Cutting Force Model Research Articles

An Analytical and Experimental Study on Cutting Characteristics and Transient Cutting Force Modeling in Feed Directional Ultrasonic Vibration-Assisted Cutting of High Strength Alloys.

Ultrasonic vibration-assisted cutting (UVC) is progressively being used in machining as it can significantly promote the fabrication process. However, the ultrasonic vibration affecting the cutting process is still controversial. The full-transient cutting process is proposed in this study to analyze the affecting mechanism induced by ultrasonic vibration in the cutting process. This novel model is the first developed based on the fact that ultrasonic vibration would change mechanical behaviors and the cutting process. For example, the reduction of shear flowing stress in the primary shear zone and alteration of the shear angle in the UVC process. Then, considering those coupled effects, a novel model is proposed to determine the average and transient cutting forces. Here, insight and understanding into the physical phenomenon in UVC are provided. The effectiveness of the proposed model is verified by comparison with experimental results and analytical models available in the literature, with cutting parameters varying from macro to micro-scale. The results show that the ultrasonic vibration affects the cutting process in a complicated way, which is determined by transient characteristics, acoustic softening, thermal softening, plowing, and friction. Those effects on cutting performances in the UVC process under various cutting scenarios are investigated and discussed systematically. The average deviation of cutting forces between experiments and values predicted by the proposed model for Ti6Al4V, AISI 1045, and Al6063 is about 7%, 10.2%, and 11%, respectively. The deviation decreases with the increase of cutting speed in the machining of Ti6Al4V, which is different from the machining of other materials. This is contributed by the varied effect of ultrasonic vibration on the cutting process.

Modeling of cutting force and final thickness for low stiffness 2024-T3 aluminum alloy part milling considering its geometry and fixtures

The aeronautic industry is facing many challenges regarding the lifetime, weight and accuracy that aircraft skins must comply to meet stringent structural and aerodynamic requirements. Currently, mechanical milling of aircraft skin parts of 2024-T3 aluminum alloy is displacing the highly pollutant chemical milling. Consequently, flexible and reconfigurable vacuum holding fixtures are being increasingly employed, because they are adaptable to several part geometries, but, since their rigidity is extremely reduced, the low stiffness of parts limits severely their deployment. Aiming to harness the full potential of these holding systems for aluminum alloy skin parts, a complete analysis of final thickness achieved and cutting force is developed. Thin floor parts of different geometries are pocket milled, simply screwed at their corners, emulating a skin part supported by four vacuum cups. Process forces are continuously monitored, and final thickness is measured. It has been proven that the reduction of mass and stiffness during milling causes a corresponding reduction of the natural frequencies of the parts. Also, as long as natural frequencies are not excited, final thickness error is almost constant and not affected by the tool position, but only by the initial geometry and fixtures distribution of the part. Additionally, a new cutting force model for skin parts is empirically calculated. Unlike models designed for fully supported parts, this model is designed for skins held in flexible fixtures. It has a relative error of 5.6% and it allows to optimize the trajectory, geometry and support distribution, thus boosting the use of flexible fixtures.

A hybrid model for turning force based on shear and extrusion deformation considering cutting-edge radius

Turning is a machining process widely used in many industries, such as aviation, aerospace, and optics. The existing turning force model considers the shear deformation and ploughing effect between the tool flank and machined surface of the workpiece while often ignoring the effect of the cutting-edge radius (CER) on the cutting process. Thus, it cannot comprehensively capture the cutting force in the turning process. In this study, the formation mechanism of the turning force is investigated considering the material-deformation mechanism during the turning process, and the effect of CER on the turning force is discussed herein. Further, a method to determine the boundaries of the undeformed chip region is proposed using a three-dimensional geometric model. The extrusion deformation is simulated considering the CER geometry and a three-item cutting-force model for shear–extrusion–ploughing established. Further, an analytical method to calculate the singular position is proposed. The validity of the proposed model is verified experimentally. The proposed model can be used as a guideline to aid further research on the surface integrity of turning-machined parts.

