Cutting Force Prediction Model Research Articles

Effects of Machining Parameters on Cutting Force of Endmilling of Inconel 718 Using Wavy-Edge Bull-Nose Helical End-Mill under Minimum Quantity Lubrication

This paper investigates effects of machining parameters: cutting speed (CS), feedrate (FR), and axial depth of cut (DC), on cutting force of endmilling of Inconel 718. A Wavy-edge bull-nose helical endmill (WEBNHE) was simulated cutting this material, at different levels of these parameters, then the maximum values of cutting force components (FxMax, FyMax, FzMax), as well as the resultant (FMax) were predicted using a mechanistic cutting force prediction model developed and cited from references [1-3]. The mechanistic model predicts the cutting force based on instantaneous cross-sectional area of the chip, and the local differential cutting-edge length, whereas minimum quantity lubrication (MQL) cooling strategy was incorporated into the mechanistic model via experimentally-identified cutting force and edge force coefficients which were identified and cited from the reference [4]. The simulated experimental runs in this research were designed based on Full-factorial principle, whereas MATLAB was used to simulate the mechanistic model and predict the cutting forces. The resultes showed that depth of cut contributed the most (by 78.94%) on the predicted resultant force (FMax), Followed by Feedrate, which contributed by 20.56%, and last was the cutting speed which contributed only by7.13%. Resultes also showned that, increasing feedrate and depth of cut resulted in increasing the three cutting force components and the resultant, Whereas increasing the cutting speed resulted in decreasing the FxMax and FyMax, but increasing the FzMax. Furthemore, by focusing on the axial force component (FzMax), it was observed that the effect of cutting speed was completelly reversed when the feedrate reached 41 mm/min and depth of cut reched 25 mm. At these conditions, cutting speed 93 produced more FzMax than 62. This can be justified by the wavy-cutting edge affecting cutting force direction

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

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.

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

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.

Cutting Force Modeling and Experimental Study for Ball-End Milling of 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.

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

Accurate cutting force prediction serves as an important reference to the optimization of numerically controlled machining process. Traditional cutting force modeling via theoretical cutting mechanism hampers accurate prediction for actual machining process due to its highly suppressed modeling flexibility. On the other hand, machine learning based modeling approaches demand large amount of diversified labeled samples to achieve comparable prediction results, while collecting these samples can be tedious and costly because the cutter workpiece engagement (CWE) keeps changing during actual process. This paper presents a cutting force prediction model, named ForceNet, which incorporates elementary physical priori into structured neural networks to predict cutting force for end-milling process of complex CWE. The main idea is to use grayscale images to represent CWE geometry, providing a universal input to the ForceNet. Unlike traditional deep neural networks served as an unexplainable black box, the core of the ForceNet is constructed by the vector summation of directional primitive cutting force elements, which are approximated using elementary neural networks. Preliminary results indicate that ForceNet outperformed existing methods not only with greater prediction accuracy in unseen cutting situations, but also with less training data needed thanks to its inherent neuro-physical structure.

Modeling of cutting forces in helical milling of unidirectional CFRP considering carbon fiber fracture

Helical milling is applied to the machining of CFRP owing to its favorable characteristics such as low cutting forces and heat generation. However, the prediction of helical milling forces remains a problem in CFRP processing. In this study, a novel predictive cutting force model of helical milling for unidirectional CFRP was established. Based on the cutting parameters, the dynamic cutting angle for the fiber and the corresponding cutting states of the fiber during the cutting process were analyzed, and the number and length of cutting edges involved in cutting were calculated. Then, the cutting forces on the cutting-edge micro-element of the periphery edge and bottom cutting edge under two different cutting states were calculated by treating the fiber as an equivalent homogeneous material. The cutting force prediction model was obtained by taking this into consideration. Finally, the helical milling experiment for unidirectional CFRP was carried out. The results show that the model can effectively predict the cutting force. • A new prediction cutting force model of Helical milling for unidirectional CFRP was established. • The model is based on the fracture mode of carbon fiber and cutting edges micro-element cutting force.

