Pulse-on Time Research Articles

Prediction of erosion rate by a novel method and parametric optimization of edm of novel sic insulated ceramic reinforced with carbon nano tube

In this study, a mathematical model for the multi-optimization of Silicon carbide [SiC] reinforced by Carbon Nano tube [CNT] machined by Electrical discharge machining[EDM] has been done. SiC has an excellent mechanical properties owing to its large use as heat exchangers, sensors and automotive brake discs, etc. All of these applications need a highly precise machined hole with reasonable surface clarity. But due to its high hardness it is impossible to be machined by Conventional mode of machining. As SiC is a highly nonconductive ceramic CNT reinforcement make it possible to machine it by EDM and also increases its mechanical properties. For this study-three different proportion of CNT [2%, 4%, 6%] by Volume has been considered as reinforced material. For selecting the optimal process parameter L9 Taguchi Orthogonal array has been designed for this study by considering different output parameters [i.e CNT Proportion, Current, Voltage & Pulse-On time]. Material removal rate [MRR] and Surface roughness [SR/Ra] has been calculated by conducting the experimentation. The best setting of Process parameters has been predicted by Taguchi Coupled with GREY method. At the optimal condition the deviation in between the experimental result and the predicted result is 4.3% for MRR and 4% for SR respectively. The regression model has been done with R2 and R2adj showing above 90%. ANOVA analysis has been also shows 4% CNT reinforced SiC ceramic can be considered for used in automobile, sensor industries.

Optimizacija PMEDM sa više odgovora na Inkonel 718 koristeći hibridni T-GRA, TOPSIS i ANN model

Inconel 718 is one of the Nickel-based superalloys considered one of the most difficult-to-machine materials owing to its property to retain hardness at higher temperatures. This study examined the performance of Edcutor-based PMEDM machining on Inconel 718. Taguchi L9 OA has been used with current, Pulse-OFF time & Pulse-ON time as process parameters with a delivery side pressure of 6 bar for the Alumina mixed dielectric. Material removal rate (MRR), Tool wear rate (TWR), & surface roughness (SR) have been taken as output responses. The results have been investigated by MADM techniques, namely Taguchi-based Grey Relational Analysis (T-GRA) & TOPSIS analysis. Furthermore, the ranks obtained from T-GRA & TOPSIS have been validated by developing a single layered ANN model. Ranks predicted by the ANN model are the same for T-GRA and TOPSIS and the R-values are 0.924 & 0.871, respectively. ANOVA has also been used to analyze parameter effects on output responses.

Multi-parametric optimization of Wire-EDM machining on artificially-aged al6061/b 4 c composite using RSM and grey relational analysis

Wire-electric discharge machining (W-EDM) is an advanced technology used for machining hard-to-cut materials with high hardness. Therefore, it is critical to characterize and model the Wire-ED machining performance for new materials having remarkable mechanical properties with respect to the multiple control parameters involved in the process. In this light, the present study investigates the multi-parametric optimization of current, pulse-on time (Ton), and pulse-off time (Toff) on material removal rate (MRR), kerf width (KW), surface roughness (R a) for Wire-EDM of artificially aged Al6061/B4C composite using response surface method (RSM) and grey relational analysis (GRA). The results of the investigation revealed that, Toff has the most significant impact on the multi-parametric response, with a percentage-wise contribution of 38% from the analysis of variance. The optimization results established that a multi-parametric combination of current - 6 A, Ton - 42.5253 ms, and Toff - 10 ms achieved the optimum response of MRR - 1.7036 mg/min, KW - 0.1727 mm, and R a - 5.6525 mm. The results obtained herewith have practical relevance to Wire-EDM industry for manufacturing applications.

Optimisation of EDMed fly ash and rice husk ash reinforced hybrid Al-based composite using improved COPRAS and entropy method

Rice husk ash (RHA) and fly ash (FA) pose a hazard to human health environment and are available abundantly across the globe. Attempts are being made to use such waste materials to create aluminum-based composite materials that can be used in a spectrum of uses. The Al6061/RHA/FA hybrid composite was prepared with 2.5 wt. % of each RHA and FA particle using a stair casting technique. This paper discusses mechanical characteristics like tensile strength, hardness, percentage elongation, and surface morphology, which were investigated using SEM. In addition, machinability investigations have been carried out using electric discharge machining, targeting the productivity of the component, quality, and accuracy. Taguchi's L9 array was used to investigate the impact of parameters like pulse current, duty-cycle, pulse ontime, and gap voltage on output parameters MRR, tool eroded, and radial overcut. Enhancements in tensile strength and harshness have been observed by the reinforcement of FA and RHA particles. [Submitted 15 July 2021; Accepted 17 September 2021]