Mechanistic force model for double-phased high-feed mills

Being able to predict cutting forces, torque and power in machining applications allows to check their influence on the quality of the product, to assess the feasibility of the process and to compare different operations for sustainability purposes. In this paper, the analytical development of a mechanistic model for cutting forces prediction for high-feed mills is carried out. High-feed cutters are featured by extremely low lead angles, leading to a gradual engagement of the cutter inside the workpiece. This fact prevents the mechanistic literature formulation to accurately compute the undeformed instantaneous chip section of each cutter, and thus to correctly predict the spindle torque and power. A closed analytical formulation for the mechanistic cutting force model, including an improved chip thickness formulation with variable entry and exit angles and double-phased cutter geometry, is presented. Experimental cutting tests using double-phased high-feed mills were carried out on Ti6Al4V with variable feed rate per tooth, cutting speed and axial depth of cut. The model was assessed by comparing the performances of the literature model and the developed high-feed one in the identification of specific force coefficients — SFC. The identified SFC resulted to belong to two statistically different populations. SFC 95% confidence intervals were found to be significantly narrower with respect to the literature ones. Kt,c 95% confidence intervals were equal to (1085; 1426) MPa and (970; 2423) MPa for the proposed and literature model, respectively. The validity of the proposed model was assessed in terms of mean forces, mean spindle torque and mean spindle power prediction capabilities. The Root Mean Squared Prediction Error for the proposed model resulted to be remarkably lower (15 N, 0.33 Nm, 29 W) with respect to literature model (41 N, 1.25 Nm, 120 W).

Comprehensive Study on the Cutting Force Modeling and Machinability of High Frequency Electrical Discharge Assisted Milling Process Using a Novel Tool

Comprehensive Study on the Cutting Force Modeling and Machinability of High Frequency Electrical Discharge Assisted Milling Process Using a Novel Tool

Study of the surgical needle and biological soft tissue interaction phenomenon during insertion process for medical application: A Survey.

The insertion of the surgical needle in soft tissue has involved significant interest in the current time because of its purpose in minimally invasive surgery (MIS) and percutaneous events like biopsies, PCNL, and brachytherapy. This study represents a review of the existing condition of investigation on insertion of a surgical needle in biological living soft tissue material. As observes the issue from numerous phases, like, analysis of the cutting forces modeling (insertion), tissue material deformation, analysis of the needle deflection for the period of the needle insertion, and the robot-controlled insertion procedures. All analysis confirms that the total needle insertion force is the total of dissimilar forces spread sideways the shaft of the insertion needle for example cutting force, stiffness force, and frictional force. Various investigations have analyzed all these kinds of forces during the needle insertion process. The force data in several measures are applied for recognizing the biological tissue materials as the needle is penetrated or for path planning. The deflection of the needle during insertion and tissue material deformation is the main trouble for defined needle placing and efforts have been prepared to model them. Applying existing models numerous insertion methods are established that are discussed in this review.

A transient cutting temperature prediction model for high-speed ultrasonic vibration turning

As a precision machining method, ultrasonic vibration cutting is widely applied for cutting difficult-to-machine materials due to the phenomena of cutting force and the decrease of cutting temperature when coolant is applied. However, the cutting efficiency is limited due to the existence of critical cutting speed of ultrasonic vibration cutting. Therefore, a high-speed ultrasonic vibration cutting (HUVC) method is proposed to realize high-efficiency machining with tool life prolongation and surface quality improvement. The key issue of these advantages is the decrease of cutting temperature within the cutting interfaces. Therefore, it is necessary to figure out the temperature decrease principles when ultrasonic vibration is added. In this paper, a transient cutting temperature prediction model is built to further investigate the mechanism of HUVC. In spite of the average cutting temperature, this model is mainly focused on the transient process. Firstly, the kinematics of HUVC is analyzed, based on which a cutting force model is built. Then, cutting heat is divided into heat generation in cutting duration and heat transfer in noncutting duration, which are then calculated respectively. After calculating the transient cutting heat, cutting temperature in the cutting interfaces is calculated through numeric iteration and integration in the time and space domain. At last, the accuracy of the proposed model is validated by measuring the average cutting temperature through a self-developed tool-workpiece thermocouple. The results demonstrate that the maximum error of this model is no larger than 14 %. Both cutting speed and duty cycle are key factors influencing the increase of cutting temperature in cutting duration and the decrease of it in noncutting duration. In this regard, this model is significant for cutting and vibration parameter setup to obtain an optimal tool life in high-speed machining by restraining the heat generation and enlarging the heat decrease.

Effective Optimization Based on Equilibrium Optimizer for Dynamic Cutting Force Coefficients of the End-Milling Process

This study aims to develop an accurate dynamic cutting force model in the milling process. In the proposed model, the estimated cutting force tackles the effect of the self-excited vibration that causes machining instability during the cutting process. In particular, the square root of the residual cutting force between the prediction and the actual cutting force is considered as an objective function for optimizing the cutting force coefficients using the equilibrium optimizer (EO) approach instead of the trial-and-error approach. The results confirm that the proposed model can provide higher prediction accuracy when the EO is applied. In addition, the proposed EO has a minimum integral square error (ISE) of around 1.12, while the genetic algorithm (GA) has an ISE of around 1.14 and the trial-and-error method has an ISE of around 2.4. Moreover, the proposed method can help to investigate the cutting stability and to suspend the chatter phenomenon by selecting an optimal set of cutting parameters.

