Optimization of surface roughness and tool wear in hard turning of austempered ductile iron (grade 3) using Taguchi method

In this work, the cutting parameters are optimized in hard turning of ADI using carbide inserts based on Taguchi method. The cutting insert CVD coated with AL₂O₃/MT TICN. Experiments have been carried out in dry condition using L₁₈ orthogonal array. The cutting parameters selected for machining are cutting speed, feed rate and depth of cut with each three levels, nose radius in two levels maintaining other cutting parameters constant. The ANOVA and signal to noise ratio are used to optimize the cutting parameters. The cutting speed is the most dominant factor affecting the surface roughness and tool wear. In optimum cutting condition, the confirmation tests are carried out. The optimum cutting condition results are predicted using signal to noise ratio and regression analysis. The predicted and experimental values for surface roughness and tool wear adhere closer to 9.27% and 1.05% of deviations respectively.     

Investigations on machined metal surfaces through the stylus type and optical 3D instruments and their mathematical modeling with the help of statistical techniques

The measurement of roughness on machined metal surfaces is of considerable importance to manufacturing industries as the roughness of a surface has a significant influence on its quality and function of products. In this paper, an experimental approach for surface roughness measurement has been based on the comparison of roughness values taken from the stylus and optical type instruments on the machined metal surfaces (turning, grinding and milling) is presented.Following this experimental study, all measured surface roughness parameters have been analyzed by using Statistical Package for Social Science (SPSS 15.0) statistically and mathematical models for the two most important and commonly used roughness parameters R_a and R_z have been developed so that R_a = R_a (F, P, C) and R_z = R_z (F, P, C, M), whereas F expresses feed, P periodicity, C contrast and M the type of material. The statistical results from numerous tests showed that there has been a correlation between the surface roughness and the properties of the surface topography and there have been slight differences among three measurement instruments on machined metal surfaces in this experimental study.     

Parameters optimization on surface roughness improvement of Zerodur optical glass using an innovative rotary abrasive fluid multi-jet polishing process

With the advance of contemporary technology, high precision surface finishing techniques for optical glasses are of great concern and developing to meet the requirements of the effective industrialized processes. Not only the used tools but also process parameters have great influence on the surface roughness improvements. In this paper, surface roughness improvement of Zerodur optical glass using an innovative rotary abrasive fluid multi-jet polishing process has been presented. For the same purpose, a tool for executing ultra precision polishing was designed and manufactured. Taguchi's experimental approach, an L₁₈ orthogonal array was employed to obtain the optimal process parameters. ANOVA analysis has also been carried out to determine the significant factors. It was observed that about a 98.33% improvement on surface roughness from (R_a) 0.360 μm to (R_a) 0.006 μm has been achieved. The experimental results show that a surface finished achieved can satisfy the requirements for optical-quality surface (R_a < 12 nm). In addition, the influence of significant factors on surface roughness improvement has been discussed in this study.     

Surface roughness and material removal rate of lapping process on ceramics

Lapping is a widely used surface finishing process for ceramics. An experimental investigation is conducted into the lapping of alumina, Ni−Zn ferrite and sodium silicate glass using SiC abrasive to study the effect of process parameters, such as abrasive particle size, lapping pressure, and abrasive concentration, on the surface roughness and material removal rate during lapping. A simple model is developed based on the indentation fracture and abrasive particle distribution in the slurry to explain various aspects of the lapping process. The model provides predictions for the surface roughness,R _a andR _t , on the machined surface and rough estimation for the material removal rate during lapping. Comparison of the predictions with the experimental measurements reveals same order of magnitude accuracy.     

Use of the Roughness Parameters Ssk and Sku to Control Friction—A Method for Designing Surface Texturing

The aim of this work was to show that with the use of the surface roughness parameters S_sk and S_ku we can predict tribological behavior of contact surfaces and use these parameters to plan surface texturing. This article presents a continuation of our research on virtual texturing and experimental work on surface textures in the form of channels. For this investigation, steel samples were laser surface textured in the shape of dimples with different spacings between the dimples and different dimple depths. The experimental results confirmed that the parameters S_sk and S_ku can be used to design the surface texturing, where a higher value of S_ku and more negative S_sk lead to lower friction.     

