(s):  
Takashi Matsumura ◽  
◽  
Takahiro Shirakashi ◽  
Eiji Usui
Keyword(s):  
Cutting Force ◽  
Cutting Forces ◽  
Flow Model ◽  
Flow Direction ◽  
Orthogonal Cutting ◽  
Cutting Parameters ◽  
Milling Process ◽  
Force Model ◽  
Cutting Force Prediction ◽  
Chip Flow

An adaptive force model is presented to predict the cutting force and the chip flow direction in milling. The chip flow model in the milling process is made by piling up the orthogonal cuttings in the planes containing the cutting velocities and the chip flow velocities. The chip flow direction is determined to minimize the cutting energy. The cutting force is predicted using the determined chip flow model. The force model requires the orthogonal cutting data, which associate the orthogonal cutting models with the cutting parameters. Basically, the required data for simulation can be measured in the orthogonal cutting tests. However, it is difficult to perform the cutting tests with specialized setups in the machine shops. The paper presents the adaptive model to accumulate and update the orthogonal cutting data with referring the measured cutting forces in milling. The orthogonal cutting data are identified to minimize the error between the predicted and the measured cutting forces. Then, the cutting forces can be predicted well in many cutting operations using the identified orthogonal cutting data. The adaptive is effective not only in extending the database but also in improving the quality of the database for the accurate predictions.

Analysis of Cutting Force in Elastomer End-Milling

2017 ◽  
Vol 11 (6) ◽  
pp. 958-963
Author(s):  
Koji Teramoto ◽  
◽  
Takahiro Kunishima ◽  
Hiroki Matsumoto
Keyword(s):  
Parameter Identification ◽  
Cutting Force ◽  
Cutting Forces ◽  
End Milling ◽  
Process Models ◽  
Force Model ◽  
Cutting Force Model ◽  
Cutting Force Prediction ◽  
Force Prediction ◽  
The Stability

Elastomer end-milling is attracting attention for its role in the small-lot production of elastomeric parts. In order to apply end-milling to the production of elastomeric parts, it is important that the workpiece be held stably to avoid deformation. To evaluate the stability of workholding, it is necessary to predict cutting forces in elastomer end-milling. Cutting force prediction for metal workpiece end-milling has been investigated for many years, and many process models for end-milling have been proposed. However, the applicability of these models to elastomer end-milling has not been discussed. In this paper, the characteristics of the cutting force in elastomer end-milling are evaluated experimentally. A standard cutting force model and its parameter identification method are introduced. By using this cutting force model, measured cutting forces are compared against the calculated results. The comparison makes it clear that the standard cutting force model for metal end-milling can be applied to down milling for a rough evaluation.

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.

Probabilistic Sequential Prediction of Cutting Force Using Kienzle Model in Orthogonal Turning Process

2018 ◽  
Vol 141 (1) ◽  
Author(s):  
M. Salehi ◽  
T. L. Schmitz ◽  
R. Copenhaver ◽  
R. Haas ◽  
J. Ovtcharova
Keyword(s):  
Bayesian Inference ◽  
Cutting Force ◽  
Rake Angle ◽  
Model Verification ◽  
Force Model ◽  
Cutting Force Prediction ◽  
Force Prediction ◽  
Prior Probabilities ◽  
Orthogonal Turning ◽  
Sequential Prediction

Probabilistic sequential prediction of cutting forces is performed applying Bayesian inference to Kienzle force model. The model uncertainties are quantified using the Metropolis algorithm of the Markov chain Monte Carlo (MCMC) approach. Prior probabilities are established and posteriors of the models parameters and force predictions are completed using the results of orthogonal turning experiments. Two types of tools with chamfer (rake) angles of 0 deg and −10 deg are tested under various cutting speed and feed per revolution values. First, Bayesian inference is applied to two force models, Merchant and Kienzle, to investigate the cutting force prediction at the low feed values for the 0 deg rake angle tool. Second, the results of the posteriors of the Kienzle model parameters are used as prior probabilities of the −10 deg rake angle tool. The simulation results of the 0 deg and −10 deg tool rake angle are compared with the experiments which are obtained under other cutting conditions for model verification. Maximum prediction errors of 7% and 9% are reported for the tangential and feed forces, respectively. This indicates a good capability of the Bayesian inference for model parameter identification and cutting force prediction considering the inherent uncertainty and minimum input experimental data.