The effect of interstitial fluid on the machining behaviour of cortical bone

Bone machining research is usually conducted ex-vivo with standard laboratory equipment, implying mostly that the cutting process takes place in dry state. While these studies are useful for understanding the bone cutting process, they cannot represent the real clinical cutting condition due to the disregard of internal irrigation (i.e., interstitial fluid and blood within the tissue’s vascular porosities). As bone possesses ca. 20 % water, internal irrigation can influence the bone’s properties (e.g., shear strength, friction coefficient) and alter the cutting mechanism and surface deformation (e.g., crack formation, smearing). Hence, to study the ex-vivo bone cutting process in an internally irrigated state, a novel machining and pumping setup is proposed here, which enables a scenario closer to a surgical condition than the traditional dry machining method. Cutting tests demonstrated that portions of bone near the fluid-filled porosities possess shear strength and friction coefficient gradients due to the bone’s permeability. This resulted in machining forces and necrosis up to 52 % and 55 % lower than in dry bone, respectively. A cutting forces model was developed considering the internal irrigation condition and the randomness and anisotropy of the tissue. Moreover, it was found that internal irrigation can change the chip formation mechanism and induce minimised surface morphological damage due to the minimised friction between the tool and the cutting surface in near-porosity sites. This research highlights the importance of conducting bone machining research with the consideration of internal irrigation, an imperative aspect to more realistically mimic surgical scenarios in a laboratory environment.

A new dynamic boring force calculation method using the analytical model of time-varying toolpath and chip fracture

The accurate prediction of dynamic cutting force has great significance for the quality control of the boring process for deep-cavity thin-walled parts. However, most of the classic and improved cutting force models commonly neglect the mechanism analysis of dynamic cutting force, resulting in the dynamic prediction of cutting force being almost impossible. To resolve this problem, a novel analytical dynamic cutting force prediction model for the boring process was proposed to consider the time-varying toolpath and chip fracture in the machining process. The generation mechanism of dynamic cutting force was analyzed by cutting theory and mathematical formula. The theory of maximum shear stress and the law of conservation of energy were applied to derive the dynamic cutting force for an entire rotation cutting cycle. Then, the proposed dynamic cutting force model was validated using a designed boring experiment and a classical cutting force model. The compared results showed that the dynamic cutting force model based on the proposed method had good agreement with the experimental data. Meanwhile, the advantage of accurate prediction was also further demonstrated by comparing the classic cutting force model. This paper presents an analytical dynamic cutting force prediction model for the boring process considering the toolpath and chip breakage. The underlying mechanism of the dynamic change of the cutting force was studied, and data supporting the improved quality of boring deep-cavity thin-walled parts was provided.

Orthogonal Cutting Force Modeling Using the Nonequipartition Parallel Shear-Zone Distribution Model

This paper proposed a modified Oxley’s model using the nonequipartition parallel shear-zone theory. By introducing a strain and strain rate distribution model in the first shear band, the assumption that primary deformation zone was divided equally by the main shear plane was eliminated. Then the expressions of shear-zone thickness and resultant angle were derived according to Oxley’s cutting theory. Finally, a force prediction model for orthogonal cutting was established by analyzing the mechanical-thermal characteristics in the deformation zone. The thin-walled cylinder made of AISI 304 was used to carry out the orthogonal turning experiment. A variety of cutting force prediction models were used to compare with the experimental results. The calculation results from the proposed model show that the prediction accuracy of cutting force in both cutting and feed directions is improved.

Evaluation of automated stability testing in machining through closed-loop control and Bayesian machine learning

This paper describes a system for automated identification of the optimal stable cutting parameters in milling through Bayesian machine learning and closed-loop control. The closed-loop control system consists of a process monitoring architecture, an analysis framework, and a feedback mechanism. The analysis framework consists of a Bayesian machine learning algorithm that learns a stability map given test results. The learned stability map is used to select parameters for stability testing using an expected improvement in the material removal rate criterion. The test parameters are communicated to the machine controller to complete the test cut through a feedback mechanism. The test cuts were monitored using an audio signal; the stability of the test cut was determined by analyzing the frequency content of the audio signal. The test result was fed back to the Bayesian learning algorithm to complete the loop. Experimental results demonstrate that the system can identify the optimal stable parameters without information about the cutting force model or the structural dynamics. The system provides a low-cost method for optimal stable parameter identification in an industrial environment.

