Fractal roughness structures of precision-machined WC-Co- and Inconel 625-coated steel rods

Thermally sprayed WC-Co coatings on steel rods were machined by grinding and turning using diamond tools, and thermally sprayed Inconel 625 coatings on steel rods were machined by turning using various WC tools. Four of these samples were selected for surface characterization using a stylus roughness tester. The results show that precision-machined WC-Co and Inconel-625 surfaces can be identified as self-affine fractals in the stochastic sense within the correlation length. The root-mean-square roughness (R _q ) depends on the scale of cut-off length (=sampling length in this paper) as a power law. The R _q of the machined WC-Co surface was found to be dependent on the scale of cut-off length rather than the scale of evaluation length. The roughness exponent is a very useful parameter and can be used to predict the roughness value of the surfaces at any scale length, if the scale is within the correlation length and provided that one such value of a scale is known. It may be suitable to compare surfaces using roughness exponents, even if different cut-off lengths or scanning scales are used in the measurements to obtain roughness exponents.     

Relation between roughness and processing conditions of AISI 316L stainless steel treated by ultrasonic shot peening

This article assessed the roughness induced by ultrasonic shot peening. Surface properties of AISI 316L steel specimens were modified through the variation of ultrasonic shot-peening parameters (shot material, shot diameter, sonotrode amplitude vibration and coverage). Each surface was characterized using fifty surface roughness parameters and two types of robust Gaussian filter (low pass and high pass) associated with twenty one cut-off lengths. For each type of processing parameter, the most relevant roughness parameter and its corresponding length scale and filter were found. A linear relationship was identified between the four ultrasonic shot-peening parameters and the mean density of furrows with a coefficient of determination equal to 0.97.     

Effect of waterjet peening on aluminum alloy 5005

The present study addresses the effect of waterjet peening parameters on aluminum alloy 5005. The approach was based on the response surface methodology utilizing the Box–Behnken experimental design. Workable empirical models were developed to predict surface roughness (R _a ) and hardness (HV). Increasing the number of passes, pressure, and standoff distance produces a higher surface roughness as well as a higher hardness. On the contrary, increasing the feedrate produces a lower surface roughness and hardness. The developed empirical models for R _a and HV have reasonable correlations between the measured and predicted responses with acceptable coefficients of determinations. A different set of optimum parameters was generated based on different desirability functions for each response. The predicted and the actual responses for optimized R _a and HV are satisfactory with good reliability. It is shown that the models are workable in predicting the responses of R _a and HV in the present research. A proper selection of peening parameters can be formulated to be used in practical works.     

Quantifying surface modification events from scanning force microscopy images

Scanning force microscopy (SFM) is widely used to monitor surfaces and surface modification processes. Some surface modification processes involve the addition (or removal) of discrete entities to (or from) a surface in circumstances where the absolute number of entities is related to some aspect of the process. A two-dimensional surface characterisation parameter – the surface area ratio (SAR) – was previously developed as a means of quantifying such modification and can be readily obtained from SFM images. Simulations have shown that the SAR parameter is superior for quantification purposes to conventional surface roughness parameters such as roughness average S_a, the area equivalent of R_a. Key features of SAR are as follows: its linear dependence with coverage; dependence of linearity slope on coverage mechanism; and its independence from the form, waviness or roughness of the underlying surface. A further advantage of this method is its simplicity given that the SAR parameter is readily obtained from SFM images. Simulations of adsorption onto flat surfaces have been validated using SFM images of polystyrene spheres adsorbed onto mica.     

Measurement of various properties of Southern pine and aspen as function of heat treatment

The objective of this study was to investigate the influence of heat treatment parameters, namely temperature and exposure time on surface roughness, shear strength, hardness and density of Southern pine (Pinus echinata) and aspen (Populus grandidentata) samples. The specimens were exposed to two different temperature levels of 120–200 °C for time spans of 2–8 h. A stylus type portable profilometer was employed to evaluate the surface characteristics of the samples by taking measurements across the grain orientation. Average roughness (R_a), mean peak-to-valley height (R_z) and maximum roughness (R_max) were used to evaluate surface roughness of the samples exposed to various heat treatment schedules. Comten testing unit was also used to determine shear strength and Janka hardness of the control and heat treated specimens. Based on the results of this study Southern pine samples had more enhanced surface quality but lower hardness values than those of aspen specimens with increased temperature and time of heat treatment schedules. It was found that heat treatment adversely affected hardness and shear strength properties of all types of samples. Reduction in shear strength values of Southern pine and aspen samples ranged from 23.31% to 68.59% and from 4.67% to 48.55%, respectively as compared to those of control samples. It appears that influence of heat treatment on all properties of the samples was more pronounced with increasing temperature and exposure time.     