Real-Time Cutting Force Prediction and Cutting Force Coefficient Determination during Machining Processes

2011 ◽  
Vol 223 ◽  
pp. 85-92 ◽  
Author(s):  
Balázs Tukora ◽  
Tibor Szalay
Keyword(s):  
Cutting Force ◽  
Real Time ◽  
Cutting Forces ◽  
End Milling ◽  
Orthogonal Cutting ◽  
Machining Process ◽  
Work Piece ◽  
Processing Unit ◽  
Cutting Force Prediction ◽  
Force Prediction

In this paper a new method for instantaneous cutting force prediction is presented, in case of sculptured surface milling. The method is executed in a highly parallel manner by the general purpose graphics processing unit (GPGPU). As opposed to the accustomed way, the geometric information of the work piece-cutter touching area is gained directly from the multi-dexel representation of the work-piece, which lets us compute the forces in real-time. Furthermore a new procedure is introduced for the determination of the cutting force coefficients on the basis of measured instantaneous or average orthogonal cutting forces. This method can determine the shear and ploughing coefficients even while the cutting geometry is continuously altering, e.g. in the course of multi-axis machining. In this way the cutting forces can be predicted during the machining process without a priori knowledge of the coefficients. The proposed methods are detailed and verified in case of ball-end milling, but the model also enables the applying of general-end cutters.

scholarly journals Cutting Force Transition Model Considering the Influence of Tool System by Using Standard Test Table

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1340
Author(s):  
Xi Chen ◽  
Dinghua Zhang ◽  
Qi Wang
Keyword(s):  
Prediction Model ◽  
Cutting Force ◽  
Orthogonal Cutting ◽  
Cutting Force Prediction ◽  
Actual Measurement ◽  
Tool Vibration ◽  
Force Prediction ◽  
Conversion Model ◽  
Proposed Model ◽  
The Impact

The cutting force prediction model usually uses the classical oblique transformation method, which introduces the orthogonal cutting parameters into the oblique milling edge shape, and combines the geometric parameters of the tool to convert the orthogonal cutting force into the actual cutting force, thereby predicting the cutting force. However, this cutting force prediction method ignores the impact of tool vibration in actual machining, resulting in a large difference between the prediction model and the actual measurement. This paper proposes a cutting force conversion model considering the influence of the tool system. The proposed model fully considers the impact of tool vibration on the cutting force. On the basis of the orthogonal model, superimposing the additional cutting force generated by tool vibration makes the predicted value of the model closer to the actual cutting force. The results of milling experiments show that the conversion model can obtain higher prediction accuracy. Moreover, compared with the original conversion model, the accuracy of the proposed model is significantly improved.

A novel mechanics model of parametric helical-end mills for 3D cutting force prediction

2011 ◽  
Vol 225 (7) ◽  
pp. 1693-1702 ◽  
Author(s):  
W Yongqing ◽  
L Haibo
Keyword(s):  
Shear Stress ◽  
Cutting Force ◽  
Phase Angle ◽  
Manufacturing Systems ◽  
Cutting Edge ◽  
Cutting Force Prediction ◽  
Average Deviation ◽  
Force Prediction ◽  
Mechanics Model ◽  
End Mills

Cutting force prediction plays an important role in modern manufacturing systems to effectively design cutters, fixtures, and machine tools. A novel mechanics model of parametric helical-end mills is systematically presented for three-dimensional (3D) cutting force prediction in the article, which is different from mechanistic approach and Oxley’s predictive machining theory in model formulation and shear stress identification process. The single-flute cutting edge and multiflute cutting edge of helical-end mills are modelled according to kinematic analysis with vector algebra. Based on Merchant’s oblique cutting theory, a new mechanics model of 3D cutting force with runout has been developed. Meanwhile, the asynchronous problem between predicted and measured curves is solved by adjusting phase angle to minimize the average deviation. After minimizing the asynchronous phase angle deviation, shear stress can be estimated directly using corresponding peak-to-peak ratio or valley-to-valley ratio of the predicted curves and the measured curves in X- and Y-directions of an arbitrary selected milling test. To assess the feasibility of the general model, over 100 milling experiments of aluminium alloy (7075) using flat-end mills and ball-end mills were conducted, respectively, and numerical tests implemented in time domain on MathWorks platform. The comparative results indicated that the predicted and the measured waveforms were quite satisfied in both pulsation pattern and period.

scholarly journals Cutting Force in Milling of Additive Manufacturing AISI 420 Stainless Steel

2021 ◽  
Author(s):  
Shoichi Tamura ◽  
Takashi Matsumura
Keyword(s):  
Stainless Steel ◽  
Additive Manufacturing ◽  
Cutting Force ◽  
Cutting Forces ◽  
Orthogonal Cutting ◽  
Force Model ◽  
Additive Process ◽  
Aisi 420 ◽  
Chip Flow ◽  
Cutting Model

In manufacturing, hybrid systems of metal additive manufacturing and cutting in the same platform have been attractive in terms of low volume production of customized parts, complex shape, and fine surface finish. Milling is conducted to finish rough surface fabricated in additive process. The fundamental machinability of the additive workpiece should be studied because the material properties are different from metals produced in the conventional process. The paper discusses the cutting forces in milling of AISI 420 stainless steel fabricated in additive process. The cutting tests were conducted to measure the cutting forces and the chip morphologies for tool geometries. The cutting forces were also analyzed in an energy-based force model. In the analysis model, three-dimensional chip flow is interpreted as a piling up of orthogonal cuttings in the planes containing the cutting velocities and the chip flow velocities, where the cutting model is made by the orthogonal cutting data acquired in cutting tests. The chip flow direction is determined to minimize the cutting energy. The cutting forces, then, were predicted in the determined chip flow model. The cutting force model was validated in comparison of simulated forces with the actual ones.

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