The statistical modeling of surface roughness in high-speed flat end milling

Surface roughness is one of the most important requirements in machining process. The surface roughness value is a result of the tool wear. When tool wear increase, the surface roughness also increases. The determination of the sufficient cutting parameters is a very important process obtained by means of both minimum surface roughness values and long tool life. The statistical models were developed to predict the surface roughness.This paper presents the development of a statistical model for surface roughness estimation in a high-speed flat end milling process under wet cutting conditions, using machining variables such as spindle speed, feed rate, depth of cut, and step over. First- and second-order models were developed using experimental results of a rotatable central composite design, and assessed by means of various statistical tests. The highest coefficient of correlation (R_adj²) (88%) was obtained with a 10-parameter second-order model. Meanwhile, a time trend was observed in residual values between model predictions and experimental data, reflecting the probable effect of the tool wear on surface roughness. Thus, in order to enhance the estimation capability of the model, another independent variable was included into the model to account for the effect of the tool wear, and the total operating time of the tool was selected as the most suitable variable for this purpose. By inserting this new variable as a linear term into the model, R_adj² was increased to 94% and a good fit was observed between the model predictions and supplementary experimental data.In this study, it was observed that, the order of significance of the main variables is as X₅>X₃>X₄>X₁>X₂ (total machining time, depth of cut, step over, spindle speed and feed rate, respectively).     

Surface layer characteristics due to slide diamond burnishing with a cylindrical-ended tool

The article presents an unconventional method of finishing shafts - slide burnishing with a cylindrical-ended tool whose axis is perpendicular to that of the worked shaft. The contact area of the tool with the workpiece and the tool force necessary for burnishing 42CrMo4 alloy steel shafts were calculated. The effect of burnishing parameters on the surface stereometric structure, the surface layer hardening and the distribution of final stresses was examined. Compared with grinding, a considerable improvement in surface condition indicators was found and it was possible to achieve a surface roughness, Sa of 0.05-0.18 μm. Surface microhardness increased by up to 29% and compressive stresses of up to a 400 MPa of the absolute value occurred in the surface layer. The effect of burnishing parameters on surface roughness, Sa and oscillatory bending strength were examined and the relevant mathematical models - multinominals of the second order that also allow for the interaction of input factors were obtained. Fatigue strength improved (compared to that of the ground workpieces) by 18%. It was found that those effects can be achieved without a lot of technological effort.     

The influence of cutter orientation and workpiece angle on machinability when high-speed milling Inconel 718 under finishing conditions

The paper details results from a comprehensive series of experiments on the effects of key operating variables; cutter orientation and workpiece tilt angle, on tool life/length cut, cutting force, workpiece surface roughness (R_a), subsurface microstructure/microhardness and residual stress, when high-speed milling under finishing conditions. In terms of length cut, the 8 mm diameter coated (TiAlCrN multi-layer) carbide ball nose end mills achieved tool life values approaching 200 m. Life results for the horizontal downwards orientation when cutting with a workpiece tilt angle of 45° were similar to those when operating with the workpiece mounted horizontally, however, cutting forces were significantly higher in the latter case. Evidence of tool chatter was also observed from cutting force signatures with the horizontal upwards mode. Mean compressive surface residual stresses up to −850 MPa measured parallel to the feed direction were obtained when machining using worn tools with a 0° workpiece inclination, while tensile stresses were obtained when machining with horizontal downwards orientation.     

Modification of surface finish produced by hard turning using superfinishing and burnishing operations

In this study the surface finish produced by hard turning of a 41Cr4 low-alloy steel quenched to about 60 HRC hardness, using mixed Al₂O₃-TiC ceramic inserts, was subsequently modified by superfinishing and multipass burnishing operations. In the case of hard turning surfaces were produced by conventional and Wiper cutting tool inserts. The main goal of this study was to examine how additional abrasive and non-removal technological operations change 2D and 3D roughness parameters and enhance service properties of the machined surfaces. It was documented that both superfinishing and burnishing operations allow to obtain smoother surfaces with lower surface roughness and better bearing characteristics.     

