Die-sinking Electrical Discharge Machining Process Research Articles

Effect of manufacturing new U-shaped electrode on die sinking EDM process performance

Traditional electrical discharge machining (EDM) electrodes have several limitations such as long machining time, low material removal rate MRR, hazard emissions and high energy consumption. To overcome these limitations, new electrodes (plane and frame U-shaped) were manufactured considering the electrode manufacturing classifications, such as electrode flushing mechanism, electrode cross-sectional area and electrode bottom machining area. Experiments were performed on a die-sinking EDM machine using copper electrodes and aluminum alloy workpieces. The results were compared with those obtained using the conventional electrode. The newly manufactured electrodes significantly improved the EDM process performance, reducing the machining time by more than 50%, which implies a higher MRR. The reduced machining time also led to lower costs, emissions and energy consumption for efficient EDM processes. Additionally, surface roughness measurements were performed to compare the surface quality of the machined areas using different pulse-code generator systems and electrodes. The results showed an improvement in the machined surface quality when using the new electrodes in comparison with the conventional electrode when using a roughing pulse code generator system.

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.

Reviewing Performance Measures of the Die-Sinking Electrical Discharge Machining Process: Challenges and Future Scopes.

The most well-known and widely used non-traditional manufacturing method is electrical discharge machining (EDM). It is well-known for its ability to cut rigid materials and high-temperature alloys that are difficult to machine with traditional methods. The significant challenges encountered in EDM are high tool wear rate, low material removal rate, and high surface roughness caused by the continuous electric spark generated between the tool and the workpiece. Researchers have reported using a variety of approaches to overcome this challenge, such as combining the die-sinking EDM process with cryogenic treatment, cryogenic cooling, powder-mixed processing, ultrasonic assistance, and other methods. This paper examines the results of these association techniques on various performance measures, such as material removal rate (MRR), tool wear rate (TWR), surface roughness, surface integrity, and recast layer formed during machining, and identifies potential gap areas and proposes a solution. The manuscript is useful for improving performance and introducing new resolutions to the field of EDM machining.

A contribution to numerical prediction of surface damage and residual stresses on die-sinking EDM of Ti6Al4V

A numerical simulation under plane-strain assumption of residual stresses and damage on titanium alloy Ti6Al4V in die-sinking electrical discharge machining (EDM) process is presented using Johnson–Cook (J–C) model and dynamic explicit temperature-displacement algorithm. A special attention is given to model the damaged thermo-mechanical behavior of EDMed Ti6Al4V alloy while considering the ductile damage evolution via a fully uncoupled damage formulation. A rigorous selection method including analytical and finite-element (FE) computations of tensile fracture behavior with thermal effect is proposed for suitable selection of J–C model parameters for the grade of Ti6Al4V alloy under investigation. The relationships between the machining parameters and both the heat flux density and the available sparking radius are considered for defining sparking analysis input. For a selected set of machining settings, the residual stresses and surface damage profiles were retrieved at the end of a cooling analysis. It has been concluded that J–C constitutive model can be used to describe material damaged thermo-plastic behavior under die-sinking EDM process conditions and thereby forecast temperature distribution, crater cavity shape, thermally induced residual stresses, white layer thickness and EDM thermal cracks formation. Unusually, an approach including damage criterion was proposed for assessment of both the geometry of crater cavity and the thickness of white layer and compared to based-on temperature criterion classical approach. Thus, numerical simulation of damage in die-sinking EDM offers a new insight into the mechanism of surface damage creation and helps to find out such phenomenon very precociously, which is otherwise difficult to access by experiment, such as surface crack formation due to damage mechanism as triggered in sparking phase and which was re-established in cooling. The numerical model yields reliable results for residual stresses profiles when compared with titanium alloy Ti6Al4V experimental results available in literature in the same machining conditions.

EDM of high aspect ratio micro-holes on Ti-6Al-4V alloy by synchronizing energy interactions

ABSTRACT Electrical discharge machining (EDM) of high aspect ratio (AR) micro-holes on materials like Ti-6Al-4 V alloy is challenging. The ineffective removal of the machining by-products from and replenishment of fresh dielectric medium in the inter-electrode gap (IEG) limit the penetration depth. The approaches suggested in existing literature either complicate the EDM process or increase the operational costs. Moreover, the effectiveness of energy interactions in the IEG affecting the process performance has not been adequately investigated. This research attempts to synchronize effects of energy interactions between the tool electrode, dielectric, and work material in the IEG by controlling the input discharge energy through current and pulse-on-duration, and dissipated energy through pulse-off-duration and lift settings. Experimental indicators like tool penetration rate, machining time, debris morphology, gas-bubble dynamics, and discharge waveforms are employed to expound the non-linear dynamic behavior of the process. Accordingly, the machining of high AR micro-holes is defined into four zones: usual micro-EDM, transition, high-AR EDM, and critical zones. The maximum depth (10 mm) and AR (17.4) ever reported during the micro-EDM of Ti-6Al-4 V alloy was achieved without employing any additional assistance. Thereby, the capabilities of the conventional die-sinking EDM process are improved for machining high AR micro-holes on Ti-6Al-4 V alloy.

