Die-sinking Electrical Discharge Machining Research Articles

Development of a machining strategy to manufacture SiSiC nuts by EDM

Today, the high-precision manufacturing of small cavities in difficult-to-machine materials is still a challenge, even more so if they need to be threaded. The machining time, the wear suffered by the electrodes and the surface finish are determining factors in the efficiency of the threading process. However, there is scant literature on this subject so there is a need to study the process and the parameters involved. Thus, this study presents a novel machining strategy for the manufacture of nuts using die-sinking electrical discharge machining (EDM). Moreover, the novelty of this strategy is that it is carried out in a single stage and with a conventional EDM generator. To do so, a design of experiments (DOE) methodology has been followed. First, the optimal machining conditions are determined by studying the influence of EDM parameters on operation variables and mathematical models are developed using multiple linear regression. These models allow the behavior of the response variables under study to be predicted. Finally, this machining strategy developed from the previous experimental results is validated in the manufacturing process of a final part, specifically a square nut. It can be concluded that the mathematical model is good enough to predict the experimental results. Thus, the new method presented and described in this present study allowed a nut to be obtained with a real arithmetic mean deviation of the roughness profile (Ra) value of 1.27 μm whereas the predicted value from the model was 1.28 μm. To do so, the machining conditions selected were: 4 A (current intensity), 5 µs (pulse time) and 0.4 (duty cycle), which also gave a material removal rate (MRR) value of 0.5370 mm3/min. The machining strategy proposed here may be used for future research works related to the manufacturing of mechanical joints made of conductive ceramic materials.

Performance Evaluation of Electrode Fabricated by using FDM in Die-Sinking EDM

An electrode is a vital transmission tool of electrical charges that erodes a workpiece surface in die-sinking electrical discharge machining (EDM). However, the demanding requirements of the geometrical complexity and accuracy of an electrode significantly affected its manufacturing cost and time. Therefore, rapid tooling (RT) was attempted to improve electrode manufacturing. This research aims to verify the application of the FDM electrode in die-sinking EDM. Furthermore, the metallization and the machining performance of the FDM electrode were also studied. Fused Deposition Modelling (FDM) was utilized to fabricate a cylindrical electrode core made of Polyethylene Terephthalate Glycol (PETG). In primary metallization, the electrode core was immersed in copper paint. Next, the coated PETG substrate was electroplated in secondary metallization at a current density of 0.023 A cm-2 for 168 hours (7 days). The electrolyte consists of 80 g/ℓ copper (II) sulphate pentahydrate and 20 ml/ℓ sulphuric acid. The machining performance of FDM electrode such as material removal rate (MRR), electrode wear rate (EWR) and surface roughness (SR) was benchmarked with a copper electrode. Copper coating with an average thickness of 334 µm was successfully electroplated on the surface of the FDM electrode. Additionally, the FDM electrode was able to machine the mild steel workpiece with 1 mm infit at a peak current of 16 A and pulse-on time of 50 µs without suffering premature electrode failures such as edge failure, delamination, distortion and rupturing. Lastly, the machining performance of the FDM electrode was comparable to the copper electrode in terms of MRR, EWR and SR. The potential of the FDM electrode in EDM machining is proven successful and can be investigated further to enhance the performance of this electrode.

A Thermo-Structural Analysis of Die-Sinking Electrical Discharge Machining (EDM) of a Haynes-25 Super Alloy Using Deep-Learning-Based Methodologies