Modified cutting force prediction model considering the true trajectory of cutting edge and in-process workpiece geometry in ball-end milling operation

Cutting force prediction is very important for optimizing machining parameters ahead of the costly physical test. Ball-end milling operation is widely used for machining sculptured surface. Mechanistic approach can precisely predict elemental cutting force at each cutting element and integrate them into the cutter tooth with high fidelity to predict the cutting force for ball-end milling operation. However, the intersection between the cutting tool and workpiece could be complicated due to the trochoid motion trajectory of cutting edge and constantly changing workpiece geometry, making it difficult to determine the cutter-workpiece engagement (CWE) and undeformed chip thickness (UCT). In this present research, a modified cutting force prediction model was developed with considering the true trajectory of cutting edge and in-process workpiece geometry in ball-end milling operation. First, a triangular mesh model of the in-process workpiece surface was developed, and its mesh points were continuously updated by the intersection between the vertical reference line of the selected mesh point and the motion trajectory of cutting edge. Secondly, the UCT was calculated directly using the linear distance between a selected point on the cutting edge and the intersection between the radial reference line of the selected point and the triangular mesh of the in-process workpiece surface. Meanwhile, the CWE was expressed as a step function of UCT. Thirdly, a modified mechanistic approach was established by incorporation into the developed UCT and CWE models. The cutting force of ball-end milling operation was predicted with mechanistic approaches. Finally, ball-end milling experiments of AISI P20 steel were carried out for calibrating cutting force coefficients and validating cutting force model. The relative error between the predicted and measured cutting force is less than 15%, which indicates the predicted cutting force is in good agreement with measured cutting force. The works presented in this paper are one important step for optimizing machining parameters and compensating cutting force induced form error, which could improve the surface accuracy and machining efficiency.

A cutting force prediction model in axial ultrasonic vibration end grinding for BK7 optical glass considering protrusion height of abrasive grits

Axial ultrasonic vibration end grinding (AUVEG) has been recognized as an efficient machining method for hard and brittle materials. In this paper, a theoretical model was proposed for predicting cutting force in AUVEG of BK7 optical glass with consideration of the nonuniform protrusion height of abrasive grits. Since the protrusion height of diamond grits was closely related to the cutting force, the modelling of the wheel end-face morphologies was performed to obtain the protrusion height information of diamond grits. Based on indention theory combined with energy perspective, a material removal rate model was proposed for establishing the cutting force model. Experiments were conducted to verify the validity of the proposed model, and the mean error between predicted and experimental force is 4.94%. The proposed model could be used in selecting process parameters for realizing high efficiency and precision AUVEG machining of BK7 optical glass.

Modeling of Cutting Force in the Turning of AISI 4340 Using Gaussian Process Regression Algorithm

Machining process data can be utilized to predict cutting force and optimize process parameters. Cutting force is an essential parameter that has a significant impact on the metal turning process. In this study, a cutting force prediction model for turning AISI 4340 alloy steel was developed using Gaussian process regression (GPR), support vector machines (SVM), and artificial neural network (ANN) methods. The GPR simulations demonstrated a reliable prediction of surface roughness for the dry turning method with R2 = 0.9843, MAPE = 5.12%, and RMSE = 1.86%. Performance comparisons between GPR, SVM, and ANN show that GPR is an effective method that can ensure high predictive accuracy of the cutting force in the turning of AISI 4340.

Prediction of sand mold cutting force and identification of cutting force coefficients

Patternless casting technology is an advanced digital forming technology. Sand mold cutting is one of the most important techniques of patternless casting technology. In the process of sand mold cutting, the cutting force is the key factor affecting the quality of sand mold machining, and is an important prerequisite for the optimization of cutting parameters and the study of cutting stability. The accuracy of the cutting force prediction model depends largely on the identification of the cutting force coefficient. In the average cutting force model, the cutting force coefficient is considered as a constant. For identification of sand mold cutting force coefficient, a series of resin sand cutting experiments have been conducted in this paper, fixing spindle speed and depth of cutting, linearly changing the feed per tooth to measure the cutting forces, the tangential and radial cutting force coefficient are calculated by linearly fitting experimental data. The analysis results show that with the change of the cutting parameters the resin sand cutting force coefficient is basically the same.

Cutting force modeling in orthogonal cutting of UD-CFRP considering the variable thickness of uncut material

The application of the carbon fiber–reinforced polymer (CFRP) becomes increasing in aerospace. In this paper, based on the two-parameter elastic foundation model, a representative volume element (RVE) method is used to establish the deflection curve equation of the cutting fiber as the thickness of the uncut material changes. The cutting force prediction model was proposed from the three areas of the chipping area of the rake face, the bounding area of the flank face, and the shearing area of the tool nose. The deformation process of the cutting fiber under different cutting depths was analyzed. The relationship between the uncut material thickness and the fiber deformation length was discussed. The orthogonal cutting experiment of unidirectional carbon fiber–reinforced polymer (UD-CFRP) in the thickness direction was conducted to verify the model. The experimental results show that the relative errors between theoretical and experimental values of the cutting force Fy and Fx are 8.2 and 1%, respectively, when the cutting depth is 0.025 mm. The theoretical cutting force is in good agreement with the experimental cutting force, which proved the accuracy of the fiber deflection curve model. The deflection curve and the debonding length of the cutting fiber changes with the uncut material thickness under different cutting depths of 0.025, 0.05, and 0.075 mm. In addition, it explains the formation of burrs when the thickness of the uncut material is 0.1 mm.

