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Nowadays, there has been continuous development of metallic biomaterials to meet special needs in the manufacturing of biomedical implants, units and systems so as to function well in the required environment. Developed biomaterials which possess exceptional properties in terms of biocompatibility and biomechanical compatibility require precision processing and machining to obtain the desired dimensional tolerances. Electrical discharge machining (EDM) is the noncontact or nontraditional process of machining that suits the precision machining of biomaterials. In this work, an effort was made to optimize the EDM parameters during machining of titanium-based biomaterials Ti-6AL-4V, so that the multi-objective responses could be obtained. The response surface method was used in designing the experiment, while the grey relational method was used to analyze the effect of multiple objectives into a single unit. The electrical parameters that were considered in this study include peak current, gap voltage, pulse turn-on and duty cycle. These parameters were set within the acceptable limits of the equipment. Three responses were studied, which are tool wear rates (TWRs), material removal rate (MRR) and surface roughness (SR). Using the signal-to-noise ratio and ANOVA optimum tool/electrode wear rate (TWR) is obtained at $5\times 10^{-5}$ g/min with process parameters $\mathrm{\text{Ip}}=6$ A, $\mathrm{\text{Vg}}=30$ V, $\mathrm{\text{Ton}}=200$  $\mu$s, $D=65$%. Optimum values of material removal rate (MRR) are obtained as 0.01035g/min with process parameters $\mathrm{\text{Ip}}=6$ A, $\mathrm{\text{Vg}}=60$ V, $\mathrm{\text{Ton}}=140$  $\mu$s, $D=50$%. Optimum SR is observed as 2.258 $\mu$m with EDM process parameters $\mathrm{\text{Ip}}=6$ A, $\mathrm{\text{Vg}}=90$ V, $\mathrm{\text{Ton}}=200$  $\mu$s, $D=65$%. Surface characteristics are verified with SEM micrographs. Whereas, grey relation analysis predicted the multi-objective optimum response characteristics. Based on the grey relation grade, experiment number 7 ($\mathrm{\text{Ip}}=6$ A, $\mathrm{\text{Vg}}=90$ V, $\mathrm{\text{Ton}}=200$  $\mu$s, $D=65$%) secured the first rank among the experiments/trails.

Electrical discharge machining (EDM) is an unconventional machining process used for machining of hard-to-cut materials. Both EDM and micro-EDM processes are extensively used for producing dies and molds, complex cavities, and 3D structures. In recent years, researchers have intensively focused on improving the performance of both micro-EDM and EDM processes. This paper reviews the research work carried out by the researchers on vibration-assisted EDM, micro-EDM, and wire EDM. The consolidated review of this research work enables better understanding of the vibration-assisted EDM process. This study also discusses the influence of vibration parameters such as vibration frequency and amplitude on the material removal rate (MRR), electrode wear rate (EWR), and surface roughness (SR). The important issues and research gaps in the respective area of research are also presented in this paper.

This study deals with the investigation on the effect of Electrical Discharge Machining (EDM) parameters during machining of hybrid composite (Al 7075/TiC/B₄C). The optimum process parameters of die sinking EDM like pulse current, pulse duration and gap voltage on metal removal rate, tool wear rate and surface finish were investigated. Full factorial experimental design was selected for experiments. Analysis of variance was employed to study the influence of process parameters and their interactions on response variables. Among the process parameters considered, it was observed that the pulse current was found to be more influential in affecting MRR, TWR and SR. The other parameters have little effect on the response variable. Multi-objective optimization study was also performed using genetic algorithm to find the optimum parameter setting for controversial objective function combination such as high MRR and low SR and High MRR and low TWR. Scanning electron microscope study was performed to study the surface characteristics.