A comparative study of force models in monitoring the flank wear using the cutting force coefficients

Difficult-to-machine materials, such as nickel-based alloys, are widely utilized in aerospace industry, while their low thermal conductivity and high temperature strength lead to the rapid wear of cutting tool. Tool wear monitoring is regarded as one of the useful methods to guarantee the product quality and maximize the tool utilization. Due to the high nonlinearity and stochastic characteristics of tool wear process, it is difficult to establish a general tool wear monitoring model. This work contributes to find out the most suitable cutting force model by comparing their ability and performance in monitoring the flank wear. The tool wear monitoring is realized through developing the relationship between cutting force coefficients and tool wear, and the coefficients are calculated based on the average cutting forces in different feed rates. Then, correlational analysis is performed to select sensitive coefficients. Finally, the selected coefficients are normalized and then trained by the feed-forward backprop neural network. Experiments are conducted to compare the four different models in cutting force prediction and tool wear monitoring by three criteria. The cutting force model including the shearing forces, the edge forces, and forces due to the tool wear gives the best results. The obtained results also show great suitability for different cutting conditions.

Instantaneous cutting force model considering the material structural characteristics and dynamic variations in the entry and exit angles during end milling of the aluminum honeycomb core

The structural characteristics of the material and dynamic changes in the entry and exit angles are of great significance for the accurate prediction of the cutting force during milling of the aluminum honeycomb core. In this study, an instantaneous cutting force prediction model for the aluminum honeycomb core that comprehensively considers the porous structural characteristics of the material and dynamic changes in the entry and exit angles during the machining process was developed. A unified structural model for an aluminum honeycomb core with a regular hexagonal cell structure and excellent mechanical property was established. Based on the structural characteristics of the aluminum honeycomb core, three types of thin-walled edges were considered, and the dynamic changes in their entry and exit angles were investigated by considering the cutter radius, cutting width, honeycomb core wall thickness, and relative position between the cutter and thin-walled edge. An orthogonal-to-oblique cutting transformation approach that can effectively reflect the cutting characteristics of the material was adopted to calibrate the cutting force coefficients in which cutting experiments using different cutter geometries and parameters were conducted. The aluminum honeycomb core was fixed using green, high-efficiency cryogenic liquid nitrogen. To verify the reliability of the proposed model, a series of milling experiments were carried out and the experimental and simulation results were compared. It was found that the simulated cutting force is highly consistent with the experimental result. The proposed model can accurately predict the peak values of the cutting force in the x, y, and z directions, with an average prediction error of less than 10%.

Crystal orientation and material type related suppression to the graphitization wear of micro diamond tool

According to the Hencky stress theorem and J-C constitutive equation, a cutting force model is established for the diamond turning process when using micro diamond tool, through which the stress distributions on tool rake face and flank face are calculated. A stress model is further developed to calculate the stress distribution on the cutting edge region by using the stress intensity factor theory of fracture mechanics, into which the influences of crystal orientation of rake and flank faces are integrated. With consideration of elastic modulus and defect density of diamond crystal, the critical stress for graphitization of diamond tool is also deduced in response to different crystal orientations and types of diamond material. Finally, cutting experiments are performed to validate the theoretical predictions. Results show that the experimental observations agree well with the theoretical predictions. Such satisfactory consistency confirms that the natural cape Ia diamond as tool material and the (100) crystal plane as tool faces can effectively inhibit the graphitization wear of micro diamond tool.

Micro-Milling Tool Wear Monitoring via Nonlinear Cutting Force Model.

Mechanistic cutting force model has the potential for monitoring micro-milling tool wear. However, the existing studies mainly consider the linear cutting force model, and they are incompetent to monitor the micro-milling tool wear which has a significant nonlinear effect on the cutting force due to the cutting-edge radius size effect. In this study, a nonlinear mechanistic cutting force model considering the comprehensive effect of cutting-edge radius and tool wear on the micro-milling force is constructed for micro-milling tool wear monitoring. A stepwise offline optimization approach is proposed to estimate the multiple parameters of the model. By minimizing the gap between the theoretical force expressed by the nonlinear model and the force measured in real-time, the tool wear condition is online monitored. Experiments show that, compared with the linear model, the nonlinear model has significantly improved cutting force prediction accuracy and tool wear monitoring accuracy.

