Tool Edge Radius Research Articles

Nanometric behaviour of monocrystalline silicon when single point diamond turned—a molecular dynamics and response surface methodology analysis

Hard and brittle materials such as silicon and silicon carbide are widely used in aerospace and integrated circuit. They are often poorly machined owing to non-linearity in machining process and complexities in selecting suitable machining parameters and tool geometry. The experimental difficulty involved in observing nanoscale physical phenomena (i.e. in-process measurement problems, inaccessible contact area of tool and workpiece, and the difficulty of surface analysis) has led to the use of molecular dynamics (MD) and response surface methodology (RSM) to investigate effect of tool edge radius, rake and clearance angles on monocrystalline silicon in this research. The response of subsurface deformation depth (SSD), tool temperature, kinetic friction cutting and thrust forces to tool edge radius, rake and clearance angles showed that SSD increased as the rake angle, edge radius and clearance angle increased while kinetic friction reduced as they increased. The increase in SSD as the clearance angle increased as observed in this study can be associated to the interactive/combined influence of the effects of both edge radius and rake angle.

Finite element simulation and experimental research on microcutting mechanism of single crystal silicon

Microcutting technology, which has been proven to be an indispensable means for investigating the material removal mechanism, is able to realize the high efficiency processing of brittle materials with an ultrasmooth surface and a low-damage subsurface. In this study, a series of simulations were performed by finite element (FE) method to investigate the microcutting mechanism of the typical semiconductor material, single crystal silicon. The FE cutting models were established in terms of the Johnson–Cook constitutive relation. First, the material removal behavior during the microcutting process was studied. The results indicated that the chip formation was dominated by extrusion rather than shearing action, and both sides of the chips were smooth without any wrinkle or shear band. Then, the cutting force and cutting heat during the microcutting process were analyzed in deep. It was determined that when the cutting characteristic size reduced to less than the tool edge radius, much energy was needed to remove the materials per unit volume. Besides, microcutting experiments were conducted using a specially designed cutting platform in a scanning electron microscope, and the experimental results were observed to be in agreement with the FE simulation results.

A comparative analysis of characteristics of cutting forces at micro-milling of hardened steels

Micro-milling is one of the most important technologies to produce miniature components. Mainly due to the size reduction, the process has many special characteristics, such as the relatively large tool run-out, the relatively large deformation and the cutting edge radius of the micro-milling tool. The cutting force is often correlated to the phenomena mentioned above, its analysis is therefore often required. The main objective of the present paper is to analyse and compare the characteristics of cutting forces in micro-milling of different hardened steels. A systematic series of experiments were conducted on a hardened AISI H13 hot-work tool steel and a Böhler M303 martensitic corrosion resistance steel. The hardness of both materials is 50 HRC. A 500 µm diameter two fluted carbide micro end mill and a five-axis micromachining centre were applied. The effects of the cutting parameters are analysed by the analysis of variance (ANOVA). Experimental results show that the workpiece material has a significant influence on the cutting forces.

High-Precision Cutting Edge Radius Measurement of Single Point Diamond Tools Using an Atomic Force Microscope and a Reverse Cutting Edge Artifact

This paper presents a measurement method for high-precision cutting edge radius of single point diamond tools using an atomic force microscope (AFM) and a reverse cutting edge artifact based on the edge reversal method. Reverse cutting edge artifact is fabricated by indenting a diamond tool into a soft metal workpiece with the bisector of the included angle between the tool’s rake face and clearance face perpendicular to the workpiece surface on a newly designed nanoindentation system. An AFM is applied to measure the topographies of the actual and the reverse diamond tool cutting edges. With the proposed edge reversal method, a cutting edge radius can be accurately evaluated based on two AFM topographies, from which the convolution effect of the AFM tip can be reduced. The accuracy of the measurement of cutting edge radius is significantly influenced by the geometric accuracy of reverse cutting edge artifact in the proposed measurement method. In the nanoindentation system, the system operation is optimized for achieving high-precision control of the indentation depth of reverse cutting edFigurege artifact. The influence of elastic recovery and the AFM cantilever tip radius on the accuracy of cutting edge radius measurement are investigated. Diamond tools with different nose radii are also measured. The reliability and capability of the proposed measurement method for cutting edge radius and the designed nanoindentation system are demonstrated through a series of experiments.

