EDM Process Research Articles

Multi-objective Optimization in EDM Process Using Backpropagation Neural Network-Genetic Algorithm (BPNN-GA)

Multi-objective Optimization in EDM Process Using Backpropagation Neural Network-Genetic Algorithm (BPNN-GA)

Experimental investigation on optimizing wire-cut EDM process parameters of hybrid MMC(AA7475/ZrO2/Gr) using artificial neural network

Abstract Wire cut Electrical discharge machining (WCEDM) is a widely used method for machining complex shapes in advanced materials like metal matrix composites (MMCs) and hybrid metal matrix composites (HMMCs). To address these challenges, this study focusses on the wire-cut EDM (WCEDM) process of a workpiece made from zirconium dioxide and graphite-reinforced aluminium alloy 7475 with a molybdenum electrode. The effects of input process variables such as peak current (IP), pulse-on-time (TON), and flushing pressure (PF) on the output response features are investigated. These output responses include material removal rate (MRR), surface roughness (SR), and wire wear ratio (WWR). To optimise the process parameters, the Taguchi design technique is used. An artificial neural network (ANN) with a feed-forward back propagation architecture is utilised to find the best fit for the optimisation challenges. ANN predicted the results with an accuracy of 97.81% for MRR, 97.95% for SR and 95.865% for WWR. The results reveal that the WCEDM of AA7475/ZrO2/Gr with a molybdenum electrode achieved minimal WWR and SR, while maximizing the MRR.

Enhancing EDM Productivity for Plastic Injection Mold Manufacturing: An Experimental Optimization Study.

Electrical erosion molding (EDM) is an unconventional machining technology widely used in the manufacture of injection molds for plastics injection molding for the creation of complex cavities and geometries. However, EDM productivity can be challenging, directly influencing mold manufacturing time and cost. This work aims to improve EDM productivity in the context of mold manufacturing for plastics injection molding. The research focuses on the optimization of processing parameters and strategies to reduce manufacturing time and increase process efficiency. Through a rigorous experimental approach, this work demonstrates that the optimization of EDM parameters and strategies can lead to significant productivity gains in the manufacture of plastic injection molds without compromising part quality and accuracy. This research involved a series of controlled experiments on a Mitsubishi EA28V Advance die-sinking EDM machine. Different combinations of pre-cutting parameters and processing strategies were investigated using copper electrodes on a heat-treated steel plate. Productivity was evaluated by measuring the volume of material removed, and geometrical accuracy was checked on a coordinate measuring machine. The experimental results showed a significant increase in productivity (up to 61%) by using the "processing speed priority" function of the EDM machine, with minimal impact on geometric accuracy. Furthermore, the optimized parameters led to an average reduction of 12% in dimensional deviations, indicating improved geometric accuracy of the machined parts. This paper also provides practical recommendations on the selection of optimal EDM processing parameters and strategies, depending on the specific requirements of plastic injection mold manufacturing.

Enhancing of Material Removal Rate and Surface Roughness in Wire EDM Process using Grey Relational Analysis

Enhancing of Material Removal Rate and Surface Roughness in Wire EDM Process using Grey Relational Analysis

Advanced membrane contactor coupled with electrodialysis metathesis for efficient carbon dioxide capture and waste salt remediation

Rapid development of society has led to significant increases in carbon dioxide (CO2) emissions, primarily driven by intensified industrial activities and urbanization. Capture and utilization of CO2 not only mitigate greenhouse gas emissions but also support the transition towards a circular economy by recycling CO2 into high-value products. This study proposed a membrane contactor and electrodialysis metathesis (MC-EDM) for CO2 capture, NH4HCO3 generation, and NaHCO3 conversion. The MC facilitated the selective capture of CO2 from gas streams. Concurrently, EDM enhanced the NaHCO3/NH4Cl conversion from NH4HCO3/NaCl through selective ion transport mechanisms. The key influencing factors (e.g., gas flow rate, liquid flow rate, and ammonia concentration) for the MC process were optimized to achieve 1.014 mol/L NH4HCO3 concentration with 88.73 % yield and 78.94 % CO2 removal efficiency. Moreover, the parameters (e.g., solid-liquid ratio, membrane type, operating voltage, and salt component ratio) for the EDM process were optimized to achieve NaHCO3 with a 90.9 % yield and 97.80 % purity. Economic analysis indicated the overall process for NaHCO3 recovery was approximately 0.3267 $/kg. The cyclic experiments demonstrated the stability of MC-EDM for high-value NaHCO3 recovery. Thus, the MC-EDM pathways contribute significantly to reducing greenhouse gas emissions from industrial processes while promoting resource efficiency and economic sustainability.

