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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.

Machining of hard and brittle materials such as engineering ceramics, glass, and silicon is a formidable task. Unlike cutting processes employing plasma and lasers, better machining capabilities of abrasive jet machining are characterized by thermally damaged free surface which is highly competitive as well as important for survival of materials in service. In this paper, an attempt has been made to combine hot abrasives and compressed air to form a hot abrasive air jet. This study aims to analyze the cutting performance in hot-abrasive jet machining (HAJM) of hardstone quartz concerning surface roughness, taper angle (TA), and material removal rate (MRR). Combined approach of Box–Behnken design — analysis of variance, response surface methodology, and statistical technique (here desirability function approach), followed by computational approach (here genetic algorithm), is, respectively, employed for experimental investigation, predictive modeling, and multi-response optimization. Thereafter, the effectiveness of proposed two multi-objective optimization techniques is evaluated by confirmation test and subsequently, the best optimal solution (i.e. at air pressure of 7kgf/cm², abrasive temperature of $64^{\circ }$C, stand-off distance of 4 mm) is used for economic analysis. Result shows that the most significant parameter is abrasive temperature for surface roughness, whereas it is pressure in case of both TA and MRR. Applications of hot abrasives in AJM process have shown attention in enhancing the cutting performance for material removal. Due to lower percentage contribution of error (6.68% to Rz, 9.89% to TA, and 6.42% in case of MRR), a higher correlation coefficient ($R^2$) was obtained with the quadratic regression model, which showed values of 0.92, 0.9, and 0.93 for surface roughness, TA, and MRR, respectively.

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.

The area of metallurgy has witnessed many advancements in the development of novel electrically conductive materials that shows exceptional mechanical as well as thermal properties. Nonetheless, traditional machining techniques encounter difficulties while machining hard materials. In order to address this limitation, electrical discharge machining (EDM) has emerged as a widely utilised method for machining of intricate geometries and the hard materials. EDM is a category of thermo-electric process that employs rapid recurring sparks between the electrode and work material, eroding the material without direct contact. As there is no contact between the electrode and work material, the issues related to machining defects such as mechanical stresses, clattering, and vibration eliminates. However, EDM have some limitations like poor surface finish and low volumetric material removal. To overcome these kind of limitations, the introduction of metallic powder into the dielectric fluid has been explored in powder-mixed electric discharge machining (PMEDM). This introduction of powder during the process leads to enhance the conductive strength of the fluid and increases the spark gap distance between the electrode and counter material. The inclusion of powder has a significant impact on the performance of the EDM process. Hence, this review aims to facilitate researchers in comprehending the concept of PMEDM and to examine the process parameters required to achieve improved levels of quality.

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.

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.

As the population of the world is continuously increasing, demand of the mechanical manufactured products is also increasing. Machining is the most important process in any mechanical manufacturing, and in machining two factors, i.e. material removal rate (MRR) and surface roughness (SR) are the most important responses. If the MRR is high, the product will get desired shape in minimum time so the production rate will be high, but we could not scarify with the surface finishing also because in close tolerance limit parts like in automobile industry, if the surface is rough exact fit cannot take place.

The term optimization is intensively related to the field of quality engineering. Abrasive water jet machining is an important unconventional machining, in order to obtain better response, i.e. material removal rate and surface roughness. Various process parameters of AWJM need to be observed and selected to improve machining characteristics. Better machining characteristics can be achieved by optimizing various process parameters of AWJM.

This study considers four process control parameters such as transverse speed, standoff distance, abrasive flow rate and water pressure. The response is taken to be material removal rate and surface roughness. The work piece for stainless steel AISI 304 material of size 15 cm × 10 cm × 2 cm is selected for experiments. Sixteen experimental runs (two trials for each experimental runs) were carried out for calculating MRR and SR and average value of these two trials have been taken for analysis. MRR is normalized according to higher-is-better and SR is normalized according to lower is better. The experiment data analysis is done and VIKOR index is found. Finally, the analysis of VIKOR index using S/N ratio is done and found the most significant factor for AWJM and predicted optimal parameters setting for higher material removal rate and lower surface roughness. Verification of the improvement in quality characteristics has been made through confirmation test with the predicted optimal parameters setting. It is found that the determined optimum combination of AWJM parameters gives the lowest VIKOR INDEX which shows the successful implementation of VIKOR Method coupled with S/N ratio in AWJM.