Conservation law of surface roughness in single point diamond turning

In this work, a comprehensive model is established to predict the surface roughness achieved by single point diamond turning. In addition to the calculation of the roughness components in relation to the kinematics and minimum undeformed chip thickness, the newly developed model also takes the effects of plastic side flow and elastic recovery of materials as machined into account. Moreover, the ‘size effect’ has also been successfully integrated into the model, i.e. an inflection point appears in the trend line of predicted surface roughness as the ratio of maximal undeformed chip thickness to cutting edge radius (h_Dmax/r_n) is equal to one unit. Face turning experiments validate that the maximal prediction error is only 13.35%. As the ratio of h_Dmax/r_n is higher than one unit, both the prediction and experiments reveal that a conservation law exists in diamond turned surface roughness, owing to the competitive effects of kinematics, minimum undeformed chip thickness, plastic side flow and elastic recovery of materials on surface formation. Under the conservation law, the freedom control for an invariable surface roughness can be fulfilled in response to a quantitative ratio of h_Dmax/r_n, either through an accurate configuration of feed rate and depth of cut with fixed tool nose radius and cutting edge radius, or by a reasonable selection of tool nose radius and controlled cutting edge radius with designed feed rate and depth of cut.     

Adhesion phenomena in the secondary shear zone in turning of austenitic stainless steel and carbon steel

This paper aims to increase the understanding of the adhesion between chip and tool rake face by studying the initial material transfer to the tool during orthogonal machining at 150 m/min. Two types of work material were tested, an austenitic stainless steel, 316L, and a carbon steel, UHB 11. The tools used were cemented carbide inserts coated with hard ceramic coatings. Two different CVD coatings, TiN and Al₂O₃, produced with two different surface roughnesses, polished and rough, were tested. The influences of both tool surface topography and chemistry on the adhesion phenomena in the secondary shear zone were thus evaluated. Extensive surface analyses of the inserts after cutting were made using techniques such as Scanning Electron Microscopy (SEM), Energy Dispersive Spectroscopy (EDS), X-ray Photoelectron Spectroscopy (XPS), and Transmission Electron Microscopy (TEM). As expected, cutting in the stainless steel resulted in a higher amount of adhered material, compared to cutting in the carbon steel. Remnants of built-up layers were found on the surfaces of the 316L chips but not on the UHB 11 chips. Moreover, it was shown that for both materials the tool roughness had a profound effect, with the rougher surfaces comprising much higher amounts of adhered material than the polished ones. Non-metallic inclusions from both types of workpiece steels accumulate in the high temperature area on the inserts. The general tendency was that higher amounts of transferred material were found on the TiN coating than on the Al₂O₃ coating after cutting.     

Characterization of the transition from ploughing to cutting in micro machining and evaluation of the minimum thickness of cut

When the machining process is miniaturized two process mechanisms, ploughing and chip formation, are essential and a critical cutting thickness needs to be exceeded so that not only ploughing will occur but chips will also be formed. The ploughing effect thereby influences the chip formation process, workpiece surface roughness, burr formation and residual stress state after processing and is therefore of great interest. In order to optimize the machining process a better understanding of the minimum thickness of cut is crucial.The changes in surface topography along the cutting track occurring during machining with a constant feed rate of the cutting tool were analyzed. The influence of the built-up edge phenomena on the micro machining process was investigated for normalized AISI 1045 using confocal white light microscopy and scanning electron microscopy. Furthermore the sin²ψ-method was applied in order to study the residual stress state in the workpiece surface induced by the machining process. Both surface layer properties investigated, surface roughness and residual stresses, show a characteristic transition indicating a change in the dominating process mechanisms. Based on these results a model is developed to determine the minimum thickness of cut. The minimum thickness of cut is found to significantly decrease with higher cutting velocities and to moderately increase with higher cutting edge radii. In addition a propagation of error for the values obtained with the model was performed, proving the quality of the model developed.     

Prediction and control of surface roughness in CNC lathe using artificial neural network

In this study, a neural network approach is presented for the prediction and control of surface roughness in a computer numerically controlled (CNC) lathe. Experiments have been performed on the CNC lathe to obtain the data used for the training and testing of a neural network. The parameters used in the experiment were reduced to three cutting parameters which consisted of depth of cutting, cutting speed, and feed rate. Each of the other parameters such as tool nose radius, tool overhang, approach angle, workpiece length, workpiece diameter and workpiece material was taken as constant. A feed forward multi-layered neural network was developed and the network model was trained using the scaled conjugate gradient algorithm (SCGA), which is a type of back-propagation. The adaptive learning rate was used. Therefore, the learning rate was not selected before training and it was adjusted during training to minimize training time. The number of iterations was 8000 and no smoothing factor was used. R_a, R_z and R_max were modeled and were evaluated individually. One hidden layer was used for all models while the numbers of neurons in the hidden layer of the R_a model were five and the numbers of neurons in the hidden layers of the R_z and R_max models were ten. The results of the neural network approach were compared with actual values. In addition, inasmuch as the control of surface roughness is proposed, a control algorithm was developed in the present investigation. The desired surface roughness was entered into the control system as a reference value and the controller determined the cutting parameters for these surface roughness values. A new surface roughness value was determined by sending the cutting parameters to the observer (ANN block). The obtained surface roughness was fed back to the comparison unit and was compared with the reference value and the difference surface roughness was then sent to the controller. The iteration was continued until the difference was reduced to a certain value of surface roughness which could be permitted for machining accuracy. When the surface roughness reached the permitted value, these cutting parameters were sent to the CNC turning system as input values. In conclusion, both the surface roughness values corresponding to the cutting parameters and suitable cutting parameters for a certain surface roughness can be determined prior to a machining operation using the ANN and control algorithm.     

