Electrical Discharge Machining Performance Research Articles

Optimizing the Die-Sink EDM Machinability of AISI 316L Using Ti-6Al-4V-SiCp Electrodes: A Computational Approach

Die-sink electric discharge machining (EDM) is essential for shaping complex geometries in hard-to-machine materials. This study aimed to optimize key input parameters, such as the discharge current, gap voltage, pulse-on time, and pulse-off time, to enhance the EDM performance by maximizing the material removal rate while minimizing the surface roughness, residual stress, microhardness, and recast layer thickness. AISI 316L stainless steel was chosen due to its industrial relevance and machining challenges, while a Ti-6Al-4V-SiCp composite electrode was selected for its thermal resistance and low wear. Using Taguchi’s L27 orthogonal array, this study minimized the trial numbers, with analysis of the variance-quantifying parameter contributions. The results showed a maximum material removal rate of 0.405 g/min and minimal values for the surface roughness (1.95 µm), residual stress (1063.74 MPa), microhardness (244.8 Hv), and recast layer thickness (0.47 µm). A second-order model, developed through a response surface methodology, and a feed-forward artificial neural network enhanced the prediction accuracy. Multi-response optimization using desirability function analysis yielded an optimal set of conditions: discharge current of 5.78 amperes, gap voltage of 90 volts, pulse-on time of 100 microseconds, and pulse-off time of 15 microseconds. This setup achieved a material removal rate of 0.13 g/min, with reduced surface roughness (2.46 µm), residual stress (1518.46 MPa), microhardness (259.01 Hv), and recast layer thickness (0.87 µm). Scanning electron microscopy further analyzed the surface morphology and recast layer characteristics, providing insights into the material behavior under EDM. These findings enhance the understanding and optimization of the EDM processes for challenging materials, offering valuable guidance for future research and industrial use.

Optimization of electrical discharge machining parameters for enhanced performance on inconel 718 using Cu-Ni-B4C nanocomposite electrodes and advanced modeling techniques

Abstract This paper investigate into the complex field of electrical discharge machining (EDM) to improve material removal rate (MRR), electrode wear rate (EWR), and surface roughness (SR) for the machining of Inconel 718, a difficult-to-machine superalloy. The effects of discharge current, pulse duration, and pulse interval on machining performance were assessed through experiments. Response surface methodology (RSM) and artificial neural network (ANN) models, such as RNN, LSTM, and CNN, were used to optimize. Twenty runs of confirmation experiments were used to confirm the optimal process parameters found by the created models for better machining. For Inconel 718, the novel Cu-Ni-B4C nanocomposite electrode greatly enhanced EDM performance. The ideal configuration increased MRR while decreasing wear and surface roughness. Machined surfaces were inspected using SEM and EDAX analysis. With optimal settings of 50 μs pulse duration and 90 μs pulse interval, increasing current to 8 Amps increased MRR to 0.0118 g min−1, reducing EWR to 0.001 g min−1 and SR to 3.108 μm. Compared to the RNN, LSTM, and RSM models, the CNN model had the greatest R-squared (R2) score of 0.9999, suggesting greater MRR, EWR, and SR prediction.

SURFACE MORPHOLOGY OF SILICON NITRIDE (Si3N4)-TITANIUM NITRIDE (TiN) COMPOSITES USING GRA-RSM STRATEGY ENCOMPASSED WITH EDMed PARAMETERS

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 0.0281[Formula: see text]gm/min), a low EWR (at 0.0020[Formula: see text]gm/min), and a significant improvement in SR (at 0.3150[Formula: see text][Formula: see text]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.

Comparative study on manufacturing of EDM electrodes by laser sintering process

The abstract aims to investigate the comparative performance of Electrical Discharge Machining (EDM) and Selective Laser Sintering (SLS) with unconventional machining processes. Unconventional machining processes have gained significant attention due to their versatility and capability to fabricate intricate components with high precision. This study focuses on assessing the efficacy of EDM and SLS techniques in terms of data removal rate and relative wear volume. Electrical Discharge Machining (EDM) is a thermal erosion process that utilizes electrical discharges to remove material from a workpiece. In contrast, Selective Laser Sintering (SLS) is an additive manufacturing technique that employs a laser to selectively fuse powdered material, layer by layer, to build up a three-dimensional object. Both methods offer unique advantages in terms of precision, speed, and material compatibility. The performance evaluation of these techniques involves analyzing key parameters such as data removal rate, which measures the volume of material removed per unit time, and relative wear volume, which quantifies the wear on the tool or workpiece during the machining process. By comparing these metrics, insights into the efficiency and effectiveness of EDM and SLS can be gained, aiding manufacturers and researchers in selecting the most suitable method for specific applications. Through experimental investigations and data analysis, this study aims to provide valuable insights into the capabilities and limitations of EDM and SLS in unconventional machining processes. The findings will contribute to advancing the understanding of these techniques and optimizing their utilization in various industrial sectors, including aerospace, automotive, and biomedical engineering. The experimental analysis examines the impact of the Direct Metal Laser Sintering (DMLS) process parameter on sintering depth. The optimized parameters for AlSi10Mg alloy powder sintering were obtained using laser power at 162 W, scanning speed at 156 mm s−1, porosity at 20%, laser area size of 0.2 mm, and layer thickness of 1 mm.

