Values Of Material Removal Rate Research Articles

Study of effect of nanofluid concentration on response characteristics of machining process for cleaner production

With the ever-increasing concern for reducing environmental pollution and waste minimization, “green manufacturing” has been successful to draw sufficient amount of attention towards it. Minimum Quantity Lubrication (MQL) is one such technique that has revolutionized the manufacturing industry by not only reducing the amount of working fluid dramatically but also enhancing cutting tool life and reducing material costs. Past studies have reported the use of experiments in MQL based manufacturing but limited computational modeling for optimizing the process parameters Based on the past experimental procedure of machining process (micro-drilling), a computational framework such as Adaptive Neuro Fuzzy Inference System (ANFIS) and Genetic Programming (GP) in quantification of three response characteristics (torque, thrust forces and material removal rate (MRR) is proposed. The performance analysis based on the cross-validation, error metrics, curve fitting and hypothesis tests reveals that among the two models, the GP models have performed better. 2-D and 3-D surface analysis were performed to validate the robustness of the models. Among the three response characteristics, It was found that the nanofluid concentration influences torque the most, which is an important aspect for power consumption. At nanofluid concentration values of 1.4 and 4, the minimum values of torque and thrust forces is achieved respectively. When drill diameter is minimum and the spindle speed is maximum, the values of torque, thrust forces and MRR is the lowest. Thus, the feed rate, nanofluid concentration and drill diameter are most critical for obtaining higher MRR and lower values of torque and thrust force, thus enabling cleaner production and environment.

Experimental investigation of machinability characteristics in Al-TiB2metal matrix composite (MMC) based on the Taguchi method with fuzzy logics

Purpose– The purpose of this paper is to develop a mathematical model for metal removal rate and surface roughness through Taguchi method and analyse the influence of the individual input machining parameters (cutting speed, feed rate, helix angle, depth of cut and wt% on the responses in milling of aluminium-titanium diboride metal matrix composite (MMC) with solid carbide end mill cutter coated with nano-crystals.Design/methodology/approach– Taguchi OA is used to optimise the material removal rate (MRR) and Surface Roughness by developing a mathematical model. End Milling is used to create slots by combining various input parameters. Five factors, three-level Taguchi method is employed to carry out the experimental investigation. Fuzzy logic is used to find the optimal cutting factors for surface roughness (Ra) and MRR. The factors considered were weight percentage of TiB2, cutting speed, depth of cut and feed rate. The plan for the experiments and analysis was based on the Taguchi L27 orthogonal array with five factors and three levels. MINITAB 17 software is used for regression, S/N ratio and analysis of variance. MATLAB 7.10.0 is used to perform the fuzzy logics systems.Findings– Using fuzzy logics, multi-response performance index is generated, with which the authors can identify the correct combination of input parameters to get higher MRR and lower surface roughness value with the chosen range with 95 per cent confidence intervals. Using such a model, remarkable savings in time and cost can be obtained.Originality/value– Machinability characteristics in Al-TiB2MMC based on the Taguchi method with fuzzy logic has not been analysed previously.

Evaluation of Surface Roughness and Material Removal Rate in End Milling of Complex Shape

In this work, an attempt has been made to analyze the influence of various machining input parameters of CNC end milling process viz. cutting speed, feed rate and depth of cut on machining output variables (surface roughness and material removal rate) during machining complex shape of copper. Three different levels of input parameters were planned as per Taguchi's L9 orthogonal array. The parameters are optimised from analysis of mean (ANOM). Analysis of variance (ANOVA) was employed to investigate the effect of machining parameters on the variables. Results of this study indicate that the depth of cut has the most significant effect on Ra having percentage contribution of 71.06% followed by feed rate and cutting speed having percentage contribution of 23.22% and 2.12% respectively. For material removal rate, it is observed that the percentage contribution of feed rate is maximum i.e. 68.58% followed by depth of cut and cutting speed having percentage contribution of 22.13% and 7.52% respectively. Also, the results revealed that optimum combination of machining parameters which resulted in optimum value of the surface roughness is A3B1C2 i.e. cutting speed of 6000 rpm, feed rate of 500 mm/tooth and depth of Cut of 0.06 mm. Similarly, optimum combination of machining parameters which resulted in optimum value of material removal rate is A1,B3C3 where the values for cutting speed, feed rate and depth of cut are 2000 rpm, 1500 mm/tooth and 0.08 mm respectively.