Selection of optimum cutting condition of cobalt-based superalloy with GONNS

Machining of new superalloys is challenging. Automated software environments for determining the optimal cutting conditions after reviewing a set of experimental results are very beneficial to obtain the desired surface quality and to use the machine tools effectively. The genetically optimized neural network system (GONNS) is proposed for the selection of optimal cutting conditions from the experimental data with minimal operator involvement. Genetic algorithm (GA) obtains the optimal operational condition by using the neural networks. A feed-forward backpropagation-type neural network was trained to represent the relationship between surface roughness, cutting force, and machining parameters of face-milling operation. Training data were collected at the symmetric and asymmetric milling operations by using different cutting speeds (V _c), feed rates (f), and depth of cuts (a _p) without using coolant. The surface roughness (Ra_asymt, Ra_symt) and cutting force (Fx_asymt, Fy_asymt, Fz_asymt, Fx_symt, Fy_symt, Fz_symt) were measured for each cutting condition. The surface roughness estimation accuracy of the neural network was better for the asymmetric milling operation with 0.4% and 5% for training and testing data, respectively. For the symmetric milling operations, slightly higher estimation errors were observed around 0.5% and 7% for the training and testing. One parameter was optimized by using the GONNS while all the other parameters, including the cutting forces and the surface roughness, were kept in the desired range.     

Determining the optimum process parameter for grinding operations using robust process

We applied combined response surface methodology (RSM) and Taguchi methodology (TM) to determine optimum parameters for minimum surface roughness (Ra) and vibration (Vb) in external cylindrical grinding. First, an experiment was conducted in a CNC cylindrical grinding machine. The TM using L ₂₇ orthogonal array was applied to the design of the experiment. The three input parameters were workpiece revolution, feed rate and depth of cut; the outputs were vibrations and surface roughness. Second, to minimize wheel vibration and surface roughness, two optimized models were developed using computer-aided single-objective optimization. The experimental and statistical results revealed that the most significant grinding parameter for surface roughness and vibration is workpiece revolution followed by the depth of cut. The predicted values and measured values were fairly close, which indicates (R _Ra ² =94.99 and R _Vb ² =92.73) that the developed models can be effectively used to predict surface roughness and vibration in the grinding. The established model for determination of optimal operating conditions shows that a hybrid approach can lead to success of a robust process.     

Comparative assessment of wiper and conventional ceramic tools on surface roughness in hard turning AISI 4140 steel

This study considers the comparison between the surface roughness criteria (Ra, Rz and Rt) of the wiper inserts with conventional inserts during hard turning of AISI 4140 hardened steel (60 HRC).The planning of experiments was based on Taguchi’s L₂₇ orthogonal array. The response surface methodology (RSM) and analysis of variance (ANOVA) were used to check the validity of quadratic regression model and to determine the significant parameter affecting the surface roughness. The statistical analysis reveals that the feed rate and depth of cut have significant effects in reducing the surface roughness. The optimum machining conditions to produce the best possible surface roughness in the range of this experiment under these experimental conditions searched using desirability function approach for multiple response factors optimization. The results indicate that the surface quality obtained with the wiper ceramic insert significantly improved when compared with conventional ceramic insert is 2.5. Roughness measurements reveal a dependence on CC6050WH tool wear. However, although the wear rises up to the allowable flank wear of value 0.3 mm, roughness Ra did not exceeded 0.9 μm.     

A surface roughness parameter in Hertz contact

The influence of surface roughness on the accuracy with which the Hertz theory of elastic contact predicts the contact pressure and contact area between a sphere and a plane is examined theoretically and experimentally. Statistical theories of surface contact suggest that the influence of surface roughness is governed primarily by a single non-dimensional parameter α defined by $\text{α }\text{σR}\text{a}{}_0{}^2$ where σ is the combined roughness of the two surfaces, R is the radius of the sphere and a₀ is the contact radius for smooth surfaces given by the Hertz theory. Experimental measurements of contact area correlate well with this parameter. Provided that the value of α is less than about 0.05, errors in the application of the Hertz theory due to roughness of the surfaces are not likely to exceed about 7%.     