Sustainable EDM production of micro-textured die-surfaces: Modeling and optimizing the process using machine learning techniques

The present research explores the role of die-sinking EDM parameters, such as peak current, pulse duration, and gap voltage, and their proper selection for the cost-effective fabrication of negative micro-pillar-textured surfaces using a die-material of H13 steel alloy. The developed artificial neural networks (ANN) models of surface roughness and overcut outperform the response surface methodology models in predicting responses as higher ‘R2 values’ and lower ‘mean squared error’ with ANN models. A lower peak current of 2 A, lower pulse duration of 55.46 µs, and intermediate gap voltage of 37.83 V is selected from metaheuristic optimization approaches such as teaching–learning-based optimization and particle swarm optimization that are efficient and comparable with the desirability function-based approach while finding optimum parameter values. Further, sustainable fabrication of micro-textured H13 die surfaces is carried out on large areas using selected optimized parameters with a form tool electrode. The negative micro-pillar pattern surface demonstrates an average overcut of ∼ 40 ± 15 µm in comparison to the dimensions of the form tool. This research emphasized the sustainability of the EDM process by utilizing reusable dielectric fluid, prioritizing optimal parameters for high-quality fabrication using low electrical-energy utilization, and enabling large-scale production using a form tool.

Study on the mechanism of pressure-induced erosion in molten pool of EDM metal

Abstract This study employs molecular dynamics methods to explore the mechanism of pressure-induced erosion due to the pressure differential within and outside the molten pool during the EDM process. Through simulations of the EDM process for metals such as copper and tungsten, it was found that high melting point materials exhibit slow melting and evaporation rates within the molten pool, resulting in lower internal pressures and reduced efficacy in material erosion, thereby exhibiting high erosion resistance. Experimental validation has demonstrated that the machining efficiency of metals increases with the decrease in their melting points, thus confirming the accuracy of the simulation results. This research not only unveils the micro-dynamic mechanisms of material erosion but also provides a theoretical foundation and experimental support for the advancement of EDM technology.

Multi-criteria decision making for better quality indicators in µ-EDM using TiN-coated WC electrode

ABSTRACT It is highly essential to enhance the micro EDM process while machining titanium specimens. The utilization of coated electrode and adaptation of optimization algorithms in the process can enhance the material removal mechanism. In the present work, an attempt was made to find the influence of TiN coated tungsten carbide electrode in micro EDM process while machining titanium alloy specimens. It was also attempted to adopt DEAR-based optimization in the process. The TiN coating can produce lower TWR with better surface quality than uncoated tungsten carbide electrode. The capacitance has higher influential nature in µ-EDM since it controls the charging and discharging process during the spark formation across discharge gap. It was found that voltage (Level 3), capacitance (Level 3), and the tool rotation (Level 2) can create better quality measures under the prediction error of 2.3%. The optimal combination can enhance the machining accuracy with tiny craters formation.

Investigation of process parameters for modeling of ceramic composite SiSiC IN dry EDM (DEDM) cutting

The manufacturing industry is currently grappling with issues related to energy dissipation and product quality, both of which significantly impact productivity. In addressing this pertinent concern, this study endeavours to identify the key indicators that contribute a crucial role in machining process. The Dry EDM (DEDM) emerges as a novel technology, wherein environmentally friendly gases serve as an alternative dielectric medium instead of liquid EDM approaches. In conventional EDM process, hydrocarbon oils release toxic emissions while the gases used in Dry EDM process don’t produce harmful emissions and hence make the DEDM process sustainable.An investigation has been carried out to observe the influence of different gases like O2, N2 and Air on Siliconized Silicon-Carbide plate (SiSiC) of ø50mm*2 mm under Dry Electrical Discharge Machining. Effect of different tools is also observed using varying shapes of electrodes like plane Cu electrode of ø6 mm diameter with 60 mm length and tubular shape with outer diameter ø6mm and inner diameter ø5.1 mm with a length of 60 mm. The three gases are one by one supplied through a nozzle in the presence of plane Cu electrode to make the holes in SiSiC plate. The same process is executed with tubular Cu electrode. Modified Taguchi Orthogonal Array is applied to analyze the effect of control factors such as gap voltage, discharge current and pulse on-time through a series of experiments. Effect of different shape of tools and different gases is observed for the material removal rate (MRR) and surface roughness (SR) of specimen.In this paper, a latest DEDM process of swirl assisted flushing is proposed which provides a new technique to solve the problems of low MRR and poor surface integrity. Swirl assisted flushing works on Decay Law and also microscopic investigation justifies its validity. It is concluded by this research that current and Pulse on time are more contributing factors about 53.3 % and 27 % respectively. Furthermore, it is noted that DEDM increases MRR 19.5 % and lowers Ra approximately 2/3 than traditional machining. The MRR of O2 is about 3.1 times more than Air and N2 comes at least position while N2 creates better quality of surface due to formation of an inert nitride layer. Empirical relations are established for SR and MRR using Minitab 18 Software to develop a robust model. Confirmation test is performed to check the validity of developed mathematical model. The Novelty of this research is also extended by introducing a new method SAF. The results are finally evaluated by ANOVA.