Investigation of machining characteristics in rotary ultrasonic machining of alumina ceramic

ABSTRACTAlumina ceramic is well documented as a much-demanded advanced ceramic in the present competitive structure of manufacturing and industrial applications owing to its excellent and superior properties. The current article aimed to experimentally investigate the influence of several process variables, namely: spindle speed, feed rate, coolant pressure, and ultrasonic power, on considered machining characteristics of interest, i.e., chipping size and material removal rate in the rotary ultrasonic machining of alumina ceramic. Response surface methodology has been employed in the form of a central composite rotatable design to design the experiments. Variance analysis testing has also been performed with a view to observing the consequence of the considered parameters. The microstructure of machined rod samples was evaluated and analyzed using a scanning electron microscope. This analysis has revealed and confirmed the presence of plastic deformation that caused removal of material along with brittle fractures in rotary ultrasonic machining of alumina ceramic. The validity and competence of the developed mathematical model have been verified with test results. The multi-response optimization of machining responses (material removal rate and chipping size) has also been attempted by employing a desirability approach, and at an optimized parametric setting the obtained experimental values for material removal rate and chipping size were 0.4166 mm3/s and 0.5134 mm, respectively, with a combined desirability index value of 0.849.

Effect on crystalline structure of AISI M2 steel using tungsten–thorium electrode through MRR, EWR, and surface finish

To investigate on the crystalline structure of AISI M2 steel by using tungsten–thorium electrode in electrical discharge machining (EDM) process was studied. Furthermore, the investigation were carried out for finding the value of material removal rate (MRR), electrode wear rate (EWR) and surface roughness (SR) of tool steel material depending upon three variable input process parameters. On the basis of weight loss, the value of MRR and EWR were calculated at optimized process parameter. Subsequently, surface topography of the processed material were examined through different characterization techniques like scanning electron microscopy (SEM), Optical surface profiler (OSP) and Atomic force microscopy (AFM), respectively. In XRD study, broadening of the peak was observed which confirmed the change in material properties due to the homogeneous dispersion of the particles inside the matrix. Lowest surface roughness and MRR of 0.001208mg/min was obtained. Minimum surface roughness was obtained 1.12μm and 2.18427nm by OSP and AFM study, respectively. Also, minimum EWR was found as 0.013986mg/min.

Experimental investigation and optimization of EDM process parameters for machining of aluminum boron carbide (Al–B4C) composite

ABSTRACTThis study investigates the effect of electric discharge machining (EDM) process parameters [current, pulse-on time (Ton), pulse-off time (Toff) and electrode material] on material removal rate (MRR), electrode wear rate (EWR) and surface roughness (SR) during machining of aluminum boron carbide (Al–B4C) composite. This article also summarizes a brief literature review related to aluminum metal matrix composites (Al-MMCs) based on different process and response parameters, work and tool material along with their sizes, dielectric fluid and different optimization techniques used. The MMC used in the present work is stir casted using 5% (wt) B4C particles of 50 micron size in Al 6061 metal matrix. Taguchi technique is used for the design of experiments (L9-orthogonal array), while the experimental results are analyzed using analysis of variance (ANOVA). Response table for average value of MRR, EWR and SR shows that current is the most significant factor for MRR and SR, while electrode material is most important for EWR. ANOVA also confirms similar results. It is also observed that the optimum level of process parameters for maximum MRR is A3B1C3D3, for minimum EWR is A1B2C3D1, and for SR is A1B3C3D3.