Investigations on the wire EDM characteristics of Al matrix composite using TOPSIS method

This study deals with wire electrical discharge machining (WEDM) of alumina (Al2O3) reinforced AA6063 matrix composite using a brass wire electrode to analyze the two important characteristics concerning material removal rate (MRR) and surface roughness (Ra). Nine combinations of experimental runs are performed by taking three input parameters (peak current (Ip), pulse-on time (Ton) and pulse-off time (Toff)) based on Taguchi’s design of experiments. In addition, Technique for order preference by similarity to ideal solution is employed for multi-response optimization. Thereafter, analysis of variance (ANOVA) is employed to determine the influence of parameters on responses. From TOPSIS results identified that the optimal parameters for obtain the higher MRR and lower Ra are ‘Ip’ of 20A, ‘Ton’ of 100 µs and ‘Toff’ of 30 µs, respectively. ANOVA result revealed that ‘Ton’ has the main significant factor (42.40 %) in enhancement of MRR and deprivation of Ra, followed by ‘Ip’ (28.53 %) and ‘Toff’ (16.63 %), respectively.

Modelling and prediction of WEDM parameters for sustainable machining of titanium grade-2 alloy

PurposeThe purpose of the study is to establish a predictive model for sustainable wire electrical discharge machining (WEDM) by using adaptive neuro fuzzy interface system (ANFIS). Machining was done on Titanium grade 2 alloy, which is also nicknamed as workhorse of commercially pure titanium industry. ANFIS, being a state-of-the-art technology, is a highly sophisticated and reliable technique used for the prediction and decision-making.Design/methodology/approachKeeping in the mind the complex nature of WEDM along with the goal of sustainable manufacturing process, ANFIS was chosen to construct predictive models for the material removal rate (MRR) and power consumption (Pc), which reflect environmental and economic aspects. The machining parameters chosen for the machining process are pulse on-time, wire feed, wire tension, servo voltage, servo feed and peak current.FindingsThe ANFIS predicted values were verified experimentally, which gave a root mean squared error (RMSE) of 0.329 for MRR and 0.805 for Pc. The significantly low RMSE verifies the accuracy of the process.Originality/valueANFIS has been there for quite a time, but it has not been used yet for its possible application in the field of sustainable WEDM of titanium grade-2 alloy with emphasis on MRR and Pc. The novelty of the work is that a predictive model for sustainable machining of titanium grade-2 alloy has been successfully developed using ANFIS, thereby showing the reliability of this technique for the development of predictive models and decision-making for sustainable manufacturing.

Experimental Investigations of Surface Finish Generated by Wire Electrical Discharge Machining

Abstract. This study aims to investigate wire electrical discharge machining of copper alloys. Extensive research was done to design an optimum cutting method with adequate wire balance to achieve the requisite surface smoothness and geometrical dimensional correctness. Parameters were used in this work to simulate the process pulse-on time, pulse-off time, peak current, servo feed-rate, servo-volt, wire-feed rate, wire tension, and water pressure. For each given treatment requirement, the primary impacting elements are highlighted. The results are the best standard settings that have been designed to satisfy the client’s varied developing needs. A low pulse achieves superior surface polish on time and a high pulse off time. According to the (ANOVA) findings, the most significant cutting parameter is the pulse on-time (Ton), which affects surface roughness by (42.922)%, followed by pulse off time (Toff), which affects surface roughness by (24.860)%, and servo feed (SF), which affects surface roughness by (6.850)%. The impact of the process variables was wire tension on response characteristics, dimensional deviation, cutting rate, and surface roughness.