Intermetallic/ceramic composites with multiple responses are based on L₁₈ orthogonal array with gray relational analysis (GRA). This paper presents a new approach for the optimization of drilling parameters on drilling MoSi₂–SiC composites. Optimal machining parameters can then be determined by the gray relational grade as the performance index. In this study, the sparking parameters namely current (I), pulse on time (t_on), pulse off time (t_off), spark gap and dielectric flushing pressure (P) are optimized with considerations of multiple performance characteristics including multi responses such as material removal rate (MRR), electrode wear rate (EWR), circularity (CIR), cylindricity (CYL), perpendicularity (PER). A gray relational grade obtained from the GRA is used to solve the electrical discharge machining (EDM) process with the multiple performance characteristics. Based on the gray relational grade, optimum levels of parameters have been identified and significant contribution of parameters is determined by ANOVA. Confirmation test is conducted to validate the test result. Experimental results have shown that the responses in EDM drilling process can be improved effectively through the new approach.

Pure copper, copper-based alloys, brass, graphite and steel are the most common tool materials for the electrical discharge machining (EDM) process. The electrode material, which exhibits good conductivity to heat and electricity and possesses better mechanical and thermal properties, is preferred for EDM applications. The major problem with conventional electrodes like copper and graphite is their low wear resistance capacity. This study is on the fabrication of Cu–SiC composites as an electrode of EDM with improved wear characteristics for machining of hardened D2 steel which is widely used in die formation. Powder metallurgy route was used to fabricate the samples which was further followed by three-step sintering process. Copper metal was used as a matrix element which was reinforced with SiC in volume fractions of 10%, 15% and 20%. Based on the desirable properties for the EDM tool, the best composition of Cu–SiC composite tool tip was suggested and was further used for machining of D2 steel. The performance of newly developed Cu–SiC composite electrode in terms of surface roughness (SR), material removal rate (MRR) and tool wear rate (TWR) was explored, and it was compared with the pure copper electrode. Pulse on-time, pulse off-time and the input current were selected as the input process parameters. Result reveals that the TWR and SR were decreased by 12–18% and 10–12%, whereas the MRR was increased by 9–28% for Cu–SiC composite tool as compared to the pure Cu electrode. Adequacy of the results was checked by statistical analysis. The surface texture of tool and machined surface was analyzed using scanning electron microscopy (SEM). SEM micrograph revealed that surface cracks on composite tool tip were lesser than pure Cu tool tip, whereas the work surface was rough while machining with the copper tool surface. Therefore, the result indicates that the newly developed Cu–SiC composite tool can be used for machining of hard materials with EDM.

The present contribution describes an application of a hybrid approach using response surface methodology (RSM) and particle swarm optimization (PSO) for optimizing the machining parameters in electric discharge machining (EDM) of compo casted Al6061/ cenosphere AMCs. Compo casting processing route was employed to prepare the AMCs. Each experimentation in EDM was performed under different machining conditions of Peak Current (Amp), Pulse on time ($\mu$s), and Flushing Pressure (bar). Performance characteristics such as material removal rates (MRRs), surface roughness (SR), and electrode wear rates (EWRs) were evaluated. A Taguchi L27 orthogonal array was considered to plan the experimentation and RSM was applied to model the inter relationship between the input process parameters and responses. A mathematic model has been developed to provide a fitness function to PSO by unifying the multiple responses. Finally, PSO was used to predict the optimal settings of the processing condition for the multi-performance optimization of the EDM operation. The experimental observations confirm the feasibility of the strategy and are in good accordance with the predicted value over a wide range of processing conditions employed in the process.

This study deals about the influence of vibrations incorporated into a workpiece during powder-mixed electrical discharge machining (PMEDM) on quality measures such as material removal rate (MRR), surface roughness $(R_a)$ and microhardness. It has been found that the low-frequency vibration incorporated into the workpiece positively affects the processing efficiency of electrical discharge machining (EDM) and PMEDM. However, the effect of low-frequency vibration in PMEDM has been better than EDM. The higher vibration frequency significantly improves the MRR and $R_a$ in PMEDM. The MRR has been improved by 95.89% and with lower $R_a$ of 63.2% in PMEDM. The hardness of the machined surface after PMEDM using titanium powder mixed in dielectric liquid was increased approximately two times as compared with conventional EDM.