A study of back cutting surface finish from tool errors and machine tool deviations during face milling

The surface finish of mechanical components produced by face milling is given by factors such as cutting conditions, workpiece material, cutting geometry, tool errors and machine tool deviations. The contribution of the different tool teeth to imperfections in the machined surface is strongly influenced by tool errors such as radial and axial runouts. The surface profile of milled parts is not only affected by chip removal due to front cutting, but also by back cutting, which must be taken into account when predicting surface roughness. In the present work, the influence of back cutting on the surface finish obtained by face milling operations is studied. Final part surface roughness is modelled from tool runouts and height deviations that affect the surface marks provoked by back cutting. Round insert cutting tools and surface positions defined by cutter axis trajectory are considered, and milling experiments are developed for a spindle speed of 750 rpm, depth of cut of 0.5 mm and feeds from 0.4 to 1.0 mm/rev. Experimental observations are compared with the theoretical predictions provided by the surface roughness model, and good agreement is found between both results. Surface imperfections caused by front and back cutting are analysed, and discrepancies between experiments and numerical predictions are explained by undeformed chip thickness variations along the tool tooth cutting edge, the tearing of the workpiece material, and fluctuations in the feedrate and height deviation during machine tool axis displacement.     

A new approach to cutting state monitoring in end-mill machining

A new cutting state monitoring approach is proposed for the real-time predicting of the machining trouble and the surface quality of the machined products. In this approach, the relationships among the mechanical model of cutting process and its corresponding time series model, the surface roughness of the machined workpiece are evaluated through theoretical analysis and experimental investigation. It is therefore revealed that there is the linear relationships among the AR parameter a₁, the stiffness k₃ of cutting model and surface roughness P_z, and consequently the cutting process state can be estimated by only monitoring time series parameter a₁ of vibration signal measured during machining operation. In particular, it was found that the variation in the surface roughness of P_z=3–5 μm can be fully monitored.     

Mathematical modeling of surface roughness for evaluating the effects of cutting parameters and coating material

The work presented in this paper examines the effects of cutting parameters (cutting speed, feed rate and depth of cut) onto the surface roughness through the mathematical model developed by using the data gathered from a series of turning experiments performed. An additional investigation was carried out in order to evaluate the influence of two well-known coating layers onto the surface roughness. For this purpose, the experiments were repeated for two CNMG 120408 (with an ISO designation) carbide inserts having completely the same geometry and substrate but different coating layers, in a manner that identical cutting conditions would be ensured. The workpiece material machined was cold-work tool steel AISI P20. Of the two types of inserts employed; Insert 1 possesses a coating consisting of a TiCN underlayer, an intermediate layer of Al₂O₃ and a TiN outlayer, all deposited by CVD; whilst Insert 2 is PVD coated with a thin TiAlN layer (3 ± 1 μm). The total average error of the model was determined to be 4.2% and 5.2% for Insert 1 and Insert 2, respectively; which proves the reliability of the equations established.     

An in-process surface recognition system based on neural networks in end milling cutting operations

An in-process based surface recognition system to predict the surface roughness of machined parts in the end milling process was developed in this research to assure product quality and increase production rate by predicting the surface finish parameters in real time. In this system, an accelerometer and a proximity sensor are employed as in-process surface recognition sensors during cutting to collect the vibration and rotation data, respectively. Using spindle speed, feed rate, depth of cut, and the vibration average per revolution (VAPR) as four input neurons, an artificial neural networks (ANN) model based on backpropagation was developed to predict the output neuron-surface roughness R_a values. The experimental results show that the proposed ANN surface recognition model has a high accuracy rate (96–99%) for predicting surface roughness under a variety of combinations of cutting conditions. This system is also economical, efficient, and able to be implemented to achieve the goal of in-process surface recognition by retrieving the weightings (which were generated from training and testing by the artificial neural networks), predicting the surface roughness R_a values while the part is being machined, and giving feedback to the operators when the necessary action has to be taken.     