An Iterative Size Effect Model of Surface Generation in Finish Machining

In this work, a geometric model for surface generation of finish machining was developed in MATLAB, and subsequently verified by experimental surface roughness data gathered from turning tests in Ti-6Al4V. The present model predicts the behavior of surface roughness at multiple length scales, depending on feed, nose radius, tool edge radius, machine tool error, and material-dependent parameters—in particular, the minimum effective rake angle. Experimental tests were conducted on a commercial lathe with slightly modified conventional tooling to provide relevant results. Additionally, the model-predicted roughness was compared against pedigreed surface roughness data from previous efforts that included materials 51CrV4 and AL 1075. Previously obscure machine tool error effects have been identified and can be modeled within the proposed framework. Preliminary findings of the model’s relevance to subsurface properties have also been presented. The proposed model has been shown to accurately predict roughness values for both long and short surface roughness evaluation lengths, which implies its utility not only as a surface roughness prediction tool, but as a basis for understanding three-dimensional surface generation in ductile-machining materials, and the properties derived therefrom.

Modeling and detection of the prepared tool edge radius.

High-speed and high-efficient machining is the inevitable development direction of machining technology. The tool edge preparation can improve the life, cutting performance, and surface quality of a tool and help to achieve high-speed and efficient machining. Therefore, precise modeling and detection of the micron-level contour of a tool edge are crucial for edge preparation. The aim of this study is to provide the model and detect method of the prepared tool edge radius. The mathematical model of the milling tool trajectory is established through the Matlab. The material removal model by single abrasive particle is established based on the energy conservation principle and energy absorption theory. The material removal model by multiple abrasive grains on the cutting tool edge is constructed using the statistical methods. The mathematical model of the edge radius is established through the geometrical relationship. The milling edge preparation contour detection system is setup based on the machine vision principle through LabVIEW software. Finally, the edge radius at different process parameters is determined by the mathematical model and detection system, and the results are compared with the results of the scanning electron microscopic measurement (SEM). Through the Comparison and analysis of the edge radius measured by the SEM and calculated by the proposed model. The maximum error between the analytical results and SEM measurements is 11.18 μm, while the minimum error is 0.07 μm. Through the comparison and analysis of the edge radius measured by the SEM and the edge detection system. The maximum difference between the two methods is 2.71 μm, and the minimum difference is 0.31 μm. The maximum difference in percentage is 9.2%, and the minimum difference in percentage is 1.2%. The edge preparation mechanisms of a single particle and multiple particles on the tool edge are explained. A mathematical model of the edge radius is established, which provides a basis for a deeper understanding of the edge preparation effect. Based on the machine vision principle, the prepared tool micron-level edge detection method is proposed. The histogram specification method, median filtering, multi-threshold segmentation method, and Canny edge detection operator are adopted to obtain the edge contour. The comparison result shows that the mathematical model of the edge radius is accurate, and the proposed tool edge detection method is feasible, which lays the foundation for edge preparation and realization of high-speed and high-efficient machining.