Analysis and experimental investigation of powder concentration and stirring velocity on powder mixed electrical discharge machining performance with 3D printed electrodes

In this work, CuO mixed lemon peel dielectric is used along with the 3D printed aluminium electrodes to enhance the electrical discharge machining (EDM) performance. This work mainly focuses on improving the surface quality by optimizing the powder concentration and stirring velocity. A full factorial of 27 experiments is carried out with input parameters such as pulse off time with 3 levels (28, 58 and 98 μs), powder concentration with 3 levels (1, 2 and 3 g/L) and stirring velocity with 3 levels (900, 1800 and 2700 rpm), while keeping the current, pulse on and voltage as constant. For all trials, the output responses viz. surface roughness (SR) and material removal rate (MRR) are noted. It is evidenced that EDM performance is influenced by the stability of powder mixed dielectric. To understand the most influential input parameter and its level, analysis of variance (ANOVA) and grey relational analysis (GRA) are carried out. The output analysis exhibited that powder concentration of 2 g/L, stirring velocity of 1800 rpm and pulse off time of 28 μs as the best combination for the best quality of finish (4.72 μm) with high MRR (0.0035 g/min) than the 1 g/L PC with 900 rpm SV for the best quality finish (5.87 μm) along high MRR (0.0029 g/min) and 3 g/L PC with 2700 rpm SV for the best quality finish (5.38 μm) with high MRR (0.0030 g/min) having pulse off time of 28 μs. The experimental findings are validated with a 3D surface plot and SEM images taken on the machined surface. Also, a simulation model is built to understand the flow velocity profiles. This helps ensure the minimum stirring velocity to be maintained to enhance the stability of powder mixed dielectric.

Enhancing EDM performance with multi-objective decision-making using copper-coated aluminum electrodes and TOPSIS methodology for Ti-6Al-4V machining

The exploration of Electrical Discharge Machining (EDM) with coated electrodes represents a relatively novel research avenue, thereby yielding limited published research outcomes. The choice of coating material plays a pivotal role in the EDM machining process, and alterations in coating materials can directly influence the adjustment of technological parameters in EDM. Consequently, research dedicated to optimizing these technological parameters for EDM employing coated electrodes is of paramount importance, and it promises to advance the practical implementation of this cutting-edge technique. In this study, we systematically investigate the technological parameters for EDM employing a copper-coated aluminum electrode in the context of Ti-6Al-4V machining. Our research outcomes are framed within a multi-objective optimization paradigm, with a focus on Material Removal Rate (MRR) and Surface Roughness (SR) as vital quality indicators. To address the intricate multi-objective optimization challenge, we have harnessed the combined power of the Taguchi methodology and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The amalgamation of these techniques enables us to navigate the complexities of EDM parameter optimization effectively. Our findings reveal that the most favorable process parameters entail a configuration of [Formula: see text][Formula: see text]V, [Formula: see text] A, [Formula: see text][Formula: see text][Formula: see text]s, resulting in an MRR of 0.028[Formula: see text]mg/min and an SR of 7.56[Formula: see text][Formula: see text]m. These optimized parameters exemplify a substantial enhancement in machining efficiency and surface quality when utilizing coated electrodes. Moreover, our study scrutinizes the quality of the machined surface under optimal conditions with coated electrodes. We employ the TOPSIS method as a proficient solution for this endeavor, offering a straightforward approach to this intricate calculation process.