An improved cutting force and surface topography prediction model in end milling

During the milling operation, the cutting forces will induce vibration on the cutting tool, the workpiece, and the fixtures, which will affect the surface integrity of the final part and consequently the product's quality. In this paper, a generic and improved model is introduced to simultaneously predict the conventional cutting forces along with 3D surface topography during side milling operation. The model incorporates the effects of tool runout, tool deflection, system dynamics, flank face wear, and the tool tilting on the surface roughness. An improved technique to calculate the instantaneous chip thickness is also presented. The model predictions on cutting forces and surface roughness and topography agreed well with experimental results.     

Influence of micro-blasting on the microstructure and residual stresses of CVD κ-Al2O3 coatings

Cemented carbides coated with CVD multilayers are commonly used in metal cutting turning and milling operations. For many applications, a micro-blasting finishing procedure based on an impact treatment of the surfaces is carried out in order to smooth the coated surface and reduce sharp cutting edges. In this work, micro-blasting with corundum in aqueous solution at pressures between 0.05 and 0.3 MPa was applied to CVD TiN/Ti(C,N)/κ-Al₂O₃ multilayer coatings deposited onto cemented carbides in order to investigate its influence on the micro-topography, microstructure and residual stresses. The results showed that the micro-blasting reduces the surface roughness and affects the coating thickness. TEM investigations revealed no significant changes on the microstructure of the κ-Al₂O₃ top layer. Synchrotron X-ray investigations showed that the residual stress state of the as-deposited κ-Al₂O₃ top layer is not affected by the micro-blasting treatment under the conditions investigated.     

Cutting performance and wear mechanism of nanoscale and microscale textured Al2O3/TiC ceramic tools in dry cutting of hardened steel

Nanoscale and microscale textures with different geometrical characteristics were fabricated on the surface of the Al₂O₃/TiC ceramic tool, and molybdenum disulfide (MoS₂) solid lubricants were burnished into the textures. The effect of the textures on the cutting performance was investigated using the textured self-lubricated tools and conventional tools in dry cutting tests. The tool wear, cutting force, cutting temperature, friction coefficient, surface roughness and chip topography were measured. Results show that the cutting force, cutting temperature, friction coefficient and tool wear of nanoscale and microscale textured self-lubricated tools are significantly reduced compared with the conventional tool, and the developed tool with wavy microscale textures on the rake face is the most effective in improving the cutting performance. The textured self-lubricated tools increase the surface roughness of machined workpiece, while they can reduce the vibration for a stable cutting and produce more uniform surface quality. The chip topography is changed by the textured self-lubricated tools. As a result, the nanoscale and microscale textured self-lubricated tools effectively improve the cutting performance of conventional Al₂O₃/TiC ceramic tool, and they are applicable to a stable dry cutting of the hardened steel.     

Studies on drilling processes of intermetallic compounds

Intermetallic compounds have high-specific strength, good creep resistance and excellent oxidation and corrosion resistance at high temperatures. Those good mechanical properties make intermetallic compounds very promising structure materials in industries. Ni₃Al and Fe₃Al are two typical intermetallic compounds. This paper focuses on machinability and tool wear mechanism of PVD TiAlN coated cemented carbide tool in drilling of Ni₃Al and Fe₃Al. The influences of cutting speeds on tool wear and machined surface roughness were investigated. The tool wear mechanism was analyzed using scanning electron microscopy (SEM) and EDX analysis. Chips were analyzed by SEM and the machined surfaces were examined by surface roughness measurement instrument. Tool life when drilling of Ni₃Al is shorter than that of Fe₃Al. The built-up-edge (BUE) could be formed on the cutting edge in drilling of Fe₃Al, and no BUE was observed of Ni₃Al at the cutting speed of 29 m/min.     

An experimental and numerical study on the face milling of Ti-6Al-4V alloy: Tool performance and surface integrity

This paper is concerned with the experimental and numerical study of face milling of Ti-6Al-4 V titanium alloy. Machining is carried out by uncoated carbide cutters in the presence of an abundant supply of coolant. Experimental analysis is conducted by focusing on the measurement of specific cutting energy, surface integrity and tool performance. The experimental analysis is supplemented by simulations from a 3D finite element model (FEM) of face milling simulation where needed. A tool wear model parameterized from FEM predictions of the tool-chip interface temperature, contact stress and chip velocity is presented. Tool wear patterns are described in terms of various cutting conditions and the influence of tool wear on surface integrity is investigated. Tool wear predictions based on the 3D FEM simulation show good agreement with experimental tool wear measurements. The highest cutting speed realized for the cutting tool material is 182.9 m/min (600 sfpm). Good surface integrity in terms of favorable residual stress and surface finish is achieved under the machining conditions used with limited tool wear. Residual stresses imparted to the machined surface are shown to be compressive.     

