Electrical Discharge Machining Performance Research Articles

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.

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.

Viability and performance assessment of bipolar linear self-servo mechanism-based Maglev electrical discharge machining by processing Al-6062 alloy

The enhancement of process efficiency and eradication of basic setbacks of the electrical discharge machining (EDM) process has paved the way for its technological advancement. The discharge irregularities observed during conventional EDM operation due to servo-feedback delay have been addressed by implementing a novel bipolar linear self-servo strategy in Maglev EDM. The paper evaluates the viability of the novel Maglev EDM and analyses its performance in machining aluminum (Al) 6062 alloy. The Maglev EDM uses a systematic combination of magnetic repulsive forces to attain tool positioning in the Z-direction, which serves as the servo gap control mechanism. Experiments were carried out on Al-6062 alloy by utilizing brass tools and surrounding air as dielectric. The voltage–current waveforms exhibited stable and uniform discharges devoid of the short-circuiting and arcing phenomenon. Material removal rate, specific energy, and centerline average surface roughness of 6.717 µg/s, 2.397 J/µg, and 3.735 to 4.507 µm were attained at a discharge power of 16.1 J/s, proving the operational viability of the Maglev EDM. The experimental results were further compared with data available in the previously reported literature. Resolidified layers, globules, lumps of debris, melted debris, micro-pores, micro-voids, micro-cracks, and craters were detected from field emission scanning electron microscopy analysis of the processed work surface. The existence of tool material in the processed surface by energy-dispersive X-ray spectroscopy analysis certified the material migration and surface alloying.

Enhancing Electric Discharge Machining Performance by Selecting Electrode Design and Geometrical Parameters for Square, Triangular, and Hexagonal Profiled Holes

Manufacturing of dies, molds, and their allied components requires the machining of holes with different profiles. Electric discharge machining (EDM) die-sinking is a crucial process used in the dies and molds manufacturing industry. By nature, EDM die-sinking is a relatively slow process in terms of material removal rate (MRR) and there are high amounts of tool material loss in terms of tool wear rate (TWR) which directly influence dimensional accuracies and surface roughness (SR). Therefore, the process is continuously evolving to address these limitations. The present research is aligned in this direction such as to bring improvements in MRR, TWR, and SR through modifications to the conventional electrode design and its geometrical parameters. Traditional designs of EDM electrodes have a uniform cross-section through the tool’s entire length and have only one geometrical parameter, i.e., the tool’s cross-section. To improve the EDM performance, traditional designs are completely modified by introducing several geometrical parameters such as relief angles, land thickness, cross-sectional area, shank height, circular relief, and non-circular relief, etc. Electrode designs are employed to mill non-circular profiles including triangular, square, and hexagonal shaped holes. The EDM performance measures strongly depend on the tool’s geometrical parameters (design type, relief angle, land thickness), machining profile (circular, square, triangle, hexagon), as well as the height/depth of the machining feature. By selecting proper tool designs and corresponding geometrical parameters, the EDM performance measures can be improved significantly.

Exploring the intricacies of machine learning-based optimization of electric discharge machining on squeeze cast TiB2/AA6061 composites: Insights from morphological, and microstructural aspects in the surface structure analysis of recast layer formation and worn-out analysis