Effect of process parameters on machining behaviour using S/N ratio and ANOVA analysis

Inconel 725 super alloy is a significant and often used material for many technical applications such as oil and gas industries, aerospace, nuclear and marine areas owing to its exceptional physical and mechanical properties. The major drawback of utilizing this alloy is challenging it is to machine using traditional machining techniques. Production sectors often aim to produce goods with excellent surface finishes and high production rates at reasonable prices. Hence, in the current study deals with the effect of electric discharge machining (EDM) parameters viz. pulse-on time (Ton), pulse-off time (Toff) and discharge current (Ip) on metal removal rate (MRR) and surface roughness (Ra) of Inconel 725 alloy. According to the Taguchi’s L9 orthogonal design the EDM studies were performed. The optimal condition of EDM parameters was obtained by signal to noise (S/N) ratio analysis with an aim was to minimize the Ra and maximize the MRR. S/N ratio results obtained that the higher MRR produced at Ton of 45 µs, Toff of 60 µs and Ip of 10 A. Similarly, the lower Ra produced at Ton of 15 µs, Toff of 40 µs and Ip of 5 A. ANOVA results reveals that discharge current (Ip) has the most noteworthy factor for MRR and Ra followed by pulse-on time (Ton).

Optimization of WEDM Parameters While Machining Biomedical Materials Using EDAS-PSO.

In the present work, an attempt has been made to study the influence of process parameters of the wire electric discharge machining (WEDM) process on the machining characteristics. The commercially pure titanium is machined by WEDM using brass wire as an electrode. The input parameters in this work were pulse on-time (Aon), pulse off-time (Aoff), servo voltage (SV) and wire tension (WT). On the other hand, dimensional accuracy (DA), average surface roughness (Ra) and maximum surface roughness (Rz) were chosen as the response parameters. The empirical relations developed for response characteristics were solved collectively using Evaluation Based on Distance from Average Solution (EDAS) and Particle Swarm Optimization (PSO). The optimized setting for minimizing the surface irregularities while machining titanium alloy on WEDM is predicted as Aon: 8 μs; Aoff: 13 μs; SV: 45 V; and WT: 8 N. Moreover, the predicted solution at the optimized parametric settings came out as DA: 95%; Ra: 3.163 μm; Rz: 22.99 μm; WL: 0.0182 g; and DR: 0.1277 mm. The validation experiments at the optimized setting showed the close agreement between predicted and experimental values. The morphological study by scanning electron microscopy (SEM) at the optimized setting revealed a significant reduction in surface defects such as micro cracks, micro cavities, globules and sub-surfaces, etc. In a nutshell, the study justified the effectiveness of EDAS-PSO in efficiently predicting the results for machining of pure titanium (Grade 2) using the WEDM process.

On the WEDM of WNbMoTaZrx (x = 0.5, 1) Refractory High Entropy Alloys.

As a potential candidate for the next generation of high-temperature alloys, refractory high entropy alloys (RHEAs) have excellent mechanical properties and thermal stability, especially for high-temperature applications, where the processing of RHEAs plays a critical role in engineering applications. In this work, the wire electrical discharge machining (WEDM) performance of WNbMoTaZrx (x = 0.5, 1) RHEAs was investigated, as compared with tungsten, cemented carbide and industrial pure Zr. The cutting efficiency (CE) of the five materials was significantly dependent on the melting points, while the surface roughness (Ra) was not. For the RHEAs, the CE was significantly affected by the pulse-on time (ON), pulse-off time (OFF) and peak current (IP), while the surface roughness was mainly dependent on the ON and IP. The statistical analyses have shown that the CE data of RHEAs have relatively-smaller Weibull moduli than those for the Ra data, which suggests that the CE of RHEAs can be tuned by optimizing the processing parameters. However, it is challenging to tune the surface roughness of RHEAs by tailoring the processing parameters. Differing from the comparative materials, the WEDMed surfaces of the RHEAs showed dense spherical re-solidified particles at upper recast layers, resulting in larger Ra values. The proportion of the upper recast layers can be estimated by the specific discharge energy (SDE). Following the WEDM, the RHEAs maintained the main BCC1 phase, enriched with the W and Ta elements, while the second BCC2 phase in the Zr1.0 RHEA disappeared. Strategies for achieving a better WEDMed surface quality of RHEAs were also proposed and discussed.