Evaluation of MRR after WEDM Depending on the Resulting Surface

The aim of this article is to evaluate the material removal rate (MRR) after wire electrical discharge machining (WEDM) and subsequent characteristics of the machined surface. For efficient processing, the aim is to achieve the highest MRR values but with regard to the preserving of required quality and functional characteristics of the surface. During the electrical discharge of material removal craters occur on the workpiece surface and due to diffusion process here premixed and melted material of fodder and wire electrodes cling. As a result of melting and fast cooling down of the workpiece material microcracks may occur on its surface.

Electrical discharge machining of the AISI D6 tool steel: Prediction and modeling of the material removal rate and tool wear ratio

In this investigation, response surface method was used to predict and optimize the material removal rate and tool wear ratio during electrical discharge machining of AISI D6 tool steel. Pulse on time, pulse current, and voltage were considered as input process parameters. Furthermore, the analysis of variance was employed for checking the developed model results. The results revealed that higher values of pulse on time resulted in higher values of material removal rate and lower amounts of tool wear ratio. In addition, increasing the pulse current caused to higher amounts of both material removal rate and tool wear ratio. Moreover, the higher the input voltage, the lower the both material removal rate and tool wear ratio. The optimal condition to obtain a maximum of material removal rate and a minimum of tool wear rate was 40μs, 14A and 150V, respectively for the pulse on time, pulse current and input voltage.

Surface integrity and removal mechanism in grinding sapphire wafers with novel vitrified bond diamond plates

ABSTRACTIn order to improve machining efficiency of sapphire wafer machining using the conventional loose abrasive process, fixed-abrasive diamond plates are investigated in this study for sapphire wafer grinding. Four vitrified bond diamond plates of different grain sizes (40 µm, 20 µm, 7 µm, and 2.5 µm) are developed and evaluated for grinding performance including surface roughness, surface topography, surface and subsurface damage, and material removal rate (MRR) of sapphire wafers. The material removal mechanisms, wafer surface finish, and quality of the diamond plates are also compared and discussed. The experiment results demonstrate that the surface material is removed in brittle mode when sapphire wafers are ground by the diamond plates with a grain size of 40 µm and 20 µm, and in ductile mode when that are ground by the diamond plates of grain sizes of 7 µm and 2.5 µm. The highest MRR value of 145.7 µm/min is acquired with the diamond plate with an abrasive size of 40 µm and the lowest surface roughness values of 3.5 nm in Ra is achieved with the 2.5 µm size.

An Investigation on surface integrity in EDM Process with a Copper Tungsten Electrode

One of the most important non- conventional machining methods is Electrical Discharge Machining (EDM). The present study performs the EDM process with copper–tungsten electrode of diameter 2mm to establish the influence of the EDM parameters on various aspects of the surface integrity of AISI 4340 steel. The residual stress induced by the EDM process is measured using the X-rays diffraction method. The experimental results reveal that the values of material removal rate (MRR), surface roughness (SR), and induced residual stress tend to increase at higher values of pulse current and pulse-on duration. However, for extended pulse-on duration, it is noted that the MRR, SR, and surface crack density all decrease. A smaller pulse current (i.e. 1A) tends to increase the surface crack density, while a prolonged pulse-on duration (i.e. 30μs) widens the opening degree of the surface crack, thereby reducing the surface crack density. It is determined that the residual stress can be controlled effectively by specifying an appropriate pulse-on duration.