Nowadays, composites are used in different parts of industries and it is one of the most important subjects. The most widely used reinforcements in metal matrix composites are Al₂O₃ and SiC fibers and particles which may be used in cutting-edge functional and structural applications of aerospace, defense, and automobile industries. Depending on the type of powder used, composite materials are difficult to machine by conventional cutting tools and methods. The most appropriate way for machining of these composites is electro discharge. For the reason of improving the surface quality, tool wear rate and material removal rate and reducing the cracks on the surface, Al₂O₃ powder was used. In this study, the effect of input parameters of EDM such as voltage, pulse current, pulse on-time and pulse off-time on output parameters like material removal rate, tool wear rate and surface roughness in both conditions of the rotary tool with powder mixed dielectric EDM and the stationary tool excluding powder mixed dielectric were investigated. The critical parameters were identified by variance analysis, while the optimum machining parameter settings were achieved via Taguchi method. Results show that using of powder mixed dielectric and rotary tool reduce the tool wear rate, surface roughness and the cracks on the surface significantly. It is found also that using of powder mixed dielectric and rotary tool improve the material removal rate due to improved flushing action and sparking efficiency. The analysis of variance showed that the pulse current and pulse on-time affected highly the MRR, TWR, surface roughness and surface cracks.

Electrical discharge machining (EDM) process is widely used to process hard materials in the industry. The process of electrical discharge is changed and called PMEDM when alloy powder is added in the oil dielectric. In this study, the effect of tungsten carbide alloy powder added in the dielectric on the microhardness of surface (HV) status of the workpiece SKD61 after machining is investigated. Studies show that the microhardness of surface obtained by PMEDM is generally better than that by normal EDM. The experiment shows that at the selected process window, adding the powder has resulted in an improvement of the microhardness up to 129.17%.

Ultrasonic frequency vibration coupled micro-wire electrical discharge machining (UFV-$\mu$ WEDM) has received enormous consideration due to its zero-tolerance machining. Nickel chromium (Ni–Cr) space alloys are a natural choice within the aerospace industry, which are exposed to high temperatures and high pressure, such as turbine seals and exhaust liners. This study reveals the impact of the UFV-$\mu$ WEDM influencing machining parameters like ultrasonic frequency vibration (UFV), servo voltage ($V_S$), time on ($T_{\mathrm{\text{on}}}$), cutting angle ($A_C$), time off ($T_{\mathrm{\text{off}}}$), and current (I) on the Ni–Cr space alloy in terms of minimum surface undulation (Ra) with maximum material removal rate ($M_{\mathrm{\text{RR}}}$). The cutting trials are carried out by central composite design (CCD). Analysis of variance (ANOVA) is used to find out the proportionate contribution of several factors, and it discloses that $V_S$ was the significant parameter impacting Ra (64.57%) and $M_{\mathrm{\text{RR}}}$ (61.86%). The performance sequence of significant influencing parameters is $V_S>T_{\mathrm{\text{off}}}>A_C>T_{\mathrm{\text{on}}}>I$. According to desirability analysis (DA), optimum parameters for numerous solutions are $T_{\mathrm{\text{on}}}=8$$\mu$s, $V_S=50$V, $T_{\mathrm{\text{off}}}=14$$\mu$s, $I=3$A, and $A_C=30^{\circ }$. The optimum conditions lead to the highest $M_{\mathrm{\text{RR}}}$ (5.72mm³/min) and the lowest Ra (3.42$\mu$m). Scanning electron, 3D topography, and atomic force microscope images are used to analyze the machined surface.