Electro discharge machining performance of cryogenic heat treated copper electrode

Abstract In this study, the EDM machining performance of a cryogenic heat treated copper electrode was investigated. Within the scope of the study, electrodes selected from copper material were subjected to cryogenic heat treatment with a cycle between [room temperature/ − 184 °C/room temperature]. In the experimental design, the electrode material was changed at two levels: copper electrode (Cu) and cryogenic copper electrode (CCu). Controllable machine parameters, peak current (Ip), active pulse duration (Ton), pulse gap duration (Toff) and gap voltage (Vg) were changed at three levels. The effects of these parameters on outputs such as recast layer thickness (RLT), material removal rate (MRR), electrode wear rate (EWR) and taper angle (TA), which are taken into consideration in determining the processing quality after EDM machining experiments, were taken into account. A total of 18 experiments were carried out on Ti–6Al–4V (Titanium alloy) workpiece with copper electrode. Lower YKTK with combinations of EDM process parameters such as cryogenic copper electrode (CCu), 4 A peak current (Ip), 110 µs active pulse duration (Ton), 72 µs pulse gap time (Toff) and 6 V gap voltage (Vg), It was observed that EWR and TA and higher MRR were obtained.

Prediction and Optimization of Ultrasonic Vibration Assisted Wire EDM Process for AISI P20 + Ni Using COOT Optimization Algorithm Based Deep Neural Network

Prediction and Optimization of Ultrasonic Vibration Assisted Wire EDM Process for AISI P20 + Ni Using COOT Optimization Algorithm Based Deep Neural Network

Study of the effect of spark radius model upon the performance characteristics in EDM process

The evaluation of performance characteristics is of key importance to the EDM process technological reliability. By correctly estimating the power fraction and plasma flushing efficiency, it is possible to improve the accuracy of the surface integrity prediction of the EDM discharge models. In the present research, a combined computational and experimental approach is employed to study the effect of spark radius model upon the performance characteristics in EDM of Ti-6Al-4V alloy. Two famous spark radius relationships have been implemented and the effect on power fraction and removal efficiency was examined for a range of machining conditions. It has been found that the sparking radius relationship accounting for discharge current effect captures the essential dynamics of the EDM process and offers improved prediction accuracy. In such a case, the power fraction going to the cathode ranges from 8.5 to 24 %. When a cooper electrode is utilized, removal efficiency of up to 12 % was observed on the cathode surface. For specific machining conditions, an approximate constant ratio of 2.5 is seen between the power fractions transmitted to the cathode and tool-anode. Crater volume was computed and compared to the experiment to validate the proposed approach. The results of this comparison challenge the EDM model underlying assumption viability, which considers similarity between recast layer and electrode materials thermophysical proprieties when a hydrocarbon-based dielectric fluid is used. From a qualitative perspective, though, the outcomes are still encouraging and indicate that surface integrity in the EDM of Ti-6Al-4V alloy may be predicted using the performance characteristics found in this study.

3D fractal model with experimental analysis for assessing surface topography in EDM

This work presents a novel three-dimensional fractal model designed specifically for morphological analysis of specimens made by the EDM. Within the 3D fractal framework, an algorithm is developed to estimate fractal parameters such as fractal dimension and periodic length. AISI 316 stainless steel, dielectric media, electrode materials, and powder variations were used in experimental trials to validate the 3D fractal model. Fixed pulse time ratios were used to control the EDM process. The specimen having the lowest fractal dimension, the shortest periodic length, the least amount of surface roughness, and the least amount of ten-point height was discovered to be the one machined using kerosene oil dielectric, brass electrode, graphite powder, and 1.0 pulse ratio time. On the other hand, the specimen machined using copper electrode, graphite powder, transformer oil dielectric, and 1.5 pulse ratio time produced the largest periodic length, maximum surface roughness, fractal dimension, and ten-point height. The developed 3D fractal model evaluates the EDM process well and provides insightful information on how to improve surface properties.