Drilling process of Cf/SiC ceramic matrix composites: Cutting force modeling, machining quality and PCD tool wear analysis

Cf/SiC composites are continuous fiber-reinforced ceramic matrix composites with excellent properties, such as high-temperature resistance, high specific strength, and low coefficient of thermal expansion. However, Cf/SiC composites often cause severe tool wear and quality problems. In this paper, tool wear is studied during the machining of Cf/SiC materials. The cutting force model is applied to understand the correlation between cutting force and tool wear. Polycrystalline Diamond (PCD) tools with various point and clearance angles are designed to carry out drilling experiments on Cf/SiC composites with different machining parameters. During experimental investigations, force and acoustic emission signals are analyzed, and PCD tool wear and material machining quality are observed using scanning electron microscopy. Results indicate that PCD tools with a point angle of 140° and a clearance angle of 20° demonstrate the lowest tool wear during machining. Moreover, low-speed and feed machining parameters can effectively reduce tool wear and prolong its life. By observing fracture patterns of hole wall fibers and chip shapes at different stages of tool wear, and combined with the frequency domain distribution of AE signal, the effects of tool wear on the material removal mechanism are summarized. Before tool wear, fiber fracture is flatter, the matrix is mainly removed via crushing. After tool wear, although fiber fracture is more uneven, the matrix is changed from crushing to friction removal, leading to lower surface roughness of the hole wall.

Improved Cutting Force Modelling in Micro-Milling Aluminum Alloy LF 21 Considering Tool Wear

Aluminum alloy LF 21 has a strong ability to reflect electromagnetic waves. LF 21 waveguide slit array structure is widely used in waveguide radar antenna. The stiffness of the slit array structure is relatively weak. So, the structure is prone to deformation under the cutting force in the conventional milling process. Micro-milling technology can realize high-precision machining of mesoscale parts/structures and is a potential effective machining technology for the waveguide slit array structure. However, the diameter of the micro-milling cutter is small, and the feed per tooth is comparable to the arc radius of the cutting edge, so the micro-milling cutter is prone to wear. In addition, the effects of elastic recovery of material, the minimum cutting thickness and friction of cutting dead zone on micro-milling force cannot be ignored. A simulation model of micro-milling aluminum alloy LF 21 processes based on DEFORM 3D is built by combining the theory of cutting and the technology of process simulation. Prediction of tool wear is achieved. The quantitative relationship between the arc radius of the cutting edge and tool wear is clarified for the first time. The authors built an improved cutting force model in micro-milling LF 21 considering tool wear and cutter runout with the minimum cutting thickness as the boundary. The validity of the built micro-milling force model is verified by experiments.

Analysis of 3-DOF Cutting Stability of Titanium Alloy Helical Milling Based on PKM and Machining Quality Optimization

Aiming at the requirements of titanium alloy holes in aircraft industry, the 3-DOF cutting stability and surface quality optimization of parallel kinematic manipulator (PKM) are studied. The variation of natural frequencies with the end-effector position of the PKM is analyzed. The cutting force model of titanium alloy helical milling based PKM is developed, and the cutting force coefficients are identified. The prediction model for 3-DOF the stability of helical milling based on the PKM is established through a Semi-Discrete method, and the stability lobes are obtained. The correctness of the stability lobes is verified by subjecting the cutting force signal to time-frequency transformation and roughness detection. The step-cutter is used for machining process improvement to enhance the stability domain. The method proposed in this paper can provide a reference for further optimization of the prediction and optimization of the milling process of difficult-to-process materials based on PKM in the future.

Sub-Fiber Scale Precision Dicing of Aramid Fiber-Reinforced Plastic Composites

Aramid fiber-reinforced plastic (AFRP) composites are widely used in aerospace, rail transit, marine and military industries, due to their high specific strength, high impact resistance, fatigue resistance and excellent designable properties. In order to meet different application requirements, cutting processes need to be carried out, such as window opening, edge cutting and slit cutting. However, the characteristics of high tensile strength and toughness, low interlaminar strength, non-uniformity and anisotropy make AFRP composites a difficult-to-machine material. They are prone to produce rough cutting surfaces and cutting damages including burr, wire drawing, delamination, resin burn, material flanging, etc. To solve this problem, the ultra-thin diamond dicing blade was used for high-speed cutting of AFRP composites in sub-fiber scale in this research. The influence of process parameters on cutting force, cutting temperature, maximum spindle current, tool wear and cutting surface quality were investigated by establishing the cutting force model, L16(45) orthogonal experiment, single factor experiment, range analysis and variance analysis. The theoretical and experimental results show that cutting AFRP composites with ultra-thin diamond dicing blade can obtain smooth surfaces without common cutting damages. When the cutting speed is 91.11 m/s (spindle speed n = 30,000 r/min), the cutting depth is 0.2 mm and the feed speed is 5 mm/s, the surface roughness Ra can be as low as 32 nm, which realize the precision cutting of AFRP composites.