The most effective and cutting-edge method for achieving a 0.004 mm precision on a typical material is to employ die-sinking electrical discharge machining (EDM). The material removal rate (MRR), tool wear rate (TWR), residual stresses, and crater depth were analyzed in the current study in an effort to increase the productivity and comprehension of the die-sinking EDM process. A parametric design was employed to construct a two-dimensional model, and the accuracy of the findings was verified by comparing them to prior research. Experiments were conducted utilizing the EDM machine, and the outcomes were assessed in relation to numerical simulations of the MRR and TWR. A significant temperature disparity that arises among different sections of the workpiece may result in the formation of residual strains throughout. As a consequence, a structural model was developed in order to examine the impacts of various stress responses. The primary innovations of this paper are its parametric investigation of residual stresses and its use of Haynes 25, a workpiece material that has received limited attention despite its numerous benefits and variety of applications. In order to accurately forecast the output parameters, a deep neural network model, more precisely, a multilayer perceptron (MLP) regressor, was utilized. In order to improve the precision of the outcomes and guarantee stability during convergence, the L-BFGS solver, an adaptive learning rate, and the Rectified Linear Unit (ReLU) activation function were integrated. Extensive parametric studies allowed us to determine the connection between key inputs, including the discharge current, voltage, and spark-on time, and the output parameters, namely, the MRR, TWR, and crater depth.

Multi objective optimization of EDM process parameters for HCHCr steel

Electric discharge machining (EDM) or spark machining involves controlled erosion of electrically conducting materials by an interrupted, repetitive electric spark creating discharge between the cathode- tool and anode- work-piece, separated by a dielectric fluid medium. The objective of this work is to study the influence of machining characteristics during EDM of high carbon and high chromium steel (HCHCr) with copper electrode. EDM of HCHCr steel is conducted according to Taguchi orthogonal array (OA) design of experiment to evaluate the material removal rate (MRR), tool wear rate (TWR) and surface finish (Ra).The experiments are conducted on die-sinking EDM with varying current, voltage, and pulse-on-time to measure the above responses. Finally, the multi objective optimization technique namely principal component analysis (PCA) is used for optimizing the process parameters. The experimental results indicate the optimum parameters as: current 9 Amps, pulse-on time 15 µs and pulse-off time 10 µs.

Investigations, Processing and Analysis of High Temperature Resistant Nickel-Based Alloy with Die-Sinking Electric Discharge Machining Process

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

Investigation of Machining Characteristics in Electrical Discharge Machining Using a Slotted Electrode with Internal Flushing.

In die-sinking electrical discharge machining (EDM), it is challenging to implement internal flushing, mainly because it is easy to produce residual material columns on the workpiece cavity's bottom surface, affecting the processing quality and efficiency. In order to solve this problem, the internal flushing slotted electrode EDM technology was proposed. The slotted electrode was designed, and its preparation method was described. The influence of pulse width, pulse interval, and flushing pressure on the performance of the internal flushing slotted electrode EDM was studied using single-factor experiments. The experimental results indicate that, with the increase in pulse width, the material removal rate (MRR) increases first and then decreases, while the electrode wear rate (EWR) and the relative electrode wear rate (REWR) decrease gradually; with the increase in pulse interval, the MRR decreases, while the EWR and the REWR increase gradually; with the increase in flushing pressure, the MRR increases first and then decreases, while the EWR and the REWR increase gradually. When the slotted electrode is used for continuous internal flushing EDM, the appropriate pulse width, flushing pressure, and smaller pulse interval can improve the MRR and reduce the EWR and the REWR.

Experimentation on HCHCr steel using vegetable oil as dielectric in EDM

With simplicity and accuracy, conductive hard materials may be machined using the non-traditional material removal technique known as electrical discharge machining (EDM). In the present research endeavour, the influence of using vegetable oil (fresh vegetable oil (FVO), Used Vegetable Oil (UVO) and Mixed Vegetable Oil (MVO)) as an eco-friendly dielectric fluid during die sinking EDM of HCHCr steel has been investigated. Effects of several input variables, including current, pulse width, gap voltage, duty cycle, and using copper and copper chromium electrodes have been examined by employing the Taguchi L18 mixed orthogonal array (OA) technique, to assess the response in terms of Material Removal Rate (MRR), Tool Wear Rate (TWR), and Surface Roughness (SR).

