Surface Roughness Parameters Ra Research Articles

Study of Surface Roughness by StylusProfilometer and Binary Laser Speckle B/DCounting Techniques

In this paper, surface roughness measurements by non contact method of Binary Speckle Pattern (BSP) and contact method of stylus profilometer have been presented. When an optically rough surface is illuminated with a highly coherent source of Laser, the granular bright and dark pattern known as speckle is observed. Intensity of the Speckle image depends on the surface roughness and carries information about it. The speckle images obtained by He- Ne laser with CCD camera were binarized and examined. To evaluate the surface roughness, pixel ratios of bright and dark regions (B/D counting) of various speckle images of different surface roughness are used. The results are compared with the surface roughness parameter Ra obtained from stylus profilometer.

Fractal analysis of surface topography in ground monocrystal sapphire

The surface characterization of ground monocrystal sapphire is investigated by fractal analysis method. A serial of ground sapphire surfaces in ductile removal and brittle removal mode are obtained by grinding experiments, and their three dimensional (3D) and two dimensional (2D) fractal dimensions are calculated and analyzed by box-counting methods. The 3D surface fractal dimension Ds shows a negative correlation with the surface roughness parameter Ra and is sensitive to the ground surface defects. For the ground surface with larger fractal dimension Ds, its micro-topography is more exquisite with minor defects. Once the fractal dimension Ds become smaller, deep cracks and pronounced defects are exhibited in ground surface. Moreover, the material removal mode can be implied from the distribution of 2D cross-sectional profile fractal dimension DL. The workpiece surface generated in ductile removal mode has high surface quality with high 2D and 3D fractal dimensions. This study indicates that the box-counting fractal analysis is an effective method to evaluate ground sapphire surface comprehensively.

Comparison of Experimental Stamping Punch Machinability Made out of Unconventional Materials

The paper describes experimental stamping punch production from the view machinability and quality of stamping punch active surfaces. The tin car-body stamping punch has been chosen as a subject of experimental work. Two unconventional materials such as Textit J and Fibroflex 5 have been chosen for stamping punch. Milling strategies have been proposed, optimized and verified using CAM software SolidCAM considering the maximum Scallop Height. The final surface quality on selected areas of stamping punch shaped surface has been evaluated by surface roughness parameters Ra and Rz. These have been compared to Scallop Height set in CAM software. Manufactured areas on shaped surface were optically evaluated as well.

Influence of Some Factors on Surface Roughness Parameters at Electrical Discharge Machining

There are various electrical discharge machining techniques and experimental researches could be necessary in order to establish the operating conditions for an optimal machining process. Some theoretical considerations concerning the process of generating the surface asperities as a consequence of the electrical discharge machining process were elaborated. Experimental method was applied in order to evaluate influence exerted by some input factors (pulse on time, pulse off time, average intensity of electric current) on certain surface roughness parameters (Ra, Rz, Ry and Rq). One developed an experimental research by using a copper tool electrode and a workpiece made of high speed steel, in accordance with the requirements specific to a complete factorial experiment with three independent variables at three levels. A ram electrical discharge machine was used as machining equipment. One measured the surface roughness parameters specific to the machined surfaces. Empirical mathematical models of type power functions were established by using the method of least squares.

Investigations on Hard Turning Using Coated Carbide Insert: Grey based Taguchi and Regression Methodology

The present deals with some investigations on surface roughness during hard machining of EN 24 steel with the help of coated carbide insert. The experiment has been done under dry conditions. The optimization of process parameters have been done using Grey based Taguchi approach. Also the prediction models have been developed using regression analysis for surface roughness and adequacy has been checked. Good surface quality of roughness about 0.42 microns is obtained in hard machining. Using grey-based Taguchi approach, the optimal parametric combination for surface quality characteristics (Ra and Rz) have been obtained to be depth of cut: 0.4mm, feed: 0.04mm/rev and cutting speed: 130 m/min respectively. Feed is considered to be the most dominant parameter for both surface roughness parameters Ra and Rz. The prediction models have high correlation coefficient (R2 = 0.993 and 0.934). This is evident to be better fitting of the model and found to be high significance.