This work investigates the influence of tool surface area (TSA) on the average surface roughness ($R_a)$, tool wear rate (TWR) and material removal rate (MRR) in the micro-electrical discharge machining ($\mu$EDM). The effects of three different TSAs were investigated at three different discharge energy settings. It was observed that the TSA had substantial influence on $\mu$EDM performance owing to scaling effect. Therefore, the low-frequency workpiece vibration was applied to improve the $\mu$EDM performance. The surface topography of machined surfaces was examined using scanning electron microscopy to disclose the effect of TSA as well as vibration frequency on $\mu$EDMed surfaces.

This article presents an experimental study of a recently developed process, namely, ultrasonic assisted jet electrochemical micro-drilling (UAJet-ECMD) using pulsed DC voltage power supply. The goal of the work was to examine the effect of pulsed DC voltage on the performance of UAJet-ECMD process. In the previous work carried out by the authors, the process has been studied using the continuous DC voltage. The pulse “on” time (pulsed DC voltage), electrolyte pressure and pulse “on” time (ultrasonic vibrations) were selected as the process parameters, whereas material removal rate (MRR) and hole taper were chosen as process responses. It was found that the pulse “on” time (pulsed DC voltage) had crucial effect on the MRR as well as on the hole taper. MRR and hole taper were both found to increase with rise in pulse “on” time (pulsed DC voltage). Optimization of process responses of UAJet-ECMD process was done. The responses obtained for optimized set of process parameters were verified and found in good conformity with the experimental results.

Inconel 625 possesses excellent mechanical, chemical, and physical properties thus commonly used in different sectors. Due to its wide use, it becomes important to investigate its mechanical characteristics under die-sinking EDM. In this research, an empirical model is constructed to investigate the optimal parametric setting of die-sinking EDM. The experimental runs are developed using a Taguchi design. It has been observed from the analysis that peak current followed by pulse on time is the most significant parameter for MRR followed by pulse on time. However, the SR gives significant results on the pulse on time. The confirmatory test is conducted to validate the efficacy of the proposed 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.

The material removal rate (MRR) during precision finishing/polishing is a key factor, which dictates the process performance. Moreover, the MRR or wear rate is closely related to the material/part reliability. For nanoscale patterning and/or planarization on nano-order thickness coatings, the prediction and in-process monitoring of the MRR is necessary, because the process is not characterizable due to size effects and material property/process condition variations as a result of the coating/substrate interactions. The purpose of this research was to develop a practical methodology for the prediction and in-process monitoring of MRR during nanoscale finishing of coated surfaces. Using a specially designed magnetic abrasive finishing (MAF) and acoustic emission (AE) monitoring setup, experiments were carried out on indium-zinc-oxide (IZO) coated Pyrex glasses. After a given polishing time interval, AFM indentation was conducted for each workpiece sample to measure the adhesion force variations of the coating layers (IZO), which are directly related to the MRR changes. The force variation and AE monitoring data were compared to the MRR calculated form the surface measurement (Nanoview) results. The experimental results demonstrate strong correlations between AFM indentation and MRR measurement data. In addition, the monitored AE signals show sensitivity of the material structure variations of the coating layer, as the polishing progresses.

Research on machining continues increasingly today. The effects of independent variables (cutting speed, feed rate, cutting depth) on dependent variables (material removal rate (MRR), average surface roughness (Ra), sound intensity, energy consumption, and vibration) are among the most researched topics in machining. It is also important to achieve optimum results with low cost and time savings in machining.

In this study, titanium alloy TC4 material was turned on CNC lathe. Taguchi L${}_{16}$ mixed level design was used in experimental design. MRR, Ra, sound intensity, energy consumption, and vibration values were measured for the determined cutting parameters. The measured values were researched experimentally and statistically. Effective parameters were determined. It was concluded that the cutting parameter that has the greatest effect on MRR, Ra, energy consumption, and vibration is the feed rate. In addition, the depth of cut was the parameter that most affected the sound intensity. Control experiments were carried out after determining the optimum machining parameters. With multiple optimization, the predictions were made with approximately 89% accuracy (92.75% for MRR, 92.49% for Ra, 89.45% for sound intensity, 92.70% for energy consumption, 96.16% for vibration).