Examining the surface roughness and kerf quality of micro-slots cut on the surfaces of Ti-B4C nanocomposites by WEDM: a desirability approach

Micro slots and textures are created on Titanium (Ti) composites to improve its surface characteristics. Micro-textured Ti composites are generally recommended for bio implants, automobile, and aerospace components. In the current research, Ti-B4C nanocomposites were prepared by powder metallurgical route. Micro slots were cut on the Ti-B4C surfaces by Wire Electrical Discharge Machining (WEDM) Technology by varying the current, pulse-ON time, and pulse-OFF time. Scanning electron microscopy and XRD analysis validates the uniform distribution and inclusion of B4C nanoparticles in Ti matrix. Response surface methodology was used to plan the experimental runs. Analysis of variance and desirability analysis were employed to identify the most suitable machining factors for obtaining the minimum surface roughness, lower kerf width and higher material removal rate (MRR). Increase in applied current and pulse-ON time, increases the MRR. Increase of pulse-OFF time from 50 μs to 60 μs gradually reduces the MRR and reduce the surface roughness of the cut slots. Contrastingly an increase in pulse-ON time increases the roughness due to an extensive melting and resolidification of Ti nanocomposites. The morphology of the WEDMed surface reveals the recast layer and localized melting zones on the cut surfaces.

Drilling of Al2O3 ceramic using ultrasonic assisted electrochemical discharge machining process

Alumina is one of the most important ceramic materials in the industry due to its advantageous properties, such as electrical resistivity and high hardness. The machining of this material encounters several difficulties, and it is usually machined using non-traditional machining processes. Among these processes, ultrasonic-assisted electrochemical discharge machining has been widely used for glass machining. However, this machining process is expected to be accompanied by acceptable results in the case of alumina. Therefore, in this study, the effects of process parameters such as ultrasonic vibration amplitude, voltage, pulse-on time, and pulse-off time on material removal rate, depth, overcut, and taper angle have been experimentally studied in the machining of alumina. The results revealed that hole depth increased up to 52% using ultrasonic vibrations with an amplitude of 34 µm.

Optimization of EDM Machinability of Hastelloy C22 Super Alloys

In this study, machinability tests were carried out on a corrosion-resistant superalloy subjected to shallow (SCT) and deep cryogenic treatment (DCT) via electrical discharge machining (EDM), and the effect of the cryogenic treatment types applied to the material on the EDM processing performance was investigated. Experimental parameters, including pulse-on time (300, 400 and 500 μs), peak current (A) (6 and 10 A) and material types (untreated and treated with SCT and DCT), were used to construct the full factorial experimental design. The resulting average surface roughness (Ra) and material removal rate (MRR) results were optimized using the Taguchi L18 method. According to the Taguchi-based gray relational analysis, the optimal parameters for both Ra and MRR were determined as cryogenic treatment, pulse-on time and peak current, respectively. The response table obtained using the Taguchi method showed the most effective factors as A1BlC3 for Ra and A2B2C1 for MRR values. According to the ANOVA results for determining parameters affecting performance, peak current was the most effective factor for average surface roughness and MRR, at 74.79% and 86.43%, respectively. When examined in terms of Taguchi-gray relational degrees, the optimal parameters for both Ra and MRR were observed in the experiment performed with the SCT sample at a peak current of 6 A and 300 μs pulse-on time.

Machinability study of Al 6063-based MMCs with SiC reinforcement particles using WEDM process

ABSTRACT Metal matrix composites (MMCs) are a category of advanced materials that are challenging to process as these contain hard ceramic reinforcement particles that are distributed irregularly. Wire electro discharge machining (WEDM) is an advanced machining process that has the potential to machine hard ceramic reinforcing materials, which are electrically conductive. In this research, the WEDM process is utilized to evaluate the machinability of aluminum (Al) based MMCs. Two different fabricated Al-6063 alloy-based MMCs with silicon carbide (SiC) reinforcement particles of 220 and 600 grit size of 9 weight percentages are considered as the workpiece material. Using an experimental design with a full factorial, three process variables pulse-on time (Ton), pulse-off time (Toff), and peak current (Ip) are used to determine how they affect the on-response measures of machining time (MT), kerf width (Kf), and material removal rate (MRR). After experimentation, ANOVA analysis is applied to find out the most significant factor. ANOVA analysis reveals that Ip is the primary contributor to MT and MRR for Al/SiC (220) and Al/SiC (600) MMCs. However, Ton is the most influential factor for Kf in the case of both the MMCs. Overall evaluation criteria are also applied for the simultaneous study of response measures.