Aluminium (Al) Alloy-6061/TiB2 was developed with Squeeze casting while varying composite quantities with titanium diboride (TiB2). The metallographic structure of the composite was investigated using EDS and scanning electron microscopy (SEM). The machining of developed composite is challenging with the conventional methods due to higher tool wear and surface roughness (Ra). This study analyses the output responses, and machinability of TiB2 of 15% volume reinforced AA6061 composites using Electrical Discharge Machining (EDM). The EDM operation variables such as current, pulse on time, and voltage gap were utilized to examine material removal rate (MRR), tool wear rate (TWR) and Ra employing Box–Behnken design of experiments. The MRR, TWR and Ra data acquired from various experiments were optimized considering single and multiple objectives by a hybrid approach. Machine learning (ML) was applied to predict responses using linear regression (LR), decision tree (DT) and random forest (RF). The samples' recast layer was examined using SEM, and the thickness of the recast layer was also documented. The Al6061 alloy's SEM micrographs reveal deep equiaxed dimples on its fracture surface, indicating a high level of plastic deformation before failure. TiB2 is evenly distributed as darker particles in the Al-matrix alloy with no directional-orientation. The Al6061-15 wt% TiB2 composites' fracture surfaces display deep dimples, ductile-fracture for Al6061 alloy due to higher plastic deformation, and cleavage facets in some areas. The aluminum alloy's wear pattern depicts long, extensive ploughing grooves with short cracks parallel to the sliding direction at the grooves' bottom. SEM micrographs in recast-layer formation have reported that molten metal ligaments break into droplets during flushing, exposing fresh surfaces. The aluminum alloy's groove width is larger compared to the composites. Thus, it can be observed that the wear tracks on the base Al6061 alloy are larger and deeper in comparison to the Al- 15 wt% TiB2 surface composites due to the presence of hard TiB2 particles. Also, the recast layer may be advantageous due to its wear-resistant properties. TiB2 has importance in an industry where components slide with each other it is used in disc brakes in automobiles. Compared to industry standards, single-objective optimization considerably enhanced the outcomes: MRR increased by 10.61%, TWR enriched by 25.91%, and Ra increased by 17.60%. According to an ANOVA, peak current contributed 87.88%, 98.18%, and 95.80% respectively to MRR, TWR, and Ra. It is requisite to investigate multi-objective optimization for EDM of Al6061-15 wt% TiB2 composites' owing to the diverse optimal factor combinations for responses. Ra was slightly increased by 1.14% due to simultaneous optimization utilizing hybrid techniques with Equal and Entropy weights, which diminished TWR by 11.74% and increased MRR by 11.66%. ML, particularly DT, improves machining performance by assisting productivity, durability, and cost-efficiency under changeable circumstances and raising forthcoming study possibilities.

Electric discharge machining of hybrid composite with bio-dielectrics for sustainable developments

ABSTRACT The hybrid composite (Al-SiC-Ni) has a wide range of applications due to its high strength-to-weight ratio and exceptional mechanical and wears resistance properties. Electric Discharge Machining (EDM) is a common method for machining high-strength composites. However, one significant challenge associated with EDM is the emission of harmful fumes caused by the thermal cracking of hydrocarbon-based dielectrics, as well as the rate of material removal, both of which impact process productivity. However, no research has been conducted on the effect of non-edible biodiesel-based bio-dielectrics on the EDM of hybrid composites (Al-SiC-Ni). As a result, the primary goal of this research is to assess the environmental effects of machining. This study specifically investigates the impact of four types of non-edible biodiesel-based bio-dielectrics on key EDM process output parameters such as material removal rate (MRR), tool wear rate (TWR), and surface roughness (SR). The EDM performance of the hybrid composite (Al-SiC-Ni) was compared to that of three electrode materials (copper, brass, and graphite) and four bio-diesel-based bio-dielectrics such as Neem biodiesel (NBD), Jatropha biodiesel (JBD), Pongamia biodiesel (PBD), and Polanga biodiesel (POBD). From investigation, it has been observed that the maximum value of material removal rate (MRR) for POBD using a graphite electrode was 18.54 mg/min, which was 58.5% higher than the MRR for JBD using a brass electrode (7.17 mg/min). And it was found that the MRR with POBD was 108.15% higher than with kerosene oil. The graphite as mentioned above electrode obtains its smoothest surface under POBD. This roughness value is 77.41% lower than the JBD value obtained. Tool wear is observed lowest in the brass electrode in conjunction with the JBD. It is 68.88% lower than the TWR value obtained with PBD using the same electrode material. The results indicated that biodiesel derived from non-edible oils could be a promising dielectric for the future of the EDM process.