The factors affecting surface roughness measurements of the machined flat and spherical surface structures – The geometry and the precision of the surface

The quantitative determination of surface roughness is of vital importance in the field of precision engineering. This paper presents an experimental study of the roughness analyses for the flat and spherical surfaces of machined metal in order to compare the roughness data taken from the cloud data produced by the stylus type profilometer and two optical-based measurement instruments, namely the infinite focus microscope and the confocal laser scanning microscope.In this experimental study, the roughness measurements for fifteen flat and six spherical surfaces were repeated six times using three different measurement instruments. Great care was paid to measure the same location for each measurement. For the comparison of the measurement techniques, the same measurement process was applied to the flat and spherical surfaces individually, and the configurations of the measurement instruments (filter type, cut-off, resolution etc.) were synchronized. R_a, two-dimensional (2D) roughness parameter and S_a, three-dimensional (3D) roughness parameter were also compared. The measurement results for the samples having spherical surfaces indicated a considerably high difference in values taken from the stylus profilometer and two optical-based measurement instruments in contrast to those for flat surfaces.     

Analytical Surface Roughness Parameters of a Theoretical Profile Consisting of Elliptical Arcs

The closed‐form solutions of surface roughness parameters for a theoretical profile consisting of elliptical arcs are presented. Parabolic and simplified approximation methods are commonly used to estimate the surface roughness parameters for such machined surface profiles. The closed‐form solution presented in this study reveals the range of errors of approximation methods for any elliptical arc size. Using both implicit and parametric methods, the closed‐form solutions of three surface roughness parameters, R _t , R _a , and R _q , were derived. Their dimensionless expressions were also studied and a single chart was developed to present the surface roughness parameters. This research provides a guideline on the use of approximate methods. The error is smaller than 1.6% when the ratio of the feed and major semi‐axis of the elliptical arc is smaller than 0.5. The closed‐form expressions developed in this study can be used for the surface roughness modeling in CAD/CAM simulations.     

On the prediction of surface roughness in the hard turning based on cutting parameters and tool vibrations

This research work concerns the elaboration of a surface roughness model in the case of hard turning by exploiting the response surface methodology (RSM). The main input parameters of this model are the cutting parameters such as cutting speed, feed rate, depth of cut and tool vibration in radial and in main cutting force directions. The machined material tested is the 42CrMo4 hardened steel by Al₂O₃/TiC mixed ceramic cutting tool under different conditions. The model is able to predict surface roughness of Ra and Rt using an experimental data when machining steels. The combined effects of cutting parameters and tool vibration on surface roughness were investigated while employing the analysis of variance (ANOVA). The quadratic model of RSM associated with response optimization technique and composite desirability was used to find optimum values of cutting parameters and tool vibration with respect to announced objectives which are the prediction of surface roughness. The adequacy of the model was verified when plotting the residuals values. The results indicate that the feed rate is the dominant factor affecting the surface roughness, whereas vibrations on both pre-cited directions have a low effect on it. Moreover, a good agreement was observed between the predicted and the experimental surface roughness. Optimal cutting condition and tool vibrations leading to the minimum surface roughness were highlighted.     

<Emphasis Type="Bold">Prediction of Surface Topomorphy and Roughness in Ball-End Milling</Emphasis>

Milling is today the most effective, productive and flexible-manufacturing method for machining complicated or sculptured surfaces. Ball-end tools are used for machining 3D freeform surfaces for dies, moulds, and various parts, such as aerospace components, etc. Milling data, such as surface topomorphy, surface roughness, non-deformed chip dimensions, cutting force components and dynamic cutting behaviour, are very helpful, especially if they can be accurately produced by means of a simulation program. This paper presents a novel simulation model, the so-called MSN-Milling Software Needle program, which is able to determine the surface produced and the resulting surface roughness, for ball-end milling. The model simulates precisely the tool kinematics and considers the effect of the cutting geometry on the resulting roughness. The accuracy of the simulation model has been thoroughly verified, with the aid of a wide variety of cutting experiments. Many roughness measurements were carried out on workpieces, which were cut using a 5-axis machining centre. The calculated roughness levels were found to be in agreement with the experimental ones. The proposed model has proved to be suitable for determining optimal cutting conditions, when finishing complex surfaces. The software can be easily integrated into various CAD-CAM systems.     

