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.

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.

scholarly journals Accurate Modeling of Working Normal Rake Angles and Working Inclination Angles of Active Cutting Edges and Application in Cutting Force Prediction

Micromachines ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1207
Author(s):  
Peng Li ◽  
Zhiyong Chang
Keyword(s):  
Cutting Force ◽  
High Performance ◽  
Cutting Parameters ◽  
Rake Angle ◽  
Cutting Edge ◽  
Cutting Force Prediction ◽  
Force Prediction ◽  
Inclination Angles ◽  
Cutting Velocity ◽  
Differential Element

The normal Rake angle is an important geometric parameter of a turning tool, and it directly affects the accuracy of the cutting force prediction. In this study, an accurate model of the working normal rake angle (WNRA) and working inclination angle (WIA) is presented, including variation in the cutting velocity direction. The active cutting edge of the turning tool is discretized into differential elements. Based on the geometric size of the workpiece and the position of the differential elements, the cutting velocity direction of each differential element is calculated, and analytical expressions for the WNRA, WIA, and working side cutting edge angle are obtained for each differential element. The size of the workpiece is found to exert an effect on the WNRA and WIA of the turning tool. The WNRA and WIA are used to predict the cutting force. A good agreement between the predicted and experimental results from a series of turning experiments on GH4169 with different cutting parameters (cutting depth and feed rate) demonstrates that the proposed model is accurate and effective. This research provides theoretical guidelines for high-performance machining.

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 Cutting Force Prediction Models by FEA and RSM When Machining X56 Steel with Single Diamond Grit

Micromachines ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 326
Author(s):  
Lan Zhang ◽  
Xianbin Sha ◽  
Ming Liu ◽  
Liquan Wang ◽  
Yongyin Pang
Keyword(s):  
Cutting Force ◽  
Coefficient Of Friction ◽  
High Speed ◽  
Prediction Models ◽  
Pipeline Steel ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Cutting Force Prediction ◽  
Force Prediction ◽  
Diamond Wire Saw

In the field of underwater emergency maintenance, submarine pipeline cutting is generally performed by a diamond wire saw. The process, in essence, involves diamond grits distributed on the surface of the beads cutting X56 pipeline steel bit by bit at high speed. To find the effect of the different parameters (cutting speed, coefficient of friction and depth of cut) on cutting force, the finite element (FEA) method and response surface method (RSM) were adopted to obtain cutting force prediction models. The former was based on 64 simulations; the latter was designed according to DoE (Design of Experiments). Confirmation experiments were executed to validate the regression models. The results indicate that most of the prediction errors were within 10%, which were acceptable in engineering. Based on variance analyses of the RSM models, it could be concluded that the depth of the cut played the most important role in determining the cutting force and coefficient the of friction was less influential. Despite making little direct contribution to the cutting force, the cutting speed is not supposed to be high for reducing the coefficient of friction. The cutting force models are instructive in manufacturing the diamond beads by determining the protrusion height of the diamond grits and the future planning of the cutting parameters.

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