Finite element simulation-based predictive regression modeling and optimum solution for grain size in machining of Ti6Al4V alloy: Influence of tool geometry and cutting conditions

The present research study was aimed at studying the impact of machining parameters on grain size alterations in machining of Ti6Al4V alloy using finite element analysis (FEA) based on the Johnson-Mehl-Avrami-Kolmogorov (JMAK) recrystallization model. The machining parameters consisted of both cutting conditions and tool geometry including cutting speed, feed rate, tool edge radius and rake angle. Three series of JMAK constants were used in the simulations and the degree of accuracy of the obtained results were compared. Finite element (FE) simulations were conducted for machining conditions designed using a D-optimal Design of Experiment (DoE). Analysis of Variance (ANOVA) was carried out to identify the most effective machining parameters on the responses of average grain size (AGS), machining temperature (MT), cutting force (CF), and feed force (FF). Next, Response Surface Method (RSM) was used to predict regression models of AGS, MT, CF, and FF. The optimal values of machining parameters were obtained to improve AGS, MT, CF, and FF. The ANOVA results showed that rake angle and cutting speed were, respectively, the most and least significant parameters affecting AGS in the design space. Rake angle was the most effective parameter influencing all of the responses. The single-criterion optimization of AGS provided a small improvement in AGS with a high increase in material removal rate (MRR). The results of the multi-criteria optimization of AGS, MT, CF, and FF demonstrated that machining of Ti6Al4V alloy with a tool having a medium cutting edge radius and high positive rake angle at a medium cutting speed and a low feed rate in the design space produced finer grains along with reduced CF and FF and an unchanged MT.

Modeling Dynamic Stability and Cutting Forces in Micro Milling of Ti6Al4V Using Intermittent Oblique Cutting Finite Element Method Simulation-Based Force Coefficients

Abstract Tool breakage is a significant issue in micro milling owing to the less stiffness of the micro tool. To cope up with such limitation, precise predictions of dynamic stability, and cutting force have the utmost importance to monitor and optimize the process. In this article, dynamic stability and cutting force are predicted precisely for micro milling of Ti6Al4V by obtaining force coefficients from a novel 3D intermittent oblique cutting finite element method (FEM) simulation considering the influence of tool run out. First, the stability model is modified by incorporating the appropriate values of limiting angles obtained analytically accounting the trajectories of the flutes due to tool run out. This stability model is utilized to select chatter-free parametric combinations for micro milling tests. Next, an improved cutting force model is developed by incorporating the force coefficients obtained from oblique cutting simulation in the mechanistic model and differentiating the whole machining region into three distinct region considering size effect. The force model also considers the effect of increased edge radius of the worn tool, run out, elastic recovery, ploughing, minimum undeformed chip thickness (MUCT), and limiting angles, cumulatively. The proposed dynamic stability and cutting force models based on the oblique cutting simulation show their adequacy by predicting the stability limit and cutting force more precisely, respectively, as compared to those obtained by orthogonal cutting simulation. Besides, the proposed force model for the worn tool is found to be viable as it is closer to the experimental forces, whereas force model without the incorporation of tool wear underestimated the experimental forces.

Micro-end milling of biomedical Tz54 magnesium alloy produced through powder metallurgy

In this study, micro machinability of Mg5Sn4Zn (TZ54) alloy produced by a hot-pressing process (one of the powder metallurgy methods) is investigated. For this purpose, micro-milling experiments were carried out, considering different cutting parameters. In order to determine the appropriate cutting parameters, the variation of cutting forces, surface quality and burr width were investigated. The cutting forces obtained in micro-milling of the TZ54 alloy are relatively small compared to other biomedical materials. In terms of both cutting forces and surface roughness, the minimum chip thickness is between 7% and 34% of the tool edge radius. However, compared to alloys such as Ti6Al4V and 316 L, the burr width is about 80% smaller. An important contribution of the study is that the minimum chip thickness (0.1 μm) has been confirmed in terms of both cutting force and surface roughness. In addition, even at high material removal rates, the minimum cutting forces are important findings of the study. The predominant wear mechanism in the cutting tool is abrasive wear. In view of tool life, surface roughness and burr formation, it is envisaged that the TZ54 alloy can be an easy machinable, alternative biomedical material.