Sampling effect on contact and transport properties between fractal surfaces

In this work, we are interested in the contact between a self-affine fractal surface pressed against a smooth and perfectly rigid plane. The purpose is to analyze the influence of both sampling interval Δ and sampling length L, on the determination of surface roughness parameters, contact areas and viscous and diffusive flow through the aperture field resulting from the contact under load. To accomplish this analysis, fractal surfaces used in this work are obtained from numerical simulations. Models for synthesizing a fractal surface, computing mechanical deformation of asperities as well as determining viscous and diffusive flow are briefly presented. At the macroscopic scale, viscous and diffusive flow are fully characterized by the transmissivity K and effective diffusivity D tensors, respectively. Results show that fractal dimension D_f and arithmetic roughness Ra are almost insensitive to Δ and L under conditions that are discussed. Contact areas are invariant whatever L and become increasingly sensitive to Δ while decreasing the arithmetic roughness Ra. The impact of L and Δ in the determination of transport properties also increases K and D decrease, i.e. for small Ra and large average contact pressure Pca.     

Assessing the surface roughness of parts after shot hardening

A formula for the surface roughness Rz in the shot hardening of machine parts is derived on the basis of energy relations. Its dependence on the physicomechanical properties of the materials and the geometric and kinematic parameters of the shot is established.     

Influence of surface preparation on roughness parameters,friction and wear

The aim of the present research was to investigate influence of surface preparation on roughness parameters and correlation between roughness parameters and friction and wear. First the correlation between different surface preparation techniques and roughness parameters was investigated. For this purpose 100Cr6 steel plate samples were prepared in terms of different average surface roughness, using different grades of grinding, polishing, turning and milling. Different surface preparation techniques resulted in different R_a values from 0.02 to 7 μm. After this, correlation between surface roughness parameters and friction and wear was investigated. For this reason dry and lubricated pin-on-disc tests, using different contact conditions, were carried out, where Al₂O₃ ball was used as counter-body. It was observed that parameters R_ku, R_sk, R_pk and R_vk tend to have influence on coefficient of friction.     

Experimental extrapolation model for friction and wear of polymers on different testing scales

The friction and wear behaviour for polyoxymethylene homopolymers (POM-H) and polyethylene terephthalate with teflon additives (PET/PTFE) is compared on small-scale cylinder-on-plate tests (50-200 N normal loads) and large-scale flat-on-flat tests (190-3880 kN normal loads). A common parameter to characterise tribological data is the contact pressure×sliding velocity (pv-value), but its use seems restricted to a single testing scale. Four experimental models are presented to extrapolate tribological data from one to another testing scale, based on (i) one single mechanical parameter (normal load or contact pressure), (ii) two mechanical parameters (normal load and sliding velocity), (iii) the contact pressure-sliding velocity model (pv-temperature limit), (iv) macroscopic geometry model. The latter model is most extensive, considering the influences of thermal effects (frictional heat generation and dissipation), sample geometry (geometry factor G) and visco-elastic contact (critical contact pressure p₀). For unfilled polymers, the introduction of macroscopic scaling factors allows for the extrapolation of coefficients of friction obtained on different testing scales. Specific or volumetric wear rates cannot be extrapolated because they strongly depend on the sample geometry, while linear wear rates are in better agreement when considering the transitions between mild wear, softening and melting. For internally lubricated polymers, extrapolation is more difficult. The differences depending on the testing scale are attributed to contact stress concentrations near the sample borders and limited wear debris mobility within large contact areas, promoting a homogeneous film formation onto the polymer surface.     