Modelling and process optimisation for wire electric discharge machining of metal matrix composites

This paper describes the process modelling and optimisation of wire electric discharge machining (WEDM) of SiCp/6061 Al metal matrix composite (MMC) through response surface methodology (RSM) and artificial neural network (ANN) approach. The experiments were planned and carried out based on the design of experiments (DOE). Four WEDM input process parameters namely servo voltage (SV), pulse-on time (TON), pulse-off time (TOFF) and wire feed rate (WF) were chosen as machining process parameters. Two response criteria [i.e., material removal rate (MRR) and cutting width (kerf)] were selected during optimisation. The analysis of variance (ANOVA) was carried out to study the effect of process parameters on response variables and models have also been developed for response parameters. RSM was used to determine the optimal values of input process parameters maximum MRR and minimum kerf. The output of the RSM model was used to develop the ANN predictive model. ANN model was validated through experimentation conducted at the RSM optimal setting of input parameters and results show that ANN predictive model and the actual experimental observations are very close to each other which give a good agreement between the two. Comparisons of ANN models and RSM models show that ANN predictions are more accurate than RSM predictions.

Deep micro-hole drilling of Hardox 500 by electro-discharge machining

Abstract In this study, micro-size drillability of Hardox 500 was investigated by the electro-discharge machining (EDM) method. For this purpose, holes were drilled by using different machining parameters (discharge current, electrode rotational speed, dielectric spray pressure) and the effect of these parameters on machining performance and hole profile was specified. At the end of the tests, it was detected that discharge current and electrode rotational speed increased material removal rate (MRR), electrode wear rate (EWR) and hole dimensional error (DE) whereas dielectric spray pressure increased the MRR values and decreased the EWR and DE values.

Selection of dry drilling parameters for minimal burr size and desired drilling quality

The drilling of metals produces undesired raised material which is defined as burr. It is important to minimize the burr size by modifying the drill geometry or selection of drilling parameters. Although, selection of optimal drilling parameters can be minimize the burr size, but it may be increases the overcut or decreases the material removal rate (MRR). In this paper, drilling parameters have been selected for minimal burr size and desired overcut and MRR. Four adaptive neuro fuzzy inference system (ANFIS) models have been designed based on experimental observation in drilling of copper. Outputs of ANFIS models are burr height, burr thickness, burr type and overcut of hole; While input parameters of drilling process are cutting speed, tool diameter and ratio of feed rate to diameter. Then the particle swarm optimization method has been used to select the optimum condition of input parameters to minimize the burr size in desired value of overcut and MRR. Results showed that the proposed models can be predict the outputs well and they can be used as adequate predictors and optimizer for achieving the drilling parameters which gives a type of burr with low value of burr height and burr thickness with desirable overcut and MRR.

Electric Discharge Machining of Cryo-Treated BeCu Alloys

Beryllium copper possesses high strength which produces severe problem of surface integrity and tool wear during machining by conventional machining process. Electrical discharge machining is a practically viable option to solve this problem. The present study investigates the effect of cryogenic treatment of work part along with gap current and external magnetic field on material removal rate (MRR) and tool wear rate (TWR). Blind 3 mm square holes were produced using electrolytic copper tool electrode to machine cryo-treated BeCu and untreated BeCu. Gap current is varied from 8 A to 16 A in a step of 2 amperes and magnetic strength is varied from 0 to 0.496 T in a step of 0.124 T. Based on the experimental results it was found that MRR increases with increase in gap current for both untreated BeCu and treated work part. Plotted graphs of cryo-treated work part showed high values of MRR in comparison to untreated work part. TWR increases for both treated and untreated BeCu work part with increase in gap current. But the TWR was less for cryo-treated work part in comparison to untreated work part. MRR and TWR increases for both treated and untreated BeCu work part with increasing magnetic strength. Again the MRR was found higher with lower TWR for treated workpiece with regard to magnetic strength. Thus it can be concluded that cryogenic-treatment with magnetic strength improves EDM machining efficiency.