Study on nano-cutting of brittle material by molecular dynamics using dynamic modeling

Nano-cutting of brittle material finds wide applications in scientific research and engineering. Numerical simulation is an important tool for understanding the process mechanism, which has many advantages over experimental approaches. Currently, molecular dynamics is the most used method for nano-cutting simulation owing to its explicit description of material at atomic level. However, the model scale in current studies is far smaller than the reality. As a result, cutting-induced fracture, the main surface damage in the machining of brittle material, is difficult to reveal and well understand, which has become a critical issue in the field. In this study, a novel simulation approach is proposed to improve the computing efficiency after analyzing the shortcomings of traditional model. The principle is to build a localized workpiece near the tool which is dynamically modified so that the length of workpiece in computation is reduced and the saved computer resource can be used to increase the depth of cut and the tool edge radius. A large scale simulation on germanium verifies the capability of this method and reveals the fracture damage formation during the cutting process.

Effects of tool edge radius on chip formation during the micromachining of pure iron

The smoothed particle hydrodynamics simulation model of micromachining of industrial pure iron was established to study the effect of tool edge radius on chip formation in this paper. The process of chip production was studied by particle displacement method, and cutting force and stress were analyzed. Meanwhile, the mechanism of chip formation was revealed. The simulation results show that the tool edge radius has significant effects on chip formation in micromachining. When the depth of cut is 0.16 times of the tool edge radius, the chips begin to produce. And the minimum cutting thickness decreases with the increase of the ratio of the cutting depth to the tool edge radius, which means that chips are more easily to be produced with the decrease of the tool edge radius. Meanwhile, the larger the tool edge radius is, the wider the stress distribution area is and the greater the fluctuation of the cutting force is. Finally, values of the minimum cutting thickness under different ratios obtained by the theoretical formula are basically consistent with the simulation results, verifying the correctness of the simulation results. This paper provided valuable insights into reasonable selection of tool parameters for improving machining precision.

Rake angle effect in cutting-based single atomic layer removal

When minimum cutting depth is down to a single atomic layer, two portions of the cutting tool, namely, cutting edge and lowest atoms of the cutting tool, are involved in the cutting-induced material removal. Correspondingly, there are different critical rake angles for those two portions of the tool, different from the nominal rake angle in conventional cutting and edge radius-induced effective rake angle in nanocutting. Both they should be considered in atomic and close-to-atomic cutting to obtain the defect-free processed surface with an ideal crystalline structure. Molecular dynamics modelling is carried out to investigate the critical rake angles to enable single atomic layer removal on monocrystalline Cu (1 1 1) surface. The analysis results clearly indicate that the critical rake angles of nanometric cutting edge and the lowest tool atoms for single atomic layer removal are among the range of (–70°, –65°) and (–17°, –14°), respectively. To achieve single atomic layer removal, the tool edge radius is suggested to be not greater than 2 nm. The research findings would provide theoretical guidelines to the cutting tool design for the application of mechanical cutting of high-performance atomic scale devices.

Evaluation and Modeling of the Effect of Tool Edge Radius on Machined Surface Roughness in Turning UNS A92024-T351 Aluminum Alloy

Abstract Tool edge radius plays a significant role in affecting the surface integrity of machined products. The vast majority of existing research, however, takes no account of the effect of tool edge radius in the evaluation and modeling of machined surface roughness, an essential indicator of surface integrity. The present study fills this important research gap and has performed a total of 45 turning experiments on Unified Numbering System (UNS) A92024-T351 aluminum alloy with carefully selected cutting tools with three levels of tool edge radii. This article describes the experimental setup and measurements of tool edge radius and machined surface roughness. Machined surface roughness was evaluated using five parameters, including average roughness, root-mean-square roughness, peak roughness, maximum roughness height, and five-point average roughness. The experimental evidence presented in this article shows that the tool edge radius has a profound effect on machined surface roughness, cutting forces, and cutting vibrations. Based on the experimental data, three types of predictive models are developed, including a multiple regression model, multilayer perceptron neural network model, and radial basis function neural network model. The prediction accuracy of the three models is compared based on average mean squared errors. The results show that different models lead to different prediction accuracy for different surface roughness parameters.