Performance studies of multilayer hard surface coatings (TiN/TiCN/Al2O3/TiN) of indexable carbide inserts in hard machining: Part-II (RSM,grey relational and techno economical approach)

This paper presents the mathematical modelling and parametric optimization on flank wear and surface roughness based on response surface methodology and grey-based Taguchi method in finish hard turning of AISI 4340 steel (HRC 47 ± 1) using multilayer coated carbide (TiN/TiCN/Al₂O₃/TiN) insert under dry environment. The economical feasibility of utilizing multilayer TiN coated carbide insert has been described. Model adequacy has been checked using correlation coefficients. From main effect, it is evident that, cutting speed is the most significant factor for flank wear followed by depth of cut and feed. Again, feed is the most significant factor for surface roughness followed by cutting speed and depth of cut. The coefficient of determination (R²) is more than 75% for RSM models developed, which shows the high correlation exist between the experimental and predicted values. The experimental vs. predicted values of flank wear and surface roughness (Ra and Rz) are also found to be very close to each other implying significance of models developed. The improvement of grey relational grade from initial parameter combination (d2–f3–v4) to the optimal parameter combination (d1–f1–v3) is found to be 0.3093 using grey relational analysis coupled with Taguchi method for simultaneous optimization of responses. Flank wear (VBc) and surface roughness parameters (Ra and Rz) are decreased 1.9, 2.32 and 1.5 times respectively considering optimal parametric combinations for multi-responses. The calculated total machining cost per part is only Rs. 3.17 due to higher tool life (47 min at their optimal level) of multilayer TiN coated carbide insert. It brings to the reduction of downtime and increases the savings.     

Multilayer thin film CrN coating on aerospace AL7075-T6 alloy for surface integrity enhancement

Chromium nitride (CrN) coating has emerged as a new alternative in machining applications. CrN has good thermal stability, low deposition temperature, and excellent wear and corrosion resistance. However, no precise information exists yet regarding the ideal coating parameter conditions that lead to higher surface integrity. For this reason, an optimization study is desired—a study on the parameters of CrN coating on aerospace Al7075-T6 alloy using physical vapor deposition magnetron sputtering. The present research work investigates the effects of temperature as well as nitrogen flow rate and DC power on coated samples’ surface hardness, adhesion, surface roughness, and microstructure. To carry out the investigation, the Taguchi optimization method with L₁₆ (3⁴) orthogonal array was applied. However, to obtain optimum parameters for superior surface integrity, signal/noise (S/N) response analysis method was employed. Finally, confirmation tests with the best parameter combinations attained in the optimization process were carried out to demonstrate the progress made. Ultimately, surface hardness of coated Al7075-T6 was enhanced by 15.33 %, adhesion by 24.3 %, and surface roughness by 7.22 %.     

The effects of intrinsic and extrinsic acids on nanofilled and bulk fill resin composites: Roughness,surface hardness,and scanning electron microscopy analysis

The objective of this study was to examine the effects of extrinsic or intrinsic acids on nanofilled and bulk fill resin materials in vitro. A total of 90 disks were prepared using dental restorative material (Filtek Z350XT, GrandioSO, Filtek Bulk Fill, X‐tra fil). Thirty disks of each material were sub‐divided into three groups (n = 10) that were immersed for 7 days in deionized water (DW), 5% citric acid (CA—pH 2.1), or 0.1% hydrochloric acid (HCl—pH = 1.2). Surface hardness and roughness (stylus profilometer by R_a parameter) analysis were performed before and after immersion. Morphological changes were evaluated by scanning electron microscopy. The data were analyzed by two‐way ANOVA and Tukey's test (α = 0.05). All tested materials did not show significant differences in the effects of the DW, CA, or HCl solutions on surface roughness (p = .368). Likewise, the hardness loss was not affected by the solutions tested (p = .646), but there was a difference in the resin type (p = .002). Filtek Bulk Fill resin hardness was less affected, while Filtek Z350XT and GrandioSO presented the most hardness loss after 7 days of solution immersion. In terms of this experimental study, the results demonstrate the effectiveness of the mechanical properties (roughness and hardness surface) of nanofilled and bulk fill resin materials to resist erosion from extrinsic and intrinsic acids, therefore being potential candidates for dental applications.     