PERFORMANCE EVALUATION AND ECONOMIC ASSESSMENT IN ELECTRICAL DISCHARGE MACHINING OF SS316 USING GRAPHITE POWDER DISPERSED IN BIODEGRADABLE PALM OIL DIELECTRIC

In today’s rapidly evolving manufacturing industry, researchers and engineers are constantly seeking innovative methods to improve machining processes. One such area of interest is the use of electrical discharge machining (EDM) for difficult-to-machine metals like SS316. This research compares the performance and economic aspects of traditional EDM and powder-mixed EDM when machining SS316 using copper electrode. Graphite powder dispersed in biodegradable palm oil is investigated as a dielectric media with the aim of enhancing EDM performance. According to the findings, the analysis of the cutting performance of different machinability aspects revealed that using graphite powder mixed with palm oil as a dielectric in EDM outperformed conventional EDM relating to material removal, surface finish, surface hardness, electrode wear rate and hole overcut. The flushing condition and unique properties of graphite powder and palm oil, such as cooling, and thermal conductivity, contributed to the improved performance observed in EDM processes. These findings highlight the potential of graphite powder mixed with palm oil as a promising alternative dielectric in EDM, offering enhanced machining capabilities and improved surface quality. The total machining expenditure per part under PMEDM (INR 505.50) is lowered by 9.2% than expenditure under conventional EDM (INR 525). The surface microhardness of the machined component attained using graphite powder-mixed EDM is enhanced in comparison to that achieved using standard EDM due to the creation of a carbon-rich re-solidified layer.

A comprehensive review of parametric optimization of electrical discharge machining processes using multi-criteria decision-making techniques

Optimization of electrical discharge machining (EDM) processes is a critical issue due to complex material removal mechanism, presence of multiple input parameters and responses (outputs) and interactions among them and varying interest of different stakeholders with respect to relative importance assigned to the considered responses. Multi-criteria decision making (MCDM) techniques have become potent tools in solving parametric optimization problems of the EDM processes. In this paper, more than 130 research articles from SCOPUS database published during 2013–22 are reviewed extracting information with respect to experimental design plans employed, materials machined, dielectrics used, process parameters and responses considered and MCDM tools applied along with their integration with other mathematical techniques. A detailed analysis of those reviewed articles reveals that the past researchers have mostly preferred Taguchi’s L9 orthogonal array as the experimental design plan; EDM oil as the dielectric fluid; medium and high carbon steels as the work materials; peak current and pulse-on time as the input parameters; material removal rate, tool wear rate and surface roughness as the responses; and grey relational analysis as the MCDM tool during conducting and optimizing EDM operations. This review paper would act as a data repository to the future researchers in understanding the stochastic behaviour of EDM processes and providing guidance in setting the tentative operating levels of varying input parameters along with achievable response values. The extracted dataset can be treated as an input to any of the machine learning algorithms for subsequent development of appropriate prediction models. This review also outlines potential future research avenues, emphasizing advancements in EDM technology and the integration of innovative multi-criteria decision-making tools.

Design of experiments integrated with neural networks for optimization and predictive modelling of electrode wear of novel Ti-6Al-4V-SiCp composites during die sinking electric discharge machining

Die Sink Electric Discharge Machining is a widely used manufacturing process for shaping hard and electrically conductive materials. This study investigates the effects of various electrode materials such as, Ti-6Al-4V-SiCp, Brass and Copper on the machining performance of AISI 316 l Stainless Steel workpieces using EDM. The methodology involved optimizing parameters such as Electrode Material, Discharge Current, Gap Voltage, Spark Gap, Pulse-on Time, and Pulse-off Time. From the extensive experimantation it was observed that the combination of Ti-6Al-4V-SiCp electrode material, 8Amp Discharge Current, 90 V Gap Voltage, 75 μm Spark Gap, 100 μs Pulse-on Time and 15 μs Pulse-off Time has resulted in lowest electrode eear rate, higher machining time, and low electrode surface roughness ratio. Ti-6Al-4V-SiCp electrodes possess higher hardness and electrical conductivity compared to Brass and Copper Electrodes leading to higher wear resistance against repeated thermal shocks during electric discharge machining operation. Feed Forward Artificial Neural Network is successfully applied to predict the output characteristics of the experimentation with high accuracy of 98.3% (Electrode Wear Rate), 94.6% (Machining Time) and 93.8% (Electrode Surface Roughness Ratio). Further, microstructure analysis concludes that lowest wear is observed in Ti-6Al-4V-SiCp electrodes compared to Brass and Copper electrodes.