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

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.

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

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.

Research on the cutting dynamics for face-milling of spiral bevel gears

For an efficient and precise machining of spiral gear, the special face-milling process for spiral bevel gear is developed and widely used, exhibiting great difference from the general milling process in cutting machine, cutter and cutting kinematics. The un-deformed chip geometry, cutting force model and regenerating mechanism are hence complexly different, bringing great challenge to the modeling of cutting dynamics. In this regard, no relevant work can be found at present.To overcome this problem, through fully investigating the cutting force regenerating mechanism under complicated cutting kinematics, this paper first develops an analytical cutting force prediction model by classifying the chip geometry into 6 cases, and then a simplified dynamic chip model by assuming the chip geometry cases unchanged and ignoring edge alteration.On such basis, the model for prediction of the cutting dynamics and the chatter stability are developed and validated. Besides, the 3D stability lobe for face-milling of spiral bevel gear is presented and the cutting system tends to be stable with high cutter gear ratio and cutting speed.

A semi-analytical model for cutting force prediction in face-milling of spiral bevel gears

In the machining process, prediction of the cutting force is the key to cutting simulation and optimization. Specially, for the face milling of the spiral bevel gear, the un-deformed chip varies during the process due to the complicated generating kinematics, bringing great challenge to the prediction of cutting force.Regarding this, with a thorough investigation carried out, it is found that the un-deformed chips can be summarized as six cases and described by quadratic polygon interpolation. On such basis, a highly efficient and accurate analytical cutting force prediction model for generated face-milling spiral bevel gear is proposed. Compared to the Boolean operation based method, the proposed method is faster; compared to the chip-simplify method, the method is more precise; and compared to the semi-analytical method, the method is more effective as the chip forming rule is fully considered, which in turn simplifies the operation.Further, the proposed method is validated through both FEM simulation and cutting force experiment with a tolerance within 10%.

Machinability and cutting force modeling of 7055 aluminum alloy with wide temperature range based on dry cutting

The machinability of 7055 aluminum alloy with wide temperature range is examined, with focus on the three cutting forces, surface quality and work hardening of the material under low, medium, and high temperatures. The results demonstrate that, under low temperature, the work hardening depth of 7055 aluminum alloy is almost insensitive to the cutting speed, whereas at a higher cutting speed, the work hardening degree of the material first decreases and then increases; both the work hardening degree and hardening depth are significantly positively correlative to the cutting depth: the work hardening degree is positively correlative, though not so significantly, to the feed rate, while the work hardening depth is insensitive to the feed rate and remains at 100 μm in all cases. Under high temperature, the work hardening degree of 7055 aluminum alloy is positively correlative to the cutting speed; at depths smaller than 80 μm below the machined surface, the work hardening degree is negatively correlative to the cutting depth; at depths larger than 80 μm below the cutting surface, the work hardening degree of the material becomes significantly positively correlative to the cutting depth. A mathematical model of three cutting forces in dry cutting with wide temperature range is established based on wide temperature-range dynamic impact experimental results and the orthogonal cutting model, and modified using the LMSE (least mean square error) principle. The errors between the predicted and experimental three cutting forces, after modification, are all smaller than 10%, which is within the permissible limit of error. This verifies that the modified three cutting force prediction model can predict cutting forces accurately.

Modeling and multi-objective optimization of cutting parameters in the high-speed milling using RSM and improved TLBO algorithm

The main purpose of the present paper is to study the cutting parameter optimization technology by combining the response surface methodology (RSM) with the improved teaching–learning-based optimization (ITLBO) algorithm to obtain the best cutting parameters under multi-objective conditions. Considering the factors of cutting parameters which affect cutting force and surface roughness such as cutting speed, feed per tooth, axial depth of cut, and radial depth of cut, a series of milling experiments are carried out based on four-factor and three-level full factorial experiment design to measurement the cutting force and surface roughness. Based on the collected experimental results, a cubic polynomial regression prediction model for cutting force and surface roughness were established based on the RSM, respectively. Experiments verify that the error of the cutting force prediction model is 0.2–8.04% and 1.36–5.86% for the error of the surface roughness prediction. RSM model is further interfaced with the ITLBO algorithm to optimize the cutting parameters for the multi-objective of cutting force, surface roughness, and processing rate. The optimization experiment results show that cutting force increased by 2.70%, surface roughness decreased by 6.63%, and material removal rate has increased by 49.42%. It indicates that the cutting parameter optimization method based on RSM–ITLBO is effective.