Investigation of Surface Roughness and Material Removal Rate for High Speed Micro End Milling on PMMA

Micro end milling is one of the most important micromachining process and widely used for producing miniaturized components with high accuracy and surface finish. This paper present the influence of three micro end milling process parameters; spindle speed, feed rate, and depth of cut on surface roughness (Ra) and material removal rate (MRR). The machining was performed using multi-process micro machine tools (DT-110 Mikrotools Inc., Singapore) with poly methyl methacrylate (PMMA) as the workpiece and tungsten carbide as its tool. To develop the mathematical model for the responses in high speed micro end milling machining, Taguchi design has been used to design the experiment by using the orthogonal array of three levels L18 (21×37). The developed models were used for multiple response optimizations by desirability function approach to obtain minimum Ra and maximum MRR. The optimized values of Ra and MRR were 128.24 nm, and 0.0463 mg/min, respectively obtained at spindle speed of 30000 rpm, feed rate of 2.65 mm/min, and depth of cut of 40 μm. The analysis of variance revealed that spindle speeds are the most influential parameters on Ra. The optimization of MRR is mostly influence by feed rate. Keywords:Micromilling,surfaceroughness,MRR,PMMA

Dependence between Workpiece Material Hardness and Face Lapping Results of Steel C45

The high demands required today by manufacturing engineers for machine parts and tools necessitate very precise machining. The finishing processes are an important perspective to be considered today for meeting the goals like parallelism, tolerances, flatness, and smooth surface. These processes are high-precision abrasive processes used to generate surfaces of desired characteristic such as geometry, form, tolerances, surface integrity, and roughness characteristics. A leading importance in this perspective has the lapping process. It leads to a surface with low roughness and high precision. The topographical structure resulting from lapping is very advantageous in sliding joints, because of the high ability of lubricant retention, as well as in nonsliding joints because of the high load-carrying ability. Many materials can be lapped, including glass, ceramic, plastic, metals and their alloys, sintered materials, satellite, ferrite, copper, cast iron, steel, etc.This paper reports the observations of steel C45 elements lapping process results. Workpieces were rollers with diameter 17 mm and height 10 mm placed in the conditioning rings with use of workholdings. Samples were divided to three groups according to their Vicker’s hardness: 160, 440, and 650 HV. After grinding, lapping process was conducted. Experiments were carried out with an angular speed of the lapping plate set at 65 RPM, and lapping velocity was v = 49 m/min. The lapping pressure was provided by dead weights and during experiments executing p = 0.04 MPa. Samples were lapped during 10, 15 and 20 minutes. Abrasive slurry was composed of silicon carbide grains mixed with kerosene and machine oil. Abrasive grains size was F400/17.The material removal rate (MRR) and specimens surface characteristic are studied in the light of workpiece material hardness. Test results show that applied process parameters are the best for steel which hardness is 440 HV. In that case, the lowest values of Raparameter were obtained in conjunction with satisfactory values of material removal rate. It can be also seen, as could be predicted, that lapping time influenced on lapping results. MRR increases and surface roughness decreases with time. The worst lapping results were obtained for normalized steel (160HV). It can be the effect of surface damage, like scratching and grooving by harder abrasive grains.

Experimental study of machinability in mill-grinding of SiCp/Al composites

An attempt was made to investigate the machinability of SiCp/Al composites based on the experimental study using mill-grinding processing method. The experiments were carried out on a high-speed CNC machining center using integrated abrasive cutting tool. The effects of combined machining parameters, e g, cutting speed (vs), feed rate (vf), and depth of cut (ap), with the same change of material removal rate (MRR) on the mill-grinding force and surface roughness (Ra) were investigated. The formation mechanism of typical machined surface defects was analyzed by SEM. The experimental results reveal that with the same change of material removal rate, lower mill-grinding force values can be gained by increasing depth of cut and feed rate simultaneously at higher cutting speed. With the same change of MRR value, lower surface roughness values can be gained by increasing the feed rate at higher cutting speed, rather than just increasing the depth of cut, or increasing the feed rate and depth of cut simultaneously. The machined surface of SiCp/Al composites reveals typical defects which can influence surface integrity.