Comprehensive stratified K-fold machine learning for surface roughness prediction with 3D printed electrodes: Analyzing dielectric variability and heat treatment effects

Electrical discharge machining (EDM) is popular for its accuracy in cutting difficult materials. Material removal rate (MRR), electrode wear ratio (EWR) and surface roughness (SR) are deemed as the success indicators in EDM. The positive attributes of sustainable manufacturing make it a suitable choice for diverse applications. EDM electrodes used in this work are prepared by 3D printing and further subjected to deep cryogenic treatment (DCT) to investigate the influence of heat treatment on EDM performance. In the second instance, the experiments are conducted with different dielectric fluids viz. conventional dielectric (CD) and lemon peel biodiesel dielectric (LPD) to analyze the impact of dielectric change. When the dielectric is changed to lemon peel biodiesel, the roughness of the electro-discharged machined surface is reduced to a maximum of about 33%. A further improvement of about 11% is possible in the surface finish of machined surfaces when the EDM electrodes are subjected to DCT under an identical operating condition. LPD as dielectric also helps in attaining the primary objective of green manufacturing by reducing specific evaporative emissions. During the EDM process, LPD adoption causes a reduction of 96% in nitrogen oxide (NO) emissions and 86% in hydrocarbon (HC) emissions. A modified adaptive neuro fuzzy inference system (ANFIS) with a stratified k-fold machine learning approach with a prediction accuracy of about 95% is also developed in this work to envisage the surface roughness of electro-discharge machined surfaces.

Comparative performance evaluation and economic assessment between traditional and vibration assisted EDM during machining of Inconel 718

Nickel based superalloy, Inconel 718 offers extensive applications in aerospace and gas turbine industries because of its outstanding properties, enabling high performance in various critical components. Despite the wide application of electric discharge machining (EDM) for difficult-to-cut conductive materials, the process becomes less productive due to unstable arcing and inadequate debris flushing during machining, leading to reduced operational efficiency. This research focuses on comparative performance evaluation and economic assessment between conventional-EDM and vibration assisted EDM (VA-EDM) while machining Inconel 718 with copper electrode. The workpiece was excited to vibrate with low frequency by employing unbalanced mass attached in a rotary motor with the aim of enhancing EDM performance. Material removal rate MRR, surface integrity (surface crack density SCD, surface roughness Ra, white (recast) layer thickness WLT) and tool wear rate TWR are analyzed to determine machining performance in comprehensive analysis. The results of the performance comparison show that vibration assisted is superior to the conventional-EDM process concerning enhanced material removal rate, and surface morphology with minimum surface crack density, tool wear rate and white layer thickness. The mean value ratios for Ra EDM/ Ra VA-EDM, TWR EDM/ TWR VA-EDM, WLT EDM/ WLT VA-EDM, and SCD EDM/ SCD VA-EDM are 1.35, 1.52, 1.21, and 1.74, respectively. Additionally, the surface integrity was enhanced using vibration-assisted EDM because it (a) increases the plasma flushing efficiency and the gap pressure gradient; (b) raises the energy of electrically charged plasma particles; (c) increases the effective flow of dielectric in the gap; (d) minimizes the number of ineffective pulses (short-circuiting and arching) on the surface; and (e) improves the dielectric flushing conditions in sparking gap. According to the findings, the overall machining expenditure per part under VA-EDM in Indian rupees (INR) 534 is lowered by 8% than expenditure under conventional-EDM (INR 576.60). The outcomes of this research have the potential to benefit numerous industries that deal with difficult-to-cut materials.

Machining and wear rates in EDM of D2 steel: A comparative study of electrode designs and materials

Electrical discharge machining (EDM), especially the die-sinking variant, is a well-known slow machining process among non-conventional manufacturing processes. Different approaches are being researched to improve EDM performance characteristics especially increasing its material removal rate (MRR) and reducing the tool wear rate (TWR). This study aims to improve the EDM process performance through modifications in tool design and employing different tool materials. The performance of conventional EDM tool is compared with different tool designs while machining D2 steel. Moreover, tool designs are employed on different tool materials including copper (Cu), copper-tungsten alloy (CuW), and graphite (Gr) to investigate the combined effect of tool designs and materials on important performance indicators of EDM die-sinking. The machining time (MT), material removal rate (MRR), lateral tool wear (TWR_L), and diametric tool wear (TWR_D) are selected as the response measures. The modified tool designs reduce the machining time by 45%. Likewise, Cu and CuW remarkably improve the material removal rate by 80%. Similarly, the lateral and diametric tool wear of modified designs are less than the wear corresponding to conventional design. Microscopic analysis revealed two wear zones which are named as aggressive sparking zone and mild sparking zone. All materials (Cu, CuW, and Gr) with the modified tool designs show significantly less sparking zone compared with the conventional design. Moreover, the most appropriate combination of tool design and material is proposed to achieve better EDM performance.