PERFORMANCE ENHANCEMENT OF BRASS EDM ELECTRODES WITH CRYOGENIC TREATMENT WHILE MACHINING THE COLD WORK STEEL AISI D2

This study investigates the performance of deep cryogenically treated brass (CuZn25Al5) electrodes in the die-sink EDM process. Two different cryogenic treatment durations, 6 h and 12 h, were applied to 8 mm diameter electrodes, and their effects were compared to untreated electrodes. The machining tests were conducted under moderate and aggressive conditions. In the machining tests, the 6-h cryo-treated electrode exhibited a 16.8% increase in material removal rate (MRR) under moderate conditions and a 19.7% increase under aggressive conditions compared to the reference electrode. The 12-h cryo-treated electrode showed similar MRR values to the reference electrode but improved tool wear resistance by 9.4% under moderate conditions. The kerf angle was minimized, indicating better hole verticality, in the 6-h cryo-treated electrode group. The improvement in machining performance was attributed to the enhancement in electrical conductivity of the electrodes, which increased by 28% for the 6-h cryo-treated electrode and 20% for the 12-h cryo-treated electrode. X-ray diffraction (XRD) analysis revealed shifts in peak positions and possible phase transformations due to cryogenic treatment. Surface roughness measurements showed improved surface conditions in the cryo-treated electrodes under aggressive conditions. The results indicate that cryogenic treatment enhances MRR, reduces tool wear, and improves surface quality in die-sink EDM. These improvements are attributed to increased electrical conductivity and changes in the internal structure of the brass electrode.

Finite element analysis of wire EDM process parameters on performance characteristics of Al–SiC hybrid composite with micro and nano reinforcements

Aluminum Hybrid Composites (AHC) microchannels find extensive applications in aerospace, refrigeration and air conditioning (RAC), microelectronics, automotive, biomedical, and marine industries due to their improved mechanical properties. The combination of lower density, high hardness, elevated thermal and electrical conductivity, superior elasticity, and heightened oxidizing ability at low temperatures makes machining aluminum hybrid composites challenging through orthogonal methods in an open environment. Therefore, it is imperative to investigate the impact of various machining conditions to determine optimal parameter values for microchannel fabrication in aluminum hybrid composite materials. This study aims to identify the ideal machining parameters for Al–SiC micro-SiC nano hybrid composites using wire electrical discharge machining. Four distinct process parameters (pulse on time, gap voltage, wire tension, and wire feed rate) and two response parameters (material removal rate (MRR) and surface roughness (SR)) were considered for process optimization. Additionally, finite element modeling was conducted for the aforementioned process, and the results were compared with experimental outcomes. Single-variable optimization yielded maximum MRR at 125 tons (μs), 25 SV (volt), 12 WT (kgf), and 2 WFR (m/min), and minimum SR at 125 tons (μs), 10 SV (volt), 12 WT (kgf), and 4 WFR (m/min). Single-variable optimization for simulations resulted in maximum MRR at 125 tons (μs), 40 SV (volt), 4 WT (kgf), and 6 WFR (m/min), and minimum SR at 110 tons (μs), 10 SV (volt), 12 WT (kgf), and 2 WFR (m/min). Precise modeling aids in minimizing unnecessary machining, enabling exploration of a broader range of experimental results, thereby promoting environmentally friendly and sustainable machining practices.

Surface roughness prediction of AISI D2 tool steel during powder mixed EDM using supervised machine learning

Surface integrity is one of the key elements used to judge the quality of machined surfaces, and surface roughness is one such quality parameter that determines the pass level of the machined product. In the present study, AISI D2 steel was machined with electric discharge at different process parameters using Jatropha and EDM oil. Titanium dioxide (TiO2) nanopowder was added to the dielectric to improve surface integrity. Experiments were performed using the one variable at a time (OVAT) approach for EDM oil and Jatropha oil as dielectric media. From the experimental results, it was observed that response trends of surface roughness (SR) using Jatropha oil are similar to those of commercially available EDM oil, which proves that Jatropha oil is a technically and operationally feasible dielectric and can be efficiently replaced as dielectric fluid in the EDM process. The lowest value of S.R. (i.e., 4.5 microns) for EDM and Jatropha oil was achieved at current = 9 A, Ton = 30 μs, Toff = 12 μs, and Gap voltage = 50 V. As the values of current and pulse on time increase, the S.R. also increases. Current and pulse-on-time were the most significant parameters affecting S.R. Machine learning methods like linear regression, decision trees, and random forests were used to predict the surface roughness. Random forest modeling is highly accurate, with an R2 value of 0.89 and an MSE of 1.36% among all methods. Random forest models have better predictive capabilities and may be one of the best options for modeling complex EDM processes.