Three-dimensional turning force prediction based on hybrid finite element and predictive machining theory considering edge radius and nose radius

Abstract Cutting force provides a basis for predicting tool wear and fracture, surface quality of component, as well as vibration and power demand of machine tools during the process of turning. Based on the finite element and mechanical analysis model, a three-dimensional (3-D) cutting force prediction model with consideration given to the edge radius and the nose radius of cutting tool is proposed in this paper. Firstly, combined with cutting force experiment, 3-D cutting simulation is performed in Deform to determine the appropriate Johnson-Cook (J-C) material constitutive model, and the two-dimensional (2-D) orthogonal cutting model is simulated by applying the determined J-C model. By observing the strain rate distribution in the shear zone, the shear angle is obtained, while the nonlinear regression model of shear angle, cutting speed and cutting thickness is conducted. Then, taking into account the impact of nose radius on the cutting process, 3-D oblique cutting is converted into equivalent orthogonal cutting using the chip flow angle and the equivalent cutting edge. The method used to determine the strain rate coefficient of the second deformation zone is redefined in the modified Oxley model, and the chip forming force is calculated. Based on the Waldorf slip line field model, the plowing force generated by the edge radius is predicted. Finally, the cutting force of 3-D oblique turning is obtained by means of coordinate transformation. The proposed model is validated by the excellent consistency between the theoretical predictions and the results obtained after referencing literature data and performing experiment of cutting 304 stainless steel and Inconel 718.

Cutting Force Prediction and Experiment Verification of Paper Honeycomb Materials by Ultrasonic Vibration-Assisted Machining

The disc-cutter is a finishing tool for the ultrasonic-cutting of paper honeycomb-core material. The cutting state directly affects the machining accuracy and surface quality of the workpiece. The cutting force is an important physical quantity and the cause of ultrasonic cutting defects of the honeycomb-core material. Due to differences in the mechanical properties and cutting performance of honeycomb-core materials and commonly used metal materials, existing metal-cutting-force models cannot be applied to the calculation of ultrasonic cutting forces in the processing of honeycomb-core materials. In response to this problem—combined with actual working conditions using the ABAQUS finite element analysis software—a finite element simulation model of the ultrasonic vibration-assisted cutting force of the disc-cutter on the honeycomb-core material was established, and the cutting curves and values were obtained. The experiment of ultrasonic vibration cutting of the disc-cutter proves that from the surface morphology of the honeycomb core, the milling-width has the greatest influence on the cutting force, and the cutting-depth has the smallest influence on the cutting force. The maximum error between the cutting force experimental results and the finite element simulation results under the same cutting conditions was 13.2%, which means that the established cutting-force finite element model is more accurate and can be used to predict the cutting in honeycomb ultrasonic vibration-assisted cutting-force value. Finally, based on the response surface method, a three-dimensional cutting force prediction model of the ultrasonic cutting honeycomb core of the disc-cutter was established by using the simulation model data. The results of this study can provide a useful basis for the improvement of cutting performance and processing efficiency in the processing of paper honeycomb-core materials.

A novel analytical modeling for prediction of residual stress induced by thermal-mechanical load during orthogonal machining

Residual stress on the surface and subsurface has a great influence on the distortion and fatigue life. Rapid and accurate prediction of residual stress is important for the optimization of the machining process in intelligent manufacturing. A novel analytical model is proposed based on the equivalent stress method in this paper. The nonlinear flow characteristics of the work-piece material in the tool-work-piece contact surface and thermal-mechanical coupling effect are fully considered. A new cutting force prediction model was established and the relative errors are within 12%, which verifies the accuracy and the effectiveness of the model for further application to residual stress prediction. The thermal-mechanical conditions of the primary shear plane and machined surface are revealed based on the equivalent stress method. Then, internal stress of work-piece is caused by mechanical load and thermal load obtained on account of linear elasticity theory and heat-elastic-plastic mechanics theory. The predicted residual stress profiles have a high degree of consistency with measurement results of orthogonal turning of 20Cr2Ni4A alloy steel. Prediction accuracy of surface residual stresses was 11.3%, 12.2%, and 12.7% for the condition of v = 24 m/min, ap = 0.1 mm; v = 36 m/min, ap = 0.2 mm; v = 48 m/min, ap = 0.3 mm respectively. The predicted results of the maximum compressive stresses and DMCS are also acceptable. Ultimately, the residual stress profiles obtained from proposed model were reliable. The proposed model has high computational efficiency and provides a new idea for the analytical prediction of residual stress. And the proposed model can be used for further residual stress analysis and prediction of 3D cutting process.