Modeling of thermal damage and residual stress in slicing of silicon wafers using wire-electrical discharge machining: Comparison with experiments

Wire electrical discharge machining (wire-EDM) is a potential technique to fabricate high-quality ultra-thin silicon (Si) wafers. However, its universal integration at the industrial scale remains impeded by the inherent limitation of induced thermal damage and residual stress. It is understood that the process parameters play a significant role in determining these subsurface damages. Therefore, a single-pulse thermal model accounting for plasma heating through a surface heat flux is developed in the present study. The applied heat flux encompasses the heat transferred to the workpiece through sparking during pulse on-time. The heat flux post spark incorporates the heat dissipation via expanding plasma channel. The governing equations of the 2D computational model are solved using the finite element method (FEM) in ABAQUSTM. The proposed model is in good agreement with the experimental results of thermal damage (10 %–13 %), peak residual stress (5 %–10 %), and residual stress damage depth (15 %–20 %). It is observed the wire-EDM slicing of silicon wafers can induce thermal damage of 10–34μm, peak residual stress of 95–180 MPa, and residual stress damage depth of 13.6–55μm. The open voltage is found to have a more significant influence on thermal damage and residual stress than pulse on-time. The model reveals that thermal damage depth could be reduced to as low as 10μm, residual stress damage depth up to 13.6μm, and peak residual stress up to 95 MPa.

ANN-based performance prediction of electrical discharge machining of Ti-13Nb-13Zr alloys

PurposeThe purpose of this paper is to predict the machining performance of electrical discharge machining of Ti-13Nb-13Zr (TNZ) alloy, a promising biomedical alloy, using artificial neural networks (ANN) models.Design/methodology/approachIn the research, three major performance characteristics, i.e. the material removal rate (MRR), tool wear rate (TWR) and surface roughness (SR), were chosen for the study. The input parameters for machining were the voltage, current, pulse-on time and pulse-off time. For the ANN model, a two-layer feedforward network with sigmoid hidden neurons and linear output neurons were chosen. Levenberg–Marquardt backpropagation algorithm was used to train the neural networks.FindingsThe optimal ANN structure comprises four neurons in input layer, ten neurons in hidden layer and one neuron in the output layer (4–10-1). In predicting MRR, the 60–20-20 data split provides the lowest MSE (0.0021179) and highest R-value for training (0.99976). On the contrary, the 70–15-15 data split results in the best performance in predicting both TWR and SR. The model achieves the lowest MSE and highest R-value for training in predicting TWR as 1.17E-06 and 0.84488, respectively. Increasing the number of hidden neurons of the network further deteriorates the performance. In predicting SR, the authors find the best MSE and R-value as 0.86748 and 0.94024, respectively.Originality/valueThis is a novel approach in performance prediction of electrical discharge machining in terms of new workpiece material (TNZ alloys).

Experimental investigation into the effects of electric discharge surface modification process parameters on the biocompatibility of Ti6Al4V

Titanium alloys especially Ti6Al4V is extensively used in the fabrication of biomedical implant due to its similar mechanical properties as of bone, bio compatibility, high strength to weight ratio, better resistance to the body fluid and corrosion resistance etc. However, in order to further improve the osteointegration, anti-bacterial, anti-corrosion, and anti-wear properties, various surface modification or coating methods are often essential. Moreover, the biological behavior of surrounding cells on the implants depends on its various surface properties like surface roughness and wettability, etc. Therefore, in this paper a comprehensive experimental investigation is planned to investigate the influence of electric discharge-based surface modification process parameters on the bio-compatibility of Ti–6Al–4V. The important process parameters such as current and pulse ON time was varied at three different levels with double deionized water as the dielectric fluid to generate different functional surfaces. The areal surface roughness, wettability, surface elemental composition and morphology, etc. were analyzed in detail using scanning electron microscopy (SEM), X-Ray Diffractometry (XRD), Energy Dispersive x-ray spectroscopy (EDS). It is observed that the surface roughness values varied between 2.9 µm to 5.4 µm with respect to the variation in the pulse ON time and current. Similarly, the contact angle also varied between the hydrophilic to hydrophobic with respect to the number of days from the development of the surfaces. In addition, it is observed that a good amount of oxygen got deposited on the surface and formed various bio active titanium oxides which enhances the cell viability, cell adhesion and proliferation. The cytocompatibility tests with L929 fibroblast cells as per the ISO 10993-5, showed a maximum of cell viability up to 84.69% with 70.6633% of cell survival.