On the impacts of tool geometry and cutting conditions in straight turning of aluminum alloys 6061-T6: an experimentally validated numerical study

Aluminum alloys 6061-T6 are widely utilized in the automotive, aerospace, and marine industries due to high corrosion resistance, high strength, and good workability and machinability. The machining performance of these alloys depends on several factors including tool’s material, coating, and geometry. Cutting tool edge radius is one of the most effective factors in cutting forces, energy requirement, and chip formation during metal cutting. The present article aims to study the interactions between the cutting edge radius and cutting speed, feed rate, and rake angle and examine the impacts of the aforementioned tool geometry and cutting conditions on machining forces, cutting temperature, and chip thickness in cutting an aluminum alloy 6061-T6. Special attention is devoted to examining the influence of the cutting edge radius on machining variables and comparing the results of conventional machining (CM) and high speed machining (HSM). A finite element model was developed to simulate the above interactions and was experimentally validated for different machining parameters. The results demonstrate that although increasing the cutting edge radius clearly raises the machining forces, it has a slight influence on the chip thickness. It is also found that the maximum cutting temperatures remain nearly constant with changes in the tool edge radius, while the average temperatures of the tool tip increase especially in HSM. Furthermore, it was found that the location at which the maximum cutting temperature occurs depends more on cutting conditions and tool geometry than workpiece and tool materials.

Investigation of CFRP cutting mechanism variation and the induced effects on cutting response and damage distribution

Machining of carbon fiber-reinforced polymers (CFRP) still remains a difficult procedure in the whole manufacturing process. One of the reasons is the cutting mechanism varies during machining, causing the inconsistency of surface integrity. This study intends to investigate the continuous variation of cutting mechanism and the induced cutting responses and damages. A novel experiment, with square and circular workpieces involved in cutting, was designed. A three-dimension micro-scale cutting simulation model was built. The experiment and simulation were combined to analyze the evolution and the correlation of cutting forces, machined surface roughness, sub-surface damage and the burr formation. The effects of rake angle and tool edge radius on chip formation and sub-surface damage were also presented. The conclusions are helpful to understand the damages generation during machining of CFRP.

Investigations into edge radius and point angle on energy consumption during micro drilling of titanium alloy

In aircraft industries, micro holes need to be provided on gas turbine blade to improve cooling and efficiency of aero engines. Generating micro features in gas turbine blade materials are tedious task due to enhanced thermal, mechanical and metallurgical properties of aero engine alloy. So in this paper a finite element simulation is developed to comprehend the process mechanics of micro drilling process and study the influence of point angle and edge radius on energy consumption. The model has been developed by considering size effect, point angle and drill tool edge radius. The modified JC model is used to delineate the flow stress during micro drilling process. The simulations are done by varying drilling speed, feed rate, point angles and edge radius of the micro drill tool. The results obtained are calibrated with various friction shear factors and finally verified with experimental outcome in the literature. Thrust force is observed to decrease when the drill speed increases because of low thermal conductivity of an aero engine alloy generate thermal softening more predominant than strain hardening in the micro drill zone. When the point angle of micro drill decreases, there is less energy consumed for the generation of hole. Higher edge radius tool results in variation of dimension and form of hole, whereas for lower edge radius comparable to uncut chip thickness result in nonlinear increase in power consumption. The average thrust force prediction error is 15.17%.