The research investigation reported on the effect of machining parameters on surface roughness (Ra) in electric discharge drilling of Inconel 718. Machining was done by using a copper tool electrode. Machining was conducted by considering different process parameters viz. tool diameter, discharge current, pulse on time, pulse off time, tool rotation and depth of hole. Optical surface profiler was used to measure surface roughness of drilled hole in work-piece. Design of experiment was created by Taguchi method based L18 orthogonal array. For minimum surface roughness, optimum parameters were found using Analysis of variance (ANOVA). Based on analysis, it is found that pulse off time, pulse on time and tool rotation are the most significant parameters that affect the surface roughness. Tool diameter is the less significant parameter that affects the surface roughness. Regression analysis was used to predict a value for minimum surface roughness. The scanning electron microscope (SEM) images were used to identify the microstructure of the drilled hole in Inconel 718 work-piece. Interaction plots and residual plot have been plotted for surface roughness to identify the interaction between parameters and residual errors, respectively.

Electrical discharge machining (EDM) is one of the importantly non-traditional processing technologies employed for ceramics’ surface processing. Modeling and optimization of the EDM process are essentially applied to find and obtain the optimal values of the responses for materials having smaller surface roughness, higher removing rate of materials, lower electrode wear rate. In this study, the Grey-Taguchi system with AHP weighting was applied in order to optimize the multi-responses of the EDM processing for ceramics. When the EDM processing was used in the ZrO₂ ceramics for adhesive metal foils, the multi-response gray relational grade for the optimal level of machining parameter was 0.2685, which was higher than those using the initial experimental conditions. This study has proven that using the Grey-Taguchi system method with AHP weighting to find a model with a highly efficient standard for optimizing differently advanced machining processes is profitable.

This study employs Taguchi orthogonal design (L₉) to optimize the machining parameters of electro-discharge machining (EDM). The aluminum matrix composite (AMC) with 16wt.% titanium carbide (TiC) and 4wt.% graphite (Gr) specimen was prepared by stir casting process. This study involves three control parameters with three levels, namely pulse current, voltage and fluid pressure to predict the process response, such as material removal rate (MRR) and surface roughness (SR) of the worn surface. Maximum MRR of 0.1661g/min was attained for 10A, 500V and 15kgf/cm² fluid pressure with corresponding roughness of 11.43$\mu$m and the minimum value of 7.51$\mu$m was observed for 10A, 100V and fluid pressure of 5kgf/cm². A regression model was developed and the effect of control parameters on process responses were determined by analysis of variance (ANOVA). According to ANOVA outcome, the machining parameters which control the process response MRR were determined as voltage (47.94%), pulse current (33.19%) and fluid pressure (17.58%). Similarly, the SR was affected by machining parameters voltage (55.17%), pulse current (22.41%) and flushing pressure (21.47%). The optimum machining parameters were predicted and confirmed by conducting experiments with reasonable error of 2.49% and 2.02% for MRR and SR, respectively. Surface characteristics of the machined AMC was analyzed by scanning electron microscope (SEM) to observe the defects like craters, voids, glued debris and recast layers.

In this paper, the copper (Cu)-based multi-wall carbon nanotube (MWCNT) composite tools were fabricated using electro-co-deposition method. The composite tools were prepared from different MWCNT concentrated (0.5, 0.75 and 1g/L) electrolytic solution and these tools were utilized in electro discharge machining (EDM). The experiments were performed with varying discharge currents. The results indicated that the incorporation of MWCNTs into the copper matrix greatly influenced the machining performances. A lower rate of tool wear and higher material removal rate (MRR) were observed for the copper-based MWCNT composite tools at different discharge currents. The highest tool wear rate (TWR) was reduced by 45.68% and the MRR was improved by 63% for the Cu-MWCNT (0.5g/L) composite tool compared to copper coated tool. At higher discharge current, smoother machined surfaces were generated using copper-based MWCNT composite tools compared to the copper tools. The SEM image exhibits that the micro-crack-free machined surfaces were produced by using copper-based MWCNT composite tools. The migration of tool material to the machined surface was also reduced for copper-based MWCNT composite tools.