A comparative study on modelling material removal rate by ANFIS and polynomial methods in electrical discharge machining process

Due to the controversy associated with modelling Electrical Discharge Machining (EDM) processes based on physical laws; this task is predominantly accomplished using empirical modelling methods. The modelling studies reported in the literature deal predominantly with quantitative parameters i.e. ones with numerical levels. In fact, modelling categorical parameters has been devoted a scant attention. This study reports the results of an EDM experiment conducted on the Ti–6Al–4V alloy. Its aim was to model the relationship between the Material Removal Rate (MRR) and the parameters of the process, namely, current, pulse on-time and pulse off-time along with a categorical factor (electrode material). The modelling process was accomplished using adaptive neuro-fuzzy inference system (ANFIS) and polynomial modelling approaches. In fact, one purpose of this study was to compare the performance of these modelling approaches as no study was found contrasting their prediction capability in the literature. Regarding the polynomial model, two numerical parameters (current and pulse on-time) were declared significant in the ANOVA together with the electrode material and its interaction with pulse on-time. Thus, they were all incorporated in the developed polynomial model. Furthermore, five ANFIS models with 6, 9, 19, 21 and 51 rules were developed utilizing the first order Sugeno fuzzy approach by back-propagation neural networks training algorithm. Of these, the ANFIS model with 21rules was the best. This model also outperformed the polynomial model remarkably in terms of predicting error, residuals range and the correlation coefficient between the experimental and predicted MRR values. The study sheds light on the powerful learning capability of ANFIS models and its superiority over the conventional polynomial models in terms of modelling complex non-linear machining processes.

Investigating material removal rate and surface roughness using multi-objective optimization for focused ion beam (FIB) micro-milling of cemented carbide

Cemented carbide has been investigated as a useful material for the fabrication of micro devices. Focused ion beam (FIB) micro-milling has been found to be one of the most appropriate methods for the fabrication of micro devices. The experimental FIB micro-milling on cemented carbide have been conducted according to the L16 orthogonal array of Taguchi technique. Beam current, extraction voltage, angle of beam incidence, dwell time and percentage overlap between beam diameters have been considered as process variables of FIB micro-milling in experimental design. Material removal rate (MRR) and surface roughness have been determined experimentally for FIB micro-milling of cemented carbide and beam current has been identified as the most significant parameter. The minimum surface roughness of 5.6nm has been reported on cemented carbide, which is not a usual practice to achieve on such polycrystalline material, and hence it may be considered as a significant research contribution. Maximum MRR of 0.4836μm3/s has been reported. Moreover, genetic algorithm toolbox of MATLAB has been utilized for multi-objective optimization between MRR and surface roughness. The corresponding optimum values of MRR and surface roughness for multi-objective optimization have been represented by pareto optimum solution generated by genetic algorithm. The research work presented in this paper determines the setting of process parameters of FIB micro-milling for achieving a specific combination of MRR and surface roughness on cemented carbide.

The Performance of Brass Electrode on Material Removal for Aluminium Composite in EDM Die-Sinking

This paper investigates the performance of brass electrode on the removal of aluminium alloys LM6 (Al-Sil2) in an electrical discharge machining (EDM) die-sinking. The machining parameters such as pulse-on time, pulse-off time and peak current were selected to find the responses on the material characteristics such as material removal rate (MRR), electrode wear rate (EWR) and surface roughness (Ra). Brass with diameter of 10mm was chosen as an electrode. Orthogonal array of Taguchi method was used to develop experimental matrix and to optimize the MRR, EWR and Ra. It is found that the current is the most significantly affected the MRR, EWR and Ra while pulse on time, pulse off time and voltage are less significant factor that affected the responses. Percentage optimum value of MRR increases to 3.99%, however EWR and Ra reduce to 3.10% and 2.48% respectively. Thus, it shows that brass having capability to cut aluminium alloys LM6.