Surface roughness measurement in turning carbon steel AISI 1045 using wiper inserts

Surface roughness of the workpiece is an important parameter in machining technology. Wiper inserts have emerged as a significantly class of cutting tools, which are increasingly being utilized in last years. This study considers the influence of the wiper inserts when compared with conventional inserts on the surface roughness obtained in turning. Experimental studies were carried out for the carbon steel AISI 1045 because of its great application in manufacturing industry. Surface roughness is represented by different amplitude parameters (R_a, R_zD, R_3z, R_q, R_t, R_a/R_q, R_q/R_t, R_a/R_t). With wiper inserts and high feed rate it is possible to obtain machined surfaces with R_a < 0.8 μm (micron). Consequently it is possible to get surface quality in workpiece of mechanics precision without cylindrical grinding operations.     

Prediction of surface roughness of turned surfaces using neural networks

In this study, the prediction of surface roughness heights R_a and R_t of turned surfaces was carried out using neural networks with seven inputs, namely, tool insert grade, workpiece material, tool nose radius, rake angle, depth of cut, spindle rate, and feed rate. Coated carbide, polycrystalline and single crystal diamond inserts were used to conduct 304 turning experiments on a lathe, and surface roughness heights of the turned surfaces were measured. A systematic approach to obtain an optimal network was employed to consider the effects of network architecture and activation functions on the prediction accuracy of the neural network for this application. The reliability of the optimized neural network was further explored by predicting the roughness of surfaces turned on another lathe, and the results proved that the network was equally effective in predicting the R_a and R_t values of the surfaces machined on this lathe as well.     

The Role of Slider/Disk Roughness in 1 Tb/in.2 Magnetic Recording

To achieve 1 Tb/in.² magnetic recording areal density, the head/disk spacing, or the flying height of the slider, has become so small that both the disk surface roughness and the slider air-bearing surface roughness need to be considered. In this region, the intermolecular force and the contact force become more significant due to the roughness of the two surfaces. This article targets two points: 1) slider/disk roughness effects on intermolecular force and 2) slider/disk roughness requirement for 1 Tb/in.² areal density. A probability model is built to simulate the intermolecular force and the contact force, and these two forces are introduced into the modified compressible Reynolds equation governing the air-bearing pressure of the slider. The equation is solved by the finite volume method based on an unstructured triangle-based mesh. The simulation results show that in 1 Tb/in.² areal density magnetic recording the effects of slider/disk roughness on the intermolecular force are negligible. Smaller R _a values will have fewer effects on flying performance.     

Measurement of surface roughness of metals using binary speckle image analysis

In this paper, results from an optical technique for measuring surface roughness using image analysis of speckle pattern images are presented. The technique coined as statistical properties of binary images (SPBI) utilizes the combined effects of speckle and scattering phenomena. The speckle patterns obtained with a He–Ne laser were binarized and examined. The parameters such as bright and dark regions and their ratios obtained from this model to evaluate the surface roughness were compared with the surface roughness parameter R_a obtained from a profilometer. It was found that there is a strong relationship between these parameters and R_a, especially in the range of λ<R_a<2λ where λ is He–Ne laser wavelength. Although, it is a relative method, it has great potential to be used for in-process measurement and automation due to the simplicity of optical system used. The proposed method for the surface roughness combined with a non-contact optical measuring system is applied to samples from 0.5825 to 1.9 μm of steel (CK 45) through CNC face-milling process.     

Modelling the effect of surface roughness factors in the machining of 2024Al/Al2O3 particle composites based on orthogonal arrays

This study presents an experimental investigation of the effects of cutting speed, size and volume fraction of particle on the surface roughness in turning of 2024Al alloy composites reinforced with Al₂O₃ particles. A plan of experiments, based on Taguchi method, was performed machining with different cutting speeds using coated carbide tools K10 and TP30. The objective was to establish a correlation between cutting speed, size and volume fraction of particle with the surface roughness in workpieces. These correlations were obtained by multiple linear regression. The analysis of variance was also employed to carry out the effects of these parameters on the surface roughness. The test results revealed that surface roughness increased with increasing the cutting speed and decreased with increasing the size and the volume fraction of particles for both cutting tools. The average surface roughness values of TP30 cutting tools were observed to be lower than those of K10 tools. For the average surface roughness values of TP30 tool, cutting speed was found to be the most effective factor while the volume fraction of particle was the most effective factor for those of K10 tool. A good agreement between the predicted and experimental surface roughness was observed within a reasonable limit.     