Machinability of different cutting tool materials for electric discharge machining: A review and future prospects

Electric Discharge Machining (EDM) is essential for shaping and cutting tool steel. EDM’s precision in machining difficult materials and tool steel characteristics are well known. EDM efficiency requires reliable performance measurement parameters. The physical shape and mobility of the electrode tool are critical in EDM research. Layer machining is an advanced method that removes material in a sequential manner to produce intricate 3D shapes in tool steel and several other materials. The improvement in layer machining methods with precise toolpath algorithms, adaptive layer thickness management, and real-time monitoring systems is required to maximize precision and efficiency. Response surface methodology, the artificial neural network, and other techniques are necessary to optimize EDM operations and maximize performance. Many researchers experimented with electrode shapes and movement patterns to enhance the removal of material and the quality of surfaces. Investigation of complex electrode structures and innovative tool path strategies has been performed in previous studies. It was very difficult to consider various factors during the EDM operation; hence, the present review summarizes the positive outcomes of previous research. The review emphasizes optimizing pulse duration and discharge current to improve EDM efficiency. The present comprehensive review discusses research on EDM in three main areas: electrode tool geometry and motion, tool steel layer processing, and factors for measuring EDM performance. The objective of the present review is to focus on measuring material removal rates, surface roughness, tool wear, and energy usage. The present review concludes that EDM is crucial to machining tool steel and cutting tool materials. Integrating and hybrid machining technologies can improve performance, and improved optimization techniques are crucial. It also recognizes knowledge gaps and explores new frontiers in this dynamic field.

Electrode Wear Rate of RBD Palm Oil as Dielectric Fluids on Electrical Discharge Machining (EDM) at Different Peak Current and Pulse Duration of Titanium Alloys

Electrical Discharge Machining (EDM) is a widely utilized commercial method for generating a variety of forms of materials that are used as the fundamental material in a wide range of industries. Vegetable oil as the dielectric fluid is one technique for assuring EDM's long-term viability because it is ecologically benign and biodegradable. This article presents experimental investigations on the influence of electrical discharge machining (EDM) input parameters on electrode wear rate (EWR) while using EDM oil and vegetable oil as dielectric fluid. Kerosene which is known as conventional oil for EDM has been used as a benchmark to compare the feasibility of the EDM process by using a different type of dielectric fluid which is RBD palm oil. Peak currents (Ip) in the 6 to 12A range and pulse durations (ton) in the 50 to 150 µs range were chosen as the major factors for this study to improve the efficiency of EDM operation. Scanning electron microscopy (SEM) was used to observe the morphology surface characteristics of the copper electrode and the migration of workpiece material elements to the tool electrode. The EWR increases with increasing peak current, although it is inversely related to pulse duration. The lowest EWR for kerosene and RBD palm oil is 0.0416mm3/min and 0.0480mm3/min, respectively, at the same IP=6A and ton=150µs. Simultaneously, the highest EWR for both kerosene and RBD palm oil was at the same IP=12A and ton=50µs, which is 0.1725mm3/min and 0.2425mm3/min, respectively.

Optimizing micro-EDM with carbon-coated electrodes: A multi-criteria approach

The pursuit of precision machining in engineering materials has ignited an imperative to advance electrical discharge machining (EDM) techniques. This study is a deep dive into the domain of micro-electrical discharge machining ([Formula: see text]EDM) with a specific focus on the utilization of carbon-coated tool electrodes. The primary objective is to elucidate the influence of carbon-coated electrodes on vital machining parameters, including machining depth (Z coordinate), tool wear rate (TWR) and overcut (OC) in [Formula: see text]EDM operations. Moreover, the investigation extends to scrutinizing surface characteristics generated by [Formula: see text]EDM with carbon-coated tool electrodes. To enhance performance, carbon-coated tungsten carbide tool electrodes are employed for machining titanium alloy (Ti–6Al–4V) workpieces. The optimization process seeks to identify the optimal combination of process parameters using a Taguchi-DEAR-based multi-response approach. Experimental findings reveal that integrating carbon-coated electrodes significantly improves the [Formula: see text]EDM process, leading to enhanced surface performance metrics. Notably, this study identifies specific parameter settings that effectively optimize machining quality indicators. By achieving a voltage of 160[Formula: see text]V, a capacitance of 10,000[Formula: see text]pF and a tool rotation of 600[Formula: see text]RPM, the research contributes valuable insights into the intricate realm of [Formula: see text]EDM, highlighting the potential for enhanced surface performance through strategic parameter manipulation.