Design and Analysis of Acoustic Horn for Assistance in Die-Sinking EDM

Many industrial applications and production technologies are based on the application of ultrasound. In many cases, the phenomenon of ultrasound is also applied in the technological processing of the machining of materials. The main element of equipment that uses the effect of ultrasound for machining is the ultrasonic horn. It is also called a sonotrode. The performance of ultrasonic machining technologies depends on the properly designed sonotrode shape. The dependence of fundamental modal properties (natural frequencies, mode shapes) of various sonotrode shapes for various geometrical parameters is analyzed. Modal analysis of the models is determined by the numerical simulation using the finite element method (FEM) design procedure. In ultrasonic machining, the ultrasonic horn plays a vital part in the high-energy machining process. Electric discharge machining (EDM) is used to achieve high processing quality but the machining efficiency is low. The new (EDM+USM) is used for high machining efficiency. The acoustic analysis of the ultrasonically vibrating tool is done with the assistance of the finite element method (FEM) so that it can be used for EDM applications. Key Words: Modal analysis, Ultrasonic horn, Numerical analysis, efficiency of machining, acoustic analysis.

Experimental investigation to optimize machining parameters for super duplex stainless steel in spark EDM using die-sinking and MQL system

The current experimental work discusses the electric discharge machining (EDM) of super duplex stainless steel with conventional die-sinking and minimum quantity lubrication (MQL) approach. The dielectric used in the conventional die-sinking EDM process is kerosene, and sunflower oil with air mixture is used in MQL-type machining conditions. The solid-type alpha brass electrodes of diameter 10 mm were used for machining. The most prominent input variables like pulse time (OFF and ON) and discharge current (varied at 3 levels) were selected, and Taguchi's L9 orthogonal array design was selected for experimentation. The responses like electrode wear rate (EWR), hole circularity (HC), material removal rate (MRR), and surface roughness (SR) were analyzed. The output results obtained from the experimental trials were analyzed using S/N ratios and analysis of variance (ANOVA). The most contributing input parameter affecting the responses like SR, HC, MRR, and EWR outputs were analyzed. The results showed that the optimum machining conditions were obtained at L3 and L9 levels for conventional die-sinking and MQL-type machining conditions, respectively. Out of three varying input parameters, pulse time (OFF) is the most contributing factor in deciding various responses. The same has been confirmed by ANOVA analysis. The theoretical prediction of experimental data was made using the Fuzzy logic approach, and the best optimal level is found out individually for all four responses.

Investigation of Plasma-Electrolytic Processing on EDMed Austenitic Steels.

This study investigates the effect of electrolytic plasma processing on the degree of defective layer removal from a damaged layer obtained after manufacturing operations. Electrical discharge machining (EDM) is widely accepted in modern industries for product development. However, these products may have undesirable surface defects that may require secondary operations. This work aims to study the die-sinking EDM of steel components followed by the application of plasma electrolytic polishing (PeP) to enhance the surface properties. The results showed that the decrease in the roughness of the EDMed part after PeP was 80.97%. The combined process of EDM and subsequent PeP makes it possible to obtain the desired surface finish and mechanical properties. In the case of finishing EDM processing and turning, followed by PeP processing, the fatigue life is enhanced without failure up to 109 cycles. However, the application of this combined method (EDM + PeP) requires further research to ensure consistent removal of the unwanted defective layer.

Machining of Triangular Holes in D2 Steel by the Use of Non-Conventional Electrodes in Die-Sinking Electric Discharge Machining.

Electric discharge machining is relatively a slow process in terms of machining time and material removal rate. The presence of overcut and the hole taper angle caused by the excessive tool wear are other challenges in the electric discharge machining die-sinking process. The areas of focus to solve these challenges in the performance of electric discharge machines include increasing the rate of material removal, decreasing the rate of tool wear, and reducing the rate of hole taper angle and overcut. Triangular cross-sectional through-holes have been produced in D2 steel through die-sinking electric discharge machining (EDM). Conventionally, the electrode with uniform triangular cross-section throughout the electrode length is used to machine triangular holes. In this study, new designs of electrodes (non-conventional designs) are employed by introducing circular relief angles. For material removal rate (MRR), tool wear rate (TWR), overcut, taper angle, and surface roughness of the machined holes, the machining performance of conventional and unconventional electrode designs is compared. A significant improvement in MRR (32.6% increase) has been achieved by using non-conventional electrode designs. Similarly, the hole quality resulted by non-conventional electrodes is way better than hole quality corresponding to conventional electrode designs, especially in terms of overcut and hole taper angle. A reduction of 20.6% in overcut and a reduction of 72.5% in taper angle can be achieved through newly designed electrodes. Finally, one electrode design has been selected (electrode with 20 degree relief angle) as the most appropriate electrode resulting in better EDM performance in terms of MRR, TWR, overcut, taper angle, and surface roughness of triangular holes.