Machinability and parametric optimization of aluminum silicon carbide metal matrix composite (Al-SiC MMC) machined through µ-EDM

Aluminum silicon carbide metal matrix composite (Al-SiC MMC) is widely used because of its exceptional mechanical and thermal properties. Some engineering applications include aerospace, automobile, electronics, and medical devices. In the present investigation, aluminum 7075 alloy (Al-7075) as a matrix material with reinforcement particles of 10% silicon carbide (SiC) is fabricated using stir casting. The developed Al-SiC MMC is machined using an in-house developed micro-electro discharge machine (µ-EDM) setup. Experiments are carried out with input parameters—voltage (V), capacitance (µF), and pulse-on time (µs)—to analyze the responses such as hole depth (HD), material removal rate (MRR), tool wear rate (TWR), surface roughness (SR), and circularity error (CE). Taguchi L16 orthogonal array is adopted to conduct 16 experiments with varying process parameters for 5 minutes’ duration with a copper tool electrode of Ø720 µm on the Al-SiC MMC workpiece of size 20 mm × 20 mm × 2.5 mm. The dielectric medium used for all experimentation is EDM oil. The resultant blind holes are characterized using scanning electron microscopy (SEM) images and a 3D profilometer. Later, the signal-to-noise ( S/N) ratio technique is used to optimize the process parameters to enhance individual output responses. The obtained results are discussed in the article. Further, analysis of variance (ANOVA) is performed to find out the contribution of each parameter to the output responses. Grey relational analysis (GRA) is also used for multiobjective optimization to get quality blind holes. The best parametric combination obtained through GRA are at 28 V, 100 µF, and 100 µs, resulting in 823 µm of HD, 0.38 mg/min of MRR, 0.10 mg/min of TWR, 8.98 µm of SR, and 48.37 µm of CE.

Optimization of Wire Electric Discharge Machining (WEDM) Process Parameters for AISI 1045 Medium Carbon Steel Using Taguchi Design of Experiments.

With the growth of the manufacturing industry, the demand for alloy materials with high hardness, toughness, and impact strength has increased. Since products from such alloy materials are extremely difficult to manufacture with high accuracy and reduced surface roughness using traditional machining techniques, wire electric discharge machining can be used to machine such complex parts with more precision. In this case-study-based research, machining factors such as current, pulse-on time, and voltage are studied to determine their effects on the material removal rate for AISI 1045 medium carbon steel. The Taguchi L9 orthogonal array is used in the design of experiments for optimization. Statistical techniques such as analysis of variance and signal-to-noise ratio are used to identify the control parameters that matter most in bringing about optimal results. Based on the results, the current is the most crucial control variable in this investigation. Moreover, the maximum material removal rate obtained was 0.7112 mm3/min with the obtained optimized values of current (I) = 16 A, voltage (V) = 50 V, and pulse-on time (Ton) = 100 µs.

STUDY ON THE INFLUENCE OF ZINC-COATED WIRE MATERIAL ON 3D PROFILE MACHINING OF INCONEL 825 ALLOY USING WEDM PROCESS

The experimental analysis carried out in this paper aimed at the selection of optimal machining conditions for the 3D profile machining of Inconel 825 alloy using Wire Electrical Discharge Machining (WEDM). It was noticed that the 3D profile machining of Inconel 825 alloy using WEDM process has not been performed and reported so far by the researchers in this domain to the best of our knowledge. As the machining of Inconel 825 alloy is difficult using the conventional machining processes, nontraditional machining is generally used. As the material is conductive, the WEDM process is suitable to machine this material. The effects of input factors such as wire material, pulse on-time, pulse off-time, peak current, wire tension and gap voltage on the material removal rate (MRR), surface roughness (SR) and dimensional shift (DS) have been investigated using [Formula: see text] mixed-level orthogonal array of experiments. The DS value for every machining condition has been predicted and inputted into the CNC system as the wire offset value to enhance the dimensional accuracy of the product. The parametric analysis has been done by Minitab software. Analysis of variance (ANOVA) has been used to find the significant parameters affecting surface quality. The regression equations have also been formulated to study the adequacy of the model. Multi-response optimization based on the Gray Relational Analysis has been employed and the results that optimize the MRR and SR simultaneously have been suggested. SEM images have been taken on the machined surfaces to compare the surface finish on the specimens.