Novel B4C[sbnd]TiB2 composites with high electrical and low thermal conductivity by selective grain growth in reactive sintering

High electrical conductivity and low thermal conductivity are beneficial for the electrical discharge machining performance of ceramics. In this work, B4C–TiB2 composites were prepared by spark plasma sintering of B4C–TiC–B powder mixture. The chemical reaction between TiC and B, together with subsequent selective matrix grain growth, expelled small in-situ generated TiB2 grains to form conductive interlayers around large B4C grains. The unique microstructure significantly enhances the electrical conductivity of B4C–TiB2 composites, especially at low TiB2 content, while the ultrafine in-situ formed TiB2 grains endow the composites with low thermal conductivity. The effects of TiB2 content on the microstructure, mechanical properties, thermal & electrical conductivity of the composites were investigated. B4C–20 vol% TiB2 composite exhibits excellent comprehensive performance, including a relative density, Vickers hardness, flexural strength, fracture toughness, room electrical and thermal conductivity of 98.6%, 28.15 GPa, 656 MPa, 5.46 MPa⋅m1/2, 1.08 × 105 S/m and 19.37 W/m⋅K, respectively.

Electrical discharge machinable B4C–(Zr, Ti)B2 composites with enhanced mechanical properties

B4C30 vol% (ZrxTi1-x)B2 (x = 0.2, 0.4, 0.6 and 0.8) composites were fabricated via in-situ reaction by spark plasma sintering using B4C, ZrC, TiC and B powders as raw materials at 2000 °C. The effects of the Zr/Ti ratio in the (ZrxTi1-x)B2 phase on the microstructure and mechanical properties of the composites were investigated. The electrical discharge machining performance of the composites was evaluated. The formation of (Zr, Ti)B2 solid solutions was beneficial to fully dense composites with refined grains. The grain size of the (Zr, Ti)B2 phase first gradually decreased from 1.26 µm to 0.89 µm and then increased to 1.23 µm with the decreasing ZrC/TiC molar ratio. The material removal rate was slightly decreased from 6.56 mm3/min to 5.17 mm3/min with the decreasing ZrC/TiC molar ratio. The combined solid-solution and fine-grain strengthening has made the B4C30 vol% (Zr0.2Ti0.8)B2 composite enhanced Vickers hardness, flexural strength, and fracture toughness of 28.31 GPa, 772 MPa, and 6.56 MPa·m1/2, respectively, with a relative density of 99.73%.

Enhanced Powder Mixed Electrical Discharge Machining Performance toward Improved Machining Characteristics for Inconel 625 Super Alloy by Response Surface Methodology and Fuzzy Logic Techniques

Enhanced Powder Mixed Electrical Discharge Machining Performance toward Improved Machining Characteristics for Inconel 625 Super Alloy by Response Surface Methodology and Fuzzy Logic Techniques

Enhancing performance of electrical discharge machining by ultrafine-grained Cu-0.5%Cr electrode

Enhancing performance of electrical discharge machining by ultrafine-grained Cu-0.5%Cr electrode

Effect of Impregnation and Graphitization on EDM Performance of Graphite Blocks Using Recycled Graphite Scrap

In the present study, graphite scrap powder from machining of commercial graphite blocks for electrical discharge machining (EDM) applications was recycled as a filler material for manufacturing graphite blocks, and its suitability for use as EDM electrodes was thoroughly assessed. The effects of process parameters applied in EDM electrode manufacturing, including the number of impregnations and graphitization temperatures, on the physical properties of the resulting graphite blocks, were examined. Additionally, EDM performance was evaluated with respect to the above process parameters. In blocks subjected to three impregnation treatments, followed by graphitization at 2200 °C, surface protrusions formed during the EDM process, indicating that the EDM process did not proceed smoothly. On the other hand, in blocks that underwent three impregnation treatments, followed by graphitization at 2800 °C, no surface protrusions were observed, indicating successful EDM operation. This observation further confirms the suitability of these recycled materials for use in EDM electrodes. The graphite block electrodes fabricated using recycled graphite scrap exhibited inferior cyclic stability, with an electrode wear rate of 0.82%, higher than that of a commercial graphite block electrode (0.04%). Nevertheless, using recycled graphite scrap contributes to reducing product costs and CO2 emissions, making the developed graphite electrodes a favorable choice.