Adaptive Control System to Assist the Surface Workpiece Quality when Drilling

Article deals with design of adaptive control system for drilling process of aerospace critical components. The system proposed in this paper is directed towards real the time control of surface roughness parameter Ra. Proposed model for monitoring and control consists of surface roughness prediction system and decision making subsystem. The artificial neural network was employed to calculate surface roughness parameter Ra through of process monitoring indices such as torque Mz, force Fz, power P and cutting conditions feed f, cutting speed vc. Test samples were nickel based super alloy Udimet 720 used as a basic constructional material of discs for gas turbine engines.

Grey Fuzzy Multiobjective Optimization of Process Parameters for CNC Turning of GFRP/Epoxy Composites

For obtaining close fits and tolerances, certain amount of machining has to be carried out on GFRP (Glass Fibre Reinforced Plastic) composites, produced by primary manufacturing processes. A number of cylindrical GFRP composite parts are finish machined by turning. These include axles, bearings, spindles, rolls and steering columns. There is always a tradeoff between quality and productivity during machining operations. Hence it becomes essential to evaluate the optimal cutting parameters setting in order to satisfy these opposing requirements. In this study, a hybrid multiobjective optimization algorithm involving grey and fuzzy coupled with Taguchi methodology is used. Four process parameters, each at three levels are selected for the study viz. cutting tool nose radius, cutting speed, feed rate and depth of cut. Surface roughness parameter Ra, tangential cutting force Fz and material removal rate MRR are the chosen output performance measures. The experimental plan is laid according to Taguchi's orthogonal array L27. Woven fabric based GFRP/ Epoxy tubes produced using hand layup process are finish turned using PCD cutting tool. Grey relational coefficients of the three performance measures are converted into a single multi performance characteristics index (MPCI) using Mamdani type fuzzy inference system. This MPCI is then optimized using Taguchi analysis. The parameter combination of A2B1C1D3, i.e. tool nose radius of 0.8mm, cutting speed of 120 m/min, feed rate of 0.05mm/rev and depth of cut of 1.6mm, is evaluated as the optimum combination. The confirmatory experiment at these settings gave maximum value of MPCI, validating the results.

Experimental Investigation and Optimization in Edge Milling of NEMA G-11 GFRP/Epoxy Composites

NEMA (National Electrical Manufacturers Association)standard G-11, glass fiber reinforced plastic (GFRP /Epoxy) composite is an excellent insulating material for transformer and inductive appliances. This studyfocuses on an effective approach for the optimization of edge milling parameters with multiple performance characteristics based on Grey-Taguchi method. L18 orthogonal array has been used for planning the experiments. Four cutting parameters selected for this investigation are milling strategy, spindle speed, feed rate and depth of cut. Resultant machining force F, delamination factor DF and surface roughness parameter Ra are the chosen output performance measures. From the response table of the average grey relational grade (GRG), it is found that the largest value of the GRG is for the up milling, spindle speed is of 1500rpm, feed rate of 200mm/min and depth of cut 0.2mm. Milling strategy and feed rate has the most dominant role in influencing the surface roughness.

Prediction of surface roughness in turning of PEEK cf30 by using an artificial neural network

Surface roughness parameters Ra and Rt are mostly used as an index to determine the surface finish quality in the process of machining. Because of the strong nonlinear character of relationships between the process inputs and outputs, it is difficult to accurately estimate roughness characteristics by using traditional modeling techniques. In this work, accurate prediction of the Ra and Rt values during machining of reinforced poly ether ether ketone (PEEK) CF30 with TiN coated tools is achieved. The modeling is performed by using artificial neural network approach to represent the complex relationships between cutting conditions and surface roughness parameters. The input cutting parameters include cutting speed, depth of cut and feed rate. The network was trained with pairs of inputs and outputs datasets generated by machining experimental results that were obtained according to a full factorial design of experiment table. Predictions of the ANN based model were found to fit experimental data very well with a correlation coefficient as high as 99%. Complementary results that were not used during derivation of the ANN model have enabled one to assess the validity of the obtained predictions.