Adaption of graded Cr/CrN-interlayer thickness to cemented carbide substrates' roughness for improving the adhesion of HPPMS PVD films and the cutting performance

High Power Pulsed Magnetron Sputtering (HPPMS) techniques jointly with the deposition of a graded Cr/CrN-nanointerlayer on cutting inserts can increase the film adhesion and consequently the tool life. These improvements depend on the roughness of the employed cemented carbide substrates. The investigations described in the present paper intend to explain the effect of Cr/CrN-interlayer thickness and substrate roughness on the coating adhesion and cutting performance. To attain various roughnesses, the applied cemented carbide inserts were superficially treated. These treatments were grinding at a medium roughness level, or grinding with subsequent polishing for enhancing the surface integrity and finally, in all cases, micro-blasting by fine Al₂O₃ grains. After Ar-ion etching, graded Cr/CrN adhesive layers with different thicknesses were deposited by HPPMS technology on the variously pretreated substrates. Subsequently, an approximately 3 μm thick (Ti,Al)N film was deposited by HPPMS PVD on all used inserts. Rockwell C indentations and inclined impact tests were performed to assess qualitatively and quantitatively the films' adhesion. The cutting performance of the coated tools was investigated in milling of 42CrMo4 QT. FEM supported calculations of the developed stresses during the material removal process contributed in explaining the obtained tool wear results. In these calculations, the adhesion, dependent on the substrate roughness characteristics and on the adhesive interlayer thickness, was taken into account. The results revealed that the effectiveness of HPPMS adhesive graded Cr/CrN-nanointerlayer strongly depends on the substrate surface integrity and on the interlayer thickness. Thus, the film adhesion and consequently the cutting performance can be significantly improved if the interlayer thickness is adapted to the substrate roughness.     

Topography of the flank wear surface

In many applications, topography represents the main external features of a surface. This paper describes the topography of the flank wear surface and also presents the relationship between the maximum flank wear and the topography parameters (roughness parameters) of the flank wear surface during the turning operation. A modern CNC lathe machine (Okuma LH35-N) was used for the machine turning operation. Three-dimensional surface roughness parameters of the flank wear surface were measured by a surface texture instrument (from Talysurf series) using surface topography software (Talymap). Based on the resulting experimental data, it is found that as the flank wear increases, the roughness parameters (sR_a, sR_q, and sR_t) on the flank surface increase significantly. The greater the roughness value of the flank wear surface, the higher the friction of the tool on the workpiece and the greater the heat generation that will occur, thus ultimately causing tool failure. On the other hand, positive skewness (sR_sk) indicates the presence of a small number of spikes on the flank surface of the cutting tool, which could quickly wear off during the machining process.     

Cutting temperatures during hard turning—Measurements and effects on white layer formation in AISI 52100

This paper concerns the temperature evolution during white layer formation induced by hard turning of martensitic and bainitic hardened AISI 52100 steel, as well as the effects of cutting temperatures and surface cooling rates on the microstructure and properties of the induced white layers. The cutting temperatures were measured using a high speed two-colour pyrometer, equipped with an optical fibre allowing for temperature measurements at the cutting edge. Depending on the machining conditions, white layers were shown to have formed both above and well below the parent austenitic transformation temperature, A_c1, of about 750 °C. Thus at least two different mechanisms, phase transformation above the A_c1 (thermally) and severe plastic deformation below the A_c1 (mechanically), have been active during white layer formation. In the case of the predominantly thermally induced white layers, the cutting temperatures were above 900 °C, while for the predominantly mechanically induced white layers the cutting temperatures were approximately 550 °C. The surface cooling rates during hard turning were shown to be as high as 10⁴–10⁵ °C/s for cutting speeds between 30 and 260 m/min independent of whether the studied microstructure was martensitic or bainitic. Adding the results from the cutting temperature measurements to previous results on the retained austenite contents and residual stresses of the white layers, it can be summarised that thermally induced white layers contain significantly higher amounts of retained austenite compared to the unaffected material and display high tensile residual stresses. On the contrary, in the case of white layers formed mainly due to severe plastic deformation, no retained austenite could be measured and the surface and subsurface residual stresses were compressive.