Mechanistic modelling of dynamic cutting forces in micro end milling of Zr-based bulk metallic glass

This paper presents the mechanistic modelling of dynamic cutting forces in micro end milling using cutting force coefficients determined empirically from the average cutting forces in the ploughing and shearing dominant regimes. The influence of the cutting tool edge radius and the effects of ploughing, elastic recovery, overlapping tooth engagement of the cutting tool etc. are considered in the cutting force model. The ploughing forces are modelled as proportional to the interactive area between the rounded cutting edge and the work material. The proposed model is compared with the results of several micro milling experiments with Zr-based bulk metallic glass. The study reveals that the radial ploughing coefficient is larger than the tangential ploughing coefficient. However, the tangential cutting coefficient is found to be larger than the radial cutting coefficient. The developed model is found to predict the cutting forces fairly well under different micro cutting conditions.

Mechanistic modelling of dynamic cutting forces in micro end milling of Zr-based bulk metallic glass

This paper presents the mechanistic modelling of dynamic cutting forces in micro end milling using cutting force coefficients determined empirically from the average cutting forces in the ploughing and shearing dominant regimes. The influence of the cutting tool edge radius and the effects of ploughing, elastic recovery, overlapping tooth engagement of the cutting tool etc. are considered in the cutting force model. The ploughing forces are modelled as proportional to the interactive area between the rounded cutting edge and the work material. The proposed model is compared with the results of several micro milling experiments with Zr-based bulk metallic glass. The study reveals that the radial ploughing coefficient is larger than the tangential ploughing coefficient. However, the tangential cutting coefficient is found to be larger than the radial cutting coefficient. The developed model is found to predict the cutting forces fairly well under different micro cutting conditions.

Effect of relative tool sharpness on subsurface damage and material recovery in nanometric cutting of mono-crystalline silicon: A molecular dynamics approach

Depth of cut (h0) and tool edge radius (re) are two key parameters in nanometric cutting, investigating both of the two parameters simultaneously can provide comprehensive understanding of the cutting mechanism. In this paper, relative tool sharpness (RTS), which is quantified as h0/re, is employed as a factor to examine the subsurface damage and material recovery in nanometric cutting of mono-crystalline silicon using molecular dynamics (MD) simulation. Various RTS values were generated by changes of cutting depth at different tool edge radius of 1, 3 and 5 nm respectively. Results indicate that there is always a layer of particles which sticks on the tool surface and influences the machined surface, even at RTS = 0. Besides that, the increase of RTS results in subsurface damage layer serration, which is caused by stick-slip phenomenon between the tool and workpiece. A bigger RTS causes a bigger depth of serrations, although the number of serrations remains constant. Increase in RTS also causes the formation of the hexagonal diamond structure. The material recovery drops dramatically by RTS increase. Using a sharper tool edge (RTS<0.25) at a cutting depths below 1 nm does not necessarily decrease subsurface damage due to the drastic stress concentration. It is also demonstrated that silicon amorphisation can occur in the unmachined region in front of the tool due to the hydrostatic pressure wave caused by tool advancement.

Effect of tool edge radius on material removal mechanism in atomic and close-to-atomic scale cutting

For mechanical cutting, when cutting depth is decreased to atomic and close-to-atomic scale(ACS), the material removal mechanism would be dominated by dislocation motion, different from conventional cutting and nanocutting. It is is greatly influenced by cutting edge radius effect in the aspects of chip formation, cutting forces, and stress distribution, etc. There appear three deformation zones in ACS cutting, including dislocation slip zone, chip formation zone and elastic deformation zone. As cutting-edge radius increases, both of dislocation slip zone and chip formation zone are suppressed while the elastic deformation zone tends to continually grow. When cutting edge radius is increased to be larger than a threshold, the elastic deformation zone is further transformed into one elastic and plastic deformation zone, while a very small chip formation zone, and dislocation zone is remained ahead of rounded cutting edge. Consequently, though the minimum cutting depth is decreased to single atomic layer, the material removal behaviour is also dominated by extrusion action of cutting tool, following the mechanism of nanocutting. The research findings would provide theoretical guidelines to the cutting tool design for atomic and close-to-atomic scale cutting.