Surface characteristics optimization of biocompatible Ti6Al4V with RCCD and NSGA II using die sinking EDM

Machining of titanium alloy grade V (Ti6Al4V) is very difficult by conventional metal cutting process due to low thermal conductivity, ability to retain strength at elevated temperature, tendency to work harden. This may result in high heat at the cutting zone and the generation of thermal stresses. Therefore, in the present research die-sinking electrical discharge machining is used to machine Ti6Al4v alloy. A non-dominated sorting genetic algorithm (NSGA II) coupled with rotary central composite design (RCCD) based on response surface methodology (RSM) is employed to optimize machining parameters in die-sinking electrical discharge (EDM) machining of Ti6Al4V. A quadratic mathematical model has been developed for material removal rate (MRR) and surface roughness (Ra) in terms of peak current (I), pulse on time (Ton) and pulse off time (Toff) as independent input parameters. Die-sinking EDM experiments are planned using RCCD based on response surface methodology. Results revealed that peak current is the most influencing EDM parameter on both MRR and Ra with PC of 35.86% and 57.10% respectively. MRR continuously increases with peak current. MRR firstly decreases and then increases with an increase in Ton. Ra continuously increases with peak current and starts decreasing after a coded value of 1.5. The Optimization result obtained by NSGA II is validated through confirmation experiments which are in good agreement with the experimental value with an absolute error of 6% and 4.8% in MRR and Ra respectively.

Current Research Trends in Electrical Discharge Machining : A Review

One of the most widely utilised non-conventional exact material removal procedures is electrical discharge machining (EDM). Hard metals can be moulded using the electrical discharge machining (EDM) method, which uses arc erosion to create deep, intricately formed holes in all types of electroconductive materials. Between the work piece and the electrode, there is a tiny space where erosion pulse discharge takes place. By melting and vaporising the undesired material, this separates the parent metal from the unwanted stuff. The objectives of this new study are the same: to reduce tool wear and achieve enhanced surface quality while reducing metal removal rate. This study discusses the scientific work done from the beginning to the invention of die-sinking EDM, Water in EDM, and dry Electric discharge machining and powder-mixed EDM are also used. in the last ten years. Additionally, a brief description of the EDM research plan going forward is included.

A state-of-the-art review on electric discharge machining of shape memory alloys

Electrical Discharge Machining is among the early non-traditional machining methods. The heart of the EDM process is the thermoelectric energy that exists between the work piece and an electrode. By melting and vaporizing the undesired material in a narrow gap between the work piece and the electrode, a pulse discharge may remove it from the parent metal. In order for the work piece and the electrode to ignite the flame, electrical conductivity is necessary. EDM may be used to develop a range of objects, such as dies and moulds, aeronautical components, and automotive parts. EDM may be used to finish both medical and industrial items. Research trends in EDM are explored in this study, including those in dry EDM machining, ultrasonic vibration, EDM in water, and EDM with powder additives. This paper's purpose is to evaluate the extensive research that has been done to process these shape memory alloys (SMAs) utilizing the concepts of electrical discharge machining (EDM) and related methods. A careful examination and publishing of the numerous studies undertaken in the disciplines of wire EDM, die-sinking EDM, and other EDM variations on different kinds of SMAs. The various theoretical, experimental, modelling, and optimization-based studies that have been done into SMA EDM are also discussed. It was also suggested that choosing the suitable process parameters, tool electrodes, and dielectrics may considerably boost the process overall efficacy.