On the identification of the performance characteristics laws in EDM of biomedical Ti-6Al-4 V alloy with different tool electrode materials

The generation of performance characteristics laws may improve the reliability of EDM models, thus limiting experimentation and the resulting ecological effects and waste. In the present research, a finite element (FE) computational approach combined with experiment and regression analysis is employed to identify the laws relating power density and removal efficiency to the process settings in EDM of Ti-6Al-4 V alloy with various tool electrode materials. The experimental results for material removal rate (MRR), tool wear rate (TWR) and white layer thickness (WTL) are used as input data for the identification procedure. It was found that the performance characteristics are strongly affected by the machining parameters and tool-anode material. The power fraction going to the cathode varies between 7 and 30 % depending on the machining conditions and tool electrode materials studied. When employing a graphite electrode as opposed to copper or aluminum electrodes, the removal efficiency is maximized, at 51 %. Thus, the highest and lowest values of performance characteristics are obtained under the same processing conditions, irrespective of the tool material. The performance characteristics laws of the cathode are generated through a regression analysis. The established laws were validated by comparing the erosion ratio from the numerical simulation with the experiment. Qualitatively, the results of such a confrontation are deemed satisfactory. The established laws may be helpful in modeling the EDM process to predict the EDMed Ti-6Al-4 V surface integrity in the biomedical and aerospace sectors.

The Investigation of Material Removal Rate on Electrical Discharge Machining of Titanium Alloys (Ti-6Al-4V) at Different Peak Currents and Pulse Durations by Using RBD Palm Oil and Kerosene as Dielectric Fluids

The type of dielectric fluid is the most significant component that might affect the machining performance of EDM such as material removal, tool wear, and electrode surface roughness. However, the most serious of these issues is the inability to comply with health and environmental rules when the conventional dielectric was harmful to the surrounding ecosystem. One approach to ensure the long-term sustainability of EDM is to use vegetable oil as the dielectric fluid as it is environmentally friendly and biodegradable. To satisfy industrial objectives, the machining industry must ensure that the maximum material removal rate (MRR) can be achieved. This paper investigated the effect of kerosene and refined, bleached, and deodorised (RBD) palm oil as dielectric fluids with different peak currents (6, 9, and 12A) and pulse duration (50, 100 and 150µs) settings on MRR of Titanium alloy. Kerosene was used as a benchmark to compare the performance of the EDM process. The implementation of RBD palm oil recorded the lowest MRR at the lowest peak current of 6A with the lowest pulse duration of 50µs, which is 1.1260mm3/min. In contrast, the highest MRR with a value of 12.1323mm3/min was recorded at the highest peak current of 12A with a pulse duration of 150µs. Overall, RBD palm oil shows an excellent MRR performance for substituting hydrocarbon or mineral oil as a dielectric fluid in EDM applications, improving cost, time, and production efficiency.

Recent Research in Wire Cut Electrical Discharge Machining Process

A product's shape and size are developed through the manufacturing process, which is essential to all sectors. With its unique thermal machining technique, Wire Cut Electrical Discharge Machining (WEDM), items with sharp edges and varied hardness that prove challenging to produce using conventional machining methods can be precisely machined. Utilizing the widely used non-contact material removal technique, the practical technology of the WEDM process is based on the typical EDM sparking phenomenon. When the process was first introduced, WEDM has developed from a crude way to make tools and dies to the best way to produce micro-scale parts with the highest level of surface finish quality and dimensional accuracy. This paper reviews the extensive amount of research done from the EDM process to the development of the WEDM. It reports on the WEDM research that involves optimizing the process parameters and examining the impact of various factors on productivity and machining performance. The impact of multiple WEDM process input parameters, including wire speed, peak current, pulse on and off times, and peak on material removal rate (MRR), surface roughness (Ra), and micro structural analysis, on various process output responses is reviewed in this study.

Study of Correlation of Machining Performance and Geometrical Tolerances of Si3N4-TiN Composites Using EDM Process

Study of Correlation of Machining Performance and Geometrical Tolerances of Si3N4-TiN Composites Using EDM Process