EFFECT OF GEOMETRY ON THE PREPARATION OF FATIGUE SPECIMENS WITH PREDETERMINED SURFACE ROUGHNESS

In the present study, the applicability of the design of experiments (DOE) approach to the design of the long fatigue specimens of austenitic stainless steels with controlled surface roughness has been studied. The response surface models which can predict the surface roughness parameters Ra and Rz as a function of the final cutting conditions (axial feed rate and radial cutting depth) of the lathe were obtained by the analysis of variance (ANOVA) for the experimental data. It was found that the surface roughness parameters Ra and Rz obtained by the model prediction were in good accordance with the experiments. However, special care should be taken to minimise the specimen deflection generated during the machining process. It was concluded that the response surface models obtained were applicable to design the long fatigue specimens with controlled surface roughness.

A Novel <i>In Situ</i> Roughness Measurement Based on Spatial Average Analysis of Binary Speckle Image

This study proposes a novel optical technique and method for in-situ roughness measurement. The speckle image was obtained by illuminating a laser beam and the reflected laser pattern image from a surface was binarizd and examined. The intensity distribution of binary image utilizes the combined effects of speckle and scattering phenomena. A new parameter of intensity distribution of binary image, Sd BD has been proposed and the surface roughness parameter Ra of machined surfaces (ground) were correlated experimentally. Measurement results demonstrate an excellent correlation between the SdBD and Ra with correlation coefficient of 0.9706. The practicality of the proposed method to in-situ roughness measurement was applied to six samples from roughness Ra 0.2 to 6.25μm (0.3 λ and 10 λ, where λ is diode laser wavelength) of steel through grinding process.

Some considerations regarding finishing by abrasive flap wheels

The diminishing of the surface roughness of a metallic part can be performed by using various finishing methods, polishing by means of abrasive flap wheels being one of them. There are several factors that influence the roughness of surfaces finished by means of abrasive flap wheels. When polishing external cylindrical surfaces by means of abrasive flap wheels, the surface roughness can be changed more easily if the following elements are modified: the peripheral speed of the workpiece and of the abrasive flap wheel, the speed of the longitudinal feed, and the grit size of the abrasive material. Experimental research has allowed for the establishment of power-type functions which highlight the influence exerted by the above-mentioned factors on the size of the surface roughness parameters Ra, RS, RSm, Rku. Analyses of the experimental results have shown that, in the case of the Ra roughness parameter, from among the range of interactions of orders 2 and 3, only the interaction between the rotation speed of the abrasive flap wheel and the speed of the longitudinal feed seems to be significant.

Performance parameters of TiN — AlN ceramic end seals frictionally coupled to steel

Performance parameters (friction moment, temperature in the friction zone, and surface roughness parameter Ra) of friction couples 50% TiN + 50% AlN (composite 1 ) steel and 25% TiN + 75% AlN (composite 2 ) used as end seal components of belt conveyor rollers have been determined experimentally.

Burr formation in face milling of cast iron with different milling cutter systems

Two face milling cutter systems, both with PCBN (polycrystalline cubic boron nitride) tools, were used to study burr formation in high-speed machining of grey cast iron under various cutting conditions. Surface roughness parameters Ra and Ri, tool life (based on flank wear, VBmax) and burr formation (length of the burr, h) were recorded and used for comparing machining performance. The best performance in terms of tool life and surface roughness was obtained with the milling cutter system consisting of 24 teeth and 24 square wiper inserts. Machining with this cutter configuration produced acceptable surface roughness values, well below the rejection criterion, after machining a batch of 3000 motor blocks in addition to achieving a significant reduction in the burr length.