Evaluation of material removal rate for different cavity geometries produced by die-sinking electrical discharge machining

The focus of this paper is to investigate the material removal rate for polygonal micro cavities of polygonal shapes of triangle, square, pentagon and hexagon. In order to start the investigation, polygonal micro cavities were machined in advanced die-sinking Electrical Discharge Machining coupled with e-pulse technology and CNC controlled multi-axes movement in a series of three over steel through 400 µm tungsten carbide electrode in die-sinking Electrical Discharge Machining (EDM). In order to evaluate the performance of machining with reference to material removal rate (MRR), well defined mathematical procedures were followed. It was reported that the average MRR of triangle shaped micro cavities is 19.17 × 104 µm3/s which is the least than that for square, pentagon and hexagon shaped cavities whose calculated values of MRR are 31.5 × 104, 28.5 × 104 and 29.2 × 104 µm3/s respectively. Based on the calculated values, it is reported that the maximum rmaterial removal rate is obtained in case of square shaped cavities as compared to others. The reason behind this is that the occurrence of secondary (side) discharge is lesser in case of square shaped cavities and also the travel of tool is limited.

Optimization-Based Hybrid Intelligent Model for Decision Making on Electrical Discharge Machining (EDM) Process of A6061/6%B4C and A6061/9%SiC Composite Materials

This study intends to suggest an improved deep learning decision-making model on the die-sinking electrical discharge machining (EDM) process of A6061/6%B4C and A6061/9% silicon carbide (SiC) composite materials. The proposed model consists of feature extraction and prediction stages. An extraction of statistics and much more advanced statistical characteristics is the first phase in the feature extraction process. The hybrid classifier that mixes convolutional neural network (CNN) and neural network (NN) is then fed the features. The final projected outcome is attained by averaging the results from both CNN and NN. An upgraded Sea Lion with Customized Levy Flight (SL-CLF) is suggested as a significant improvement to the classifier prediction accuracy. Finally, a number of indicators are employed to demonstrate the superiority of the SL-CLF strategy. At last, several metrics are used to show the superiority of SL-CLF approach. The mean standard error (MSE) of the proposed work for dataset 1 is 4. 965, which is 9. 7%, 38%, 59. 89%, and 59. 89% better than CNN, NN, Taguchi Coupled grey relational analysis (GRA), and ANN.

Comparative Analysis and Optimization of Thermoelectric Machining of Alumina and Silicon Carbide-Reinforced Aluminum Metal Matrix Composites Using Different Electrodes

In this paper, a comparative experimental analysis of die-sinking electric discharge machining (EDM) to two most exhaustively used aluminum metal matrix composites (AMMCs) has been performed using Copper and Tungsten as tool electrodes. AMMCs containing silicon carbide (SiC) and alumina (Al2O[Formula: see text] as reinforcement (10[Formula: see text]wt%) were fabricated by stir casting method. The Box–Behnken Design (BBD) approach of response surface methodology was used to develop experimental models for material removal rate (MRR) and surface roughness (SR). Effect of input parameters such as current ([Formula: see text]–12[Formula: see text]A), gap voltage ([Formula: see text][Formula: see text]V), pulse-on time ([Formula: see text]s), and duty factor ([Formula: see text]–6) on the output responses has been investigated with response surface plots. Effectiveness of design of experiment (DoE) and evolutionary algorithm-based multi-objective optimization (MOO) technique have been compared to find the best feasible optimal solution. ANOVA analysis reveals that for alumina reinforced AMMC interaction between [Formula: see text] has significant effect on both MRR and SR using Cu electrode. But for tungsten, electrode interaction between [Formula: see text], [Formula: see text], and [Formula: see text] have major role on MRR whereas SR is mostly influenced by interaction between [Formula: see text] and [Formula: see text]. The parametric analysis reveals that an increase of current from 4[Formula: see text]A to 12[Formula: see text]A at a higher pulse-ontime increases the MRR more significantly, and higher MRR occurs in cases of alumina-reinforced AMMC. Increase of pulse-ontime at low current (4[Formula: see text]A) reduces the MRR in AMMC/Al2O3. Good surface finish can be obtained by combining high voltage (60[Formula: see text]V) with either small current (4[Formula: see text]A) or small duty factor (4) for both AMMCs. Both DoE and metaheuristic-based MOO technique reveals that copper electrode should be preferred for die-sinking EDM of AMMC/SiC. Metaheuristic approach should be preferred for optimization of die-sinking EDM of AMMCs using different electrodes because it requires low current for effective machining of different AMMCs.