In this paper, experimental analysis was performed during micro-electrical discharge machining (micro-EDM) of titanium alloy Ti–6Al–4V (grade 5) using three types of tools viz. copper (Cu) tool, tungsten carbide (WC) tool, and synthetic graphite (Gr) grade three tool. The main process parameters were taken as (a) pulse on time ($T_{\mathrm{\text{on}}}$), (b) pulse off time ($T_{\mathrm{\text{off}}}$), (c) voltage (V), and (d) capacitance (C). The output responses were taken as the material removal rate (MRR) and tool wear rate (TWR). Taguchi method coupled with grey relational analysis (GRA) (L${}_{16}$ orthogonal array) technique was applied to optimize the input process parameters for both the responses. Scanning electron microscopy (SEM) analysis of the workpiece and tool was also performed to investigate the morphology of the machined surface and tool surface. Energy-dispersive spectroscopy (EDS) analysis was performed to investigate the elemental composition of the machined surface. The experimental finding reveals that tungsten carbide is the most suitable tool material for machining the chosen workpiece for obtaining optimal MRR and TWR. The optimum condition for the copper tool was found as 180V, 1000pf, 10$\mu$s ($T_{\mathrm{\text{on}}}$), and 10$\mu$s ($T_{\mathrm{\text{off}}}$). Meanwhile, the optimum parametric condition for tungsten carbide and graphite tools was found to be the same as 240V, 100pf, 20$\mu$s ($T_{\mathrm{\text{on}}}$), and 5$\mu$s ($T_{\mathrm{\text{off}}}$).

In the present study, aluminum alloy (Al/3.25Cu/8.5Si) composites reinforced with fly ash particles was fabricated using stir casting technique. Fly ash particles of three different size ranges 53–75, 75–103 and 103–125$\mu$m of 3, 6 and 9 weight percentages was reinforced in aluminum alloy. The effect of peak current, pulse on time, and pulse off time on surface roughness (SR), material removal rate (MRR) and tool wear rate (TWR) of electric discharge machining (EDM) was investigated. A central composite design using response surface methodology (RSM) was selected for conducting experiments, and mathematical models were developed using Design Expert V7.0.0 software. Analysis of variance (ANOVA) technique was used to check the significance of the models developed. Peak current was the major factor influencing the EDM of aluminum fly ash composites. The MRR, TWR, and SR of aluminum fly ash composites were also influenced by the size of the fly ash particles.

An experimental investigation was conducted to evaluate the machinability of a titanium alloy (Ti6Al4V) using copper (Cu), tungsten carbide (WC), and graphite (C) tools. Voltage (V), capacitance (pF), pulse-on time (T_on), and pulse-off time (T_off) were considered as the input machining parameters, whereas the material removal rate (MRR) and tool wear rate (TWR) were considered as the output machining parameters. A Taguchi L${}_{16}$ orthogonal array and gray relational analysis (GRA) were utilized to design and optimize the machining parameters for both responses. Artificial neural network (ANN) analysis was performed to predict the experimental outcomes. Scanning electron microscopy (SEM) and energy-dispersive spectroscopy (EDS) were used to assess the surface morphology and determine the elemental composition of the machined surface. The results indicated that the optimum machining conditions for the copper tool were 150 V, 1000 pF, 15$\mu$s (T_on), and 15$\mu$s (T_off). However, the optimal machining conditions for the WC were 200 V, 100 pF, 25 $\mu$s (T_on), and 10$\mu$s (T_off), and the optimal conditions for the C were 200 V, 1000 pF, 20$\mu$s (T_on), and 25$\mu$s (T_off), respectively. The highest MRR achieved using the WC tool was 9.4510 mg/s, whereas the TWR of the Cu, WC, and C tools were 1.1039 mg/s, 1.0307 mg/s, and 1.2796 mg/s, respectively. The results showed that machining with the graphite tool had a higher TWR than machining with the Cu and WC tools.

The mechanical properties of Aluminum metal matrix composites (AMMCs) have made them a popular choice in various industries such as automotive, aerospace, and marine. However, their composition, which includes abrasive reinforcements, makes them difficult to machine using conventional techniques. So, unconventional machining processes play a vital role in the machining of these materials. Electrical discharge turning (EDT) is one of the configurations of electrical discharge machining (EDM) that is utilized to machine cylindrical-shaped workpieces. In this study, AMMC Al 7075/ZrO₂ was fabricated using the stir casting method. Further, investigated the effect of machining parameters of EDT, namely pulse Current (I), pulse on time (T-ON), and rotating speed (RPM), on Al 7075/ZrO₂ in terms of material removal rate (MRR), tool wear rate (TWR), and overcut (OC) using one parameter at a time (OPAT) method. The outcome of the experiment reveals that MRR, TWR, and OC are more impacted by pulse current than by rotational speed. A decrease in TWR was also found with an increase in pulse on time for all rotational speeds. The size of the craters and globules observed lower with 1400 RPM in the micrograph image.