Method of determination of truncation parameters from measured surface profile

The probability density function of the roughness height of a sliding surface is not always Gaussian like that of a truncated surface caused by running-in or mild wear. Therefore, it is important for obtaining contact pressure or frictional characteristics to estimate the truncation level of the non-Gaussian distribution function. This paper presents a method of determination of the two truncation parameters in the truncation model presented by King et al. [Proceedings of the 4th Leeds–Lyon Symposium on Tribology, MEP, London, 1978, p. 333]. The two truncation parameters p and β can be determined by plotting the values of skewness S_k and kurtosis K obtained from a measured profile of surface roughness on the S_k–K diagram calculated with the truncation model for various given values of parameters p and β. The height distributions reproduced by the truncation model with the truncation parameters p and β identified by the present method is in good agreement with the original ones of the measured surfaces.     

Influence of eccentricity on roughness distributions in side milling

In this paper, a numerical model was used based on the tool-piece geometric intersection, which enables the determination of a roughness profile as a function of feed, tool radii and tool eccentricity in side milling processes. Average roughness R_a and peak-to-valley roughness R_t were obtained for a group or family of tools, defined by an average radius value and a standard deviation value of all tool radii. The Monte Carlo method was used to generate N random combinations of radius values for each family, according to a normal distribution. The model was validated by means of experimental tests. For each family of tools, roughness distributions were obtained at different feed values and for different eccentricity values. It was found that the higher eccentricity, the more asymmetrical roughness distributions become.     

Structural and mechanical properties of (Cr,Ni) N single and gradient layer coatings deposited on mild steel by magnetron sputtering

Ternary single and gradient layer (Cr, Ni) N thin films were deposited on the mild steel substrate by unbalanced magnetron sputtering technique in order to evaluate mechanical properties for machine tools and automotive applications. Microstructure, chemical composition, surface morphology and phase analysis were carried out using field emission scanning electron microscopy, energy dispersive X-ray spectroscopy, atomic force microscopy and X-ray diffraction, respectively. Both single and gradient layer of (Cr, Ni) N coatings show a significant increment in mechanical properties such as hardness, adhesion strength and surface roughness along with the reduction of friction coefficient. Mechanical tests revealed that the hardness of the gradient layer increased up to 3.1 times due to the formation of Cr₂N and Ni phase whereas single layer showed the least friction. Single layer CrNiN layer exhibited 27.2% less surface roughness (R_a) in comparison with gradient layer. High values of surface roughness, hardness, thickness and friction could be correlated with high film-to-substrate adhesion (L_c2) for the gradient layer.     

Precision surface finish of the mold steel PDS5 using an innovative ball burnishing tool embedded with a load cell

A load-cell-embedded burnishing tool has been newly developed and integrated with a machining center, to improve the surface roughness of the PDS5 plastic injection mold steel. Either the rolling-contact type or the sliding-contact type was possible for the developed ball burnishing tool. The characteristic curves of burnishing force vs. surface roughness for the PDS5 plastic injection mold steel using the developed burnishing tool for both the rolling-contact type and the sliding-contact type, have been investigated and constructed, based on the test results. The optimal plane surface burnishing force for the PDS5 plastic injection mold steel was about 420 N for the rolling-contact type and about 470 N for the sliding-contact type, based on the results of experiments. A force compensation strategy that results in the constant optimal normal force for burnishing an inclined surface or a curved surface, has also been proposed to improve the surface roughness of the test objects in this study. The surface roughness of a fine milled inclined surface of 60 degrees can be improved from R_a 3.0 μm on average to R_a 0.08 μm (R_max 0.79 μm) on average using force compensation, whereas the surface roughness was R_a 0.35 μm (R_max 4.56 μm) on average with no force compensation.     

In-process surface roughness measurement of bulk metallic glass using an adaptive optics system for aberration correction

Bulk metallic glasses (BMGs) have received extensive attention recently due to amorphous-related extraordinary properties such as high strength, elasticity, and excellent corrosion resistance. In particular, Zr-based BMGs are recognized as a biocompatible material and surface roughness may affect many aspects of cell attachment, proliferation and differentiation. Therefore, this study presents an in-process measurement of surface roughness by combining an optical probe of laser-scattering phenomena and adaptive optics (AO) for aberration correction. Measurement results of six Zr-based BMGs samples with a roughness ranging from 0.06 to 0.98 μm demonstrate excellent correlation between the peak power and average roughness with a determination coefficient (R²) of 0.9974. The proposed adaptive-optics-assisted (AO-assisted) system is in good agreement with the stylus method, and less than 8.42% error values are obtained for average sample roughness in the range of 0.05–0.58 μm. The proposed system can be used as a rapid in-process roughness monitor/estimator to further increase the precision and stability of manufacturing processes for all classes of BMGs materials in situ.