Bi-objective Optimization of Process Parameters in Electric Discharge Machining of SS630 Using Grey Relation Analysis

One of the most former and widely utilized unconventional machining is known as the process of electric discharge machining (EDM). This is a procedure, where a serialized set of electric discharges are applied to eliminate the material from a workpiece (i.e., electrically conductive). This article proposes a bi-objective optimization of process arguments in machining of stainless steel of 630 (SS630) grade using both experimentation and thermal investigation. Here, flushing pressure ( P F ), pulse on-time ( T ON ), peak current ( I p ), and pulse off-time ( T OFF ) are assumed as the input process parameters to conduct a series of experiments on die-sinking EDM (DS-EDM) of SS630 to predict the output characteristics of machining optimization using grey relation analysis (GRA). Both material removal rate (MRR) and surface roughness (SR) are used for evaluating the output response obtained using the machining performance. In addition, thermal investigation is performed using finite element method (FEM) analysis to compute theoretical MRR (T-MRR) for the distribution of temperature on workpiece. Further, GRA is employed to obtain the optimal process parameter combination for best output responses. From the confirmation test results, the optimal combination obtained using GRA approach is at I p = 6 A , T ON = 35 μ s , T OFF = 90 μ s , and P F = 4 MPa .

Optimization of Electric Discharge Machining of Al/Al2O3 Metal Matrix Composites using MOPSO

In this article, Response Surface Methodology (RSM) and Multi-objective Particle Swarm Optimization (MOPSO) were used to optimize the output response of Material Removal Rate (MRR) and Surface Roughness(SR) of die-sinking Electrical discharge machining (EDM). An aluminum based metal matrix composites, reinforced with alumina, prepared by stir casting, was used for machining on EDM by Copper (Cu) and Titanium (Ti) tool. Box- Behnken Design (BBD) approach of RSM was used to design the experiment by considering four input factors at three levels. This developed model for multi-objective optimization by MOPSO and an RSM-based multi-objective optimization was also designed for input parameters. And it was found that the MOPSO technique was easy and valuable for parametric optimization of EDM. From MOPSO, optimized input parameters for machining of AMMC using Cu tool are current 4A, Voltage 60V, pulse on-time 100 µs, and duty factor 6. From MOPSO, optimized input parameters for machining of AMMC using Ti tool are current 4.241658A, Voltage 60V, pulse on-time 100 µs, and duty factor 4. The confirmatory test found that MRR and SR decreased by 63.86 % and 53.083% for the Cu tool, respectively, for MOPSO compared to RSM optimize value.

Electrical discharge micro-texturing using compound tool electrodes for tribological and wettability applications

ABSTRACT The present work consists of large-area surface texturing through die-sinking electrical discharge machining (EDM) using compound tool electrodes. The compound tools were machined through the wire electrical discharge machining (WEDM). The micro-textured surfaces incorporating array of nearly square/circular-shaped micro-dimples, rectangular micro-channels and square micro-pillars were analysed for their wetting properties. An increase in water contact angle (CA) indicated higher water repellence for textured surfaces with respect to the untextured ones. Further, improved frictional behaviour was elicited through tribological analysis via the ball-on-disc test, revealing a lower average coefficient of friction (CoF) compared to the untextured surface. The wear volume of textured surfaces (micro-channels and micro-pillars) exhibited a slightly higher value with respect to the untextured surface, which can be ascribed to the stress concentration from microfeatures. However, the micro-dimpled textured surface showed a relatively lower wear volume, presenting a suitable micro-texture for improved tribological characteristics.