Shape memory alloys (SMAs) are an excellent material for producing components for a wide range of industrial applications, such as orthopedic implacers, micro-equipment, actuators, fittings, and screening components, as well as military equipment, aerospace components, bio-medical equipment, and fabrication requirements. Despite its remarkable qualities, the production of SMAs is a problem for investigators all over the globe. The purpose of this research is to evaluate the effects of altering the $T_{\mathrm{\text{on}}}$, $T_{\mathrm{\text{off}}}$, $I_{\mathrm{\text{p}}}$, and GV while processing copper-based SMA in an electrical discharge machining process on the material removal rate (MRR) and surface roughness (SR). The major runs were designed using a central composite design. SEM was also utilized to examine the micro-structure of EDM-processed electrode tools and work samples. SEM scans indicated the presence of debris, micro-cracks, craters, and a newly formed recast layer on the electrode tool and workpiece surface. High $I_{\mathrm{\text{p}}}$ and prolonged $T_{\mathrm{\text{on}}}$ provide huge spark energy simply at the work sample-tool contact, resulting in debris production. The experimental results reveal that the least and highest MRR values are 10.333 and 185.067mm³/min, respectively, while the minimum and maximum SR values are 3.07 and 7.15$\mu$m. The desirability technique, teacher learning based optimization (TLBO), and the Jaya algorithm were also utilized to optimize the studied solutions (i.e. MRR and SR) on a single and multi-objective basis. The best MRR and SR were determined using the desirability approach, the Jaya Algorithm, and the TLBO to be 152.788mm³/min and 4.764$\mu$m; 240.0256mm³/min and 1.637$\mu$m; and 240.0257mm³/min and 1.6367$\mu$m.

Nowadays, it has become very difficult for the manufacturer to satisfy all its customers with satisfactory products, as they have different demands considering the responses. However, hard-to-machine materials are difficult to manufacture. This study explores the application of electro-discharge machining (EDM) of Ti–6Al–4V alloy with pulse duration (Ton), duty factor ($\tau )$, peak current (Ip) and gap voltage (Vg) as the control parameters using pure copper electrode. Machining effects are evaluated by performance characteristics including material removal rate (MRR), tool wear rate (TWR) and surface roughness (SR) by considering the multi-criteria preference of the customers that vary with the preference of responses. For the experiment, proper orthogonal arrays are found out using Taguchi methodology. The optimum parametric settings were obtained by utility-concept-based Taguchi method which were compared with desirability-approach-based Taguchi. It was found that utility-concept-based Taguchi optimization methodology results in more feasible parametric setting which has also been confirmed by the validation experiments. The optimum values of process variables obtained were pulse duration of 30$\mu$s, duty factor of 9%, peak current of 10A and gap voltage of 6V to achieve maximum MRR and lower TWR with better surface finish to satisfy multi-user criteria.

Electrical Discharge Machining (EDM) is a thermal energy based non-traditional shaping process for shaping of hard and brittle electrically conductive materials, but it suffers with low machinability and recast layer formations. The combination of grinding with EDM means enhancement in machining capability, but the process becomes highly complex. Therefore, the assortment of control factors for optimum results is greatly challenging for the industries. The objective of present study is to optimize the control factors such as current, pulse on-time, pulse off-time, wheel RPM and abrasive grit number (GN) to optimize the material removal rate (MRR) and average surface roughness (Ra) for Grinding Aided-EDM process. For this purpose, the simultaneous application of soft computing methods such as Artificial Neural Network (ANN) and Genetic Algorithm (GA) has been employed. The results demonstrate that combination of ANN with GA effectively predicts the data and provides optimal results with adequate percentage errors in MRR and Ra positively.