Noncontact roughness measurement of turned parts using machine vision

The surface roughness of turned parts is usually measured using the conventional stylus type instruments. These instruments, although widely accepted, have several limitations such as low speed measurement, contacting in nature, requiring vibration-free environment, etc. Machine vision methods of roughness measurement are being developed worldwide due to their inherent advantages, including noncontact measurement, high information content, rapid measurement, and surface measurement capability. In past research, area-based light scattering method and gray scale line intensity measurement have been developed for roughness assessment using machine vision. Such methods, however, produced redundant data when applied to measure roughness of turned parts. In this paper, an alternative method of roughness measurement using the 2-D profile extracted from an edge image of the workpiece surface is proposed. Comparison with a stylus type instrument shows a maximum difference of 10% in the measurement of average roughness R _a using the vision method.     

Effect of electrode material in wire electro discharge machining characteristics of Ti50Ni50−xCux shape memory alloy

TiNiCu alloy belongs to new class of shape memory alloy (SMA), which exhibits superior properties like shape memory effect, super elasticity and reversible martensitic transformation phase and thus find broad applications in actuators, micro tools and stents in biomedical components. Even though, SMA demonstrates outstanding property profile, traditional machining of SMAs is fairly complex and hence non-traditional machining like wire electric discharge machining (WEDM) has been performed. Hence, there is a need to investigate the WEDM performance characteristics of shape memory alloys due to excellent property profile and potential applications. In the present investigation, various machining characteristics like material removal rate (MRR), surface roughness, surface topography and metallographic changes have been studied and the influence of wire material on TiNiCu alloy machining characteristics has also been evaluated through ANOVA. Ti₅₀Ni_50−xCu_{x=10, 20} was prepared by vacuum arc melting process. The proposed alloy as-cast material exhibits austenite property (B2 phase) and having higher hardness when compared to TiNi alloy. The investigation on WEDM of Ti₅₀Ni_50−xCu_x alloy reveals that the machining parameters such as servo voltage, pulse on time and pulse off time are the most significant parameters affecting MRR as well as surface roughness using both brass and zinc coated brass wires. However, machining with zinc coated brass wire yields reduced surface roughness and better MRR and also produces less surface defects on the machined surface of Ti₅₀Ni_50−xCu_x alloys.     

Research on surface integrity of grinding Inconel718

Inconel718 is widely used in the aerospace industry; the finished surface quality has significant effect on service performance of component. The surface integrity in grinding Inconel718 respectively by using a vitrified bond single alumina (SA) wheel and a resin cubic boron nitride (CBN) wheel were investigated. First, effects of different grinding parameters on grinding temperature and grinding force and grinding chips feature by using a SA and a CBN wheel respectively were investigated. Then, the surface roughness and topography by using a SA and a CBN wheel through single factor experiment were compared, and in the grinding parameters range of the present study, the better surface can be obtained by a SA wheel. Finally, surface integrity by using a SA wheel and the different grinding depth was studied and analyzed by the grinding temperature and the grinding force. It was possible to conclude that better surface can be achieved by using a SA, and taking a _p?=?0.005 mm, v _w?=?16 m/min, v _s?=?25 m/s for grinding Inconel718. In this grinding case, the surface roughness was Ra0.112 μm, the surface residual stress was +700Mpa, and the surface hardness was 440 HV; the depth of residual stress layer was 40～60 μm, the depth of softened layer was 30～40 μm and the depth of plastic deformation layer was 10～15 μm.     

Surface roughness and cutting forces modeling for optimization of machining condition in finish hard turning of AISI 52100 steel

An experimental investigation was conducted to analyze the effect of cutting parameters (cutting speed, feed rate and depth of cut) and workpiece hardness on surface roughness and cutting force components. The finish hard turning of AISI 52100 steel with coated Al₂O₃ + TiC mixed ceramic cutting tools was studied. The planning of experiment were based on Taguchi’s L₂₇ orthogonal array. The response table and analysis of variance (ANOVA) have allowed to check the validity of linear regression model and to determine the significant parameters affecting the surface roughness and cutting forces. The statistical analysis reveals that the feed rate, workpiece hardness and cutting speed have significant effects in reducing the surface roughness; whereas the depth of cut, workpiece hardness and feed rate are observed to have a statistically significant impact on the cutting force components than the cutting speed. Consequently, empirical models were developed to correlate the cutting parameters and workpiece hardness with surface roughness and cutting forces. The optimum machining conditions to produce the lowest surface roughness with minimal cutting force components under these experimental conditions were searched using desirability function approach for multiple response factors optimization. Finally, confirmation experiments were performed to verify the pertinence of the developed empirical models.