New superalloys are potential materials in aircraft and power plant industries because of their properties like high-temperature strength, creep life and resistance to corrosion and oxidation at elevated temperatures. Because of the superior properties of superalloys, machining them using the conventional processes is a difficult task that is associated with high cost and poor accuracy. In this study, an attempt has been made to machine NIMONIC 75 superalloy by the electro discharge machining (EDM) process, using the Taguchi-based Gray Relational Analysis method for multi-objective optimization of material removal rate (MRR), tool electrode wear rate (TEWR) and surface finish (SF). The experiments conducted were based on $L_{18}$ (2${}^1\times 3^5$) orthogonal array. Six input parameters namely tool material, peak current, gap voltage, pulse on-time, pulse off-time and tool lift time were considered in this study. The validation results proved that the parametric setting of tool material as copper, peak current as 12A, gap voltage as 50V, pulse on-time as 200$\mu$s, pulse off-time as 15$\mu$s and tool lift time as 2s, yields optimized values of the performance characteristics. SEM images indicate the presence of numerous surface irregularities, whereas the XRD test shows the formation of various carbides on the EDMed surface.

The virgin copper electrode has limited application due to its wear and mechanical properties using Electrical Discharge Machined (EDMed) on Inconel 718 superalloys. In order to enhance the performance of copper electrodes, in this work, Ion Nitriding (IN), Surface Hardening by Laser (LSH) and Hybrid Process ($\mathrm{\text{IN}}+\mathrm{\text{LSH}}$) are performed on copper electrodes to reduce the electrode wear in frontal and lateral. The electrode wear in the frontal and lateral of virgin copper electrode is processed and studied using EDM with varying pulse durations, current and Silicon Carbide (SiC) mixed EDM oil. The surface hardness in virgin and processed electrodes is also investigated. Overall analysis found that the hybrid technique produced a 59% higher hardness than that of virgin copper. The hardness in the EDMed surface was higher than that of the processed copper surface. A 1000$\mu$s pulse duration, 2 A current and 15 g/l SiC powder mixing EDM oil produced a low frontal wear in both virgin and processed copper electrodes. The electrode wear was reduced by 30% for frontal and 76% for lateral using a hybrid method.

This investigation explores the application of electrical discharge machining (EDM) to ceramic composites constructed from Si₃N₄–TiN (Syalon 501) by testing both square and cylindrical electrodes. Various experimental methods have been employed, including design-of-experiments (DoE), Grey relational analysis (GRA), analysis of variance (ANOVA), confirmation testing, and scanning electron microscopy (SEM), in an effort to optimize machining settings and comprehend their effect on performance. While ANOVA revealed crucial parameter levels influencing overall machining conditions as measured by the grey relational grade (GRG), the sophisticated method of GRA considerably improved the machining characteristics. Significant improvements in the EDM process were shown experimentally, resulting in outstanding results for material removal rate (MRR), surface roughness (SR), and electrode wear rate (EWR). In particular, numerous benefits of the square electrode layout over the more common cylindrical arrangement stood out. All of the aforementioned resulted in an impressively high MRR (measured at 0.0281gm/min), a low EWR (at 0.0020gm/min), and a significant improvement in SR (at 0.3150$\mu$m). The GRG value was 0.0163 for the square electrode design, which was excellent, and 0.0025 for the cylindrical electrode, which was significantly better. The optimized parameters were successfully used, especially with the square electrode arrangement, leading to significant improvements in MRR and decreases in EWR. On the other hand, surface quality was negatively affected by larger parameter values, which increased the development of microfractures, particularly when using the square electrode design. In any case, our study provides strong proof that adjusted settings can greatly improve EDM performance, allowing for accurate machining of Si₃N₄–TiN composites with increased MRR, great surface texture, and reduced electrode wear. In conclusion, our study provides useful information to improve EDM procedures for Si₃N₄–TiN ceramic composites, as well as practical insights into increasing the efficiency and quality of EDM operations in a variety of industrial sectors.