Design and Investigate of Flushing System for Electrical Discharge Machining (EDM) Application

Electrical Discharge Machining (EDM) is high precision machining process in which no actual contact between the workpiece and electrode during sparking. Dielectric fluid play a role as flushing medium and semiconductor between workpiece and electrode to stabilization and controlled spark gap ionization condition. In real condition, nozzle flushing system in EDM machine not able to complete remove debris formed during machining and affect the machining performance. Improper flushing due to lack of guideline at setup position of nozzle and inlet pressure caused low material removal rate, irregular tool and higher cost on raw material. To overcome this problem, the design and investigate of flushing system in EDM application is required. The design and investigation undergo by simulation of ANSYS Computational Fluid Dynamics (CFD) with a virtual experiment to accurate prediction of flushing performance. The influence of nozzle size and inlet pressure supplied on flushing efficiency were analyzed to avoid improper flushing on die-sinking EDM process. The simulation and experiments clarified that the higher inlet pressure, P=0.20 bar and larger nozzle diameter, D=6mm resulting in higher total pressure which is 2647.16 Pa. Furthermore, the streamline of velocity and eddy viscosity contour in the work tank using to analyze the turbulence zone by nozzle flushing obtained by the CFD analysis. The condition in case 5 (D=5mm, P=0.15 bar) is more efficiency on debris removal rate based on the result of high total pressure on machining zone and eddy viscosity contour showed the turbulence zone only formed area near to outlet of system. The model results have been shown good agreement with experiment and co-relation data.

Die-sinking of super dielectric based electrical discharge machining using 3D printed electrodes

Electrical discharge machining (EDM) is a popular nonconventional manufacturing process for the machining of complex or hard materials that are difficult to machine by the conventional machining process. In the EDM process, the electric current is used to ablate the material, and there is no contact between the tool and workpiece. One of the variants of the EDM process is the die sinking EDM where the electrode shape is mirrored in the workpiece, and die sinking electrodes are usually manufactured using conventional machining process. However, in the die sinking EDM process, the material removal rate is significantly lower than the conventional machining. Due to this fact, the regular die sinking EDM process is unable to meet the demands of today’s fast moving manufacturing industry. This study presents an innovative electrode design strategy together with a super dielectric machining fluid to tackle the low-efficiency issue of the die sinking EDM process. In general, flushing becomes very important when deep features are machined. In the die sinking EDM process flushing holes in the tool electrode is considered impractical, and the regular method of flushing is not effective because of the accumulation of a large amount of debris in the machining zone. In this study, 3D printed die sinking EDM electrode with multiple through electrode flushing channel for high-pressure flushing is introduced. In addition, an innovative super dielectric based EDM fluid is proposed in this study, which provides high capacitive plasma in the machining process and ensures better machining efficiency. The effect of super dielectric fluid on the EDM plasma has been analysed and compared with the plasma physics theory. The performance of the proposed 3D printed multi flushing channel electrode together with super dielectric fluid for the feature manufacturing has been demonstrated by making multiple features efficiently in hard to cut materials.

Limits of Die-Sinking EDM for micro Structuring in W300 Steel with pure Copper Electrodes

Electrical discharge machining (EDM) is capable of almost force-free 2D and 3D machining of any kind of conductive material. The micro die-sinking EDM process described in this paper uses electrodes with features in the micrometer scale as a working tool. The ability to machine micro features is desirable for many applications, which range from miniaturization to functionalization of large surfaces. To achieve the desired workpiecès final shape, the working gap and the tool wear behavior must be known and minimized or compensated if possible. For an overall understanding, the interaction between process parameters, such as pulse and pause duration, as well as discharge current with resulting gap sizes, wear formation and work piece shape must be displayed. Besides the optimization of the micro-EDM process itself, the entire process chain must be discussed, including the shaping of the electrodes. This paper provides knowledge on micro structuring copper electrodes using wire-EDM. It also includes information about their subsequent use in micro die-sinking EDM when machining large areas with high aspect ratio micro structures in W300 steel of Böhler Edelstahl. On electrodes, micro ribs with heights of 350 µm, widths of 70 µm and pitch distances of 320 µm could be reached. For micro die-sinking, a relative frontal length wear as low as 19% was determined. The limits of minimum structure sizes in W300 have been investigated, and rib widths down to 31 µm, as well as pillar edge lengths down to 80 µm, have been achieved. Surface quality and changes of the chemical surface compounds of W300 were analyzed using scanning electron microscope (SEM) and energy dispersive X-ray spectroscopy (EDX). Deposit of copper material from the electrode was identified and a proliferation of carbon was detected on the workpiece.

A Block Divided EDM Process for Diffuser Shaped Film Cooling Holes

Diffuser shaped film cooling holes are more and more used on the hot side blade of advanced aeroengines or gas turbines. The machining of diffuser holes is a key problem for its complicated shapes and Ni base superalloy. Currently die-sinking electrical discharge machining (EDM) is still considered to be an available process for the machining of diffuser holes. However, the tool electrode shape changes after each process due to electrode wear in EDM, therefore traditional die-sinking EDM process can not meet the requirements of shape precision and machining efficiency for film cooling holes. In this study, a novel EDM process named block divided EDM is proposed. In this process, the space of the complex shape of the hole is divided into several blocks. A slender rod electrode with simple cross-section is employed to form the blocks, each of which can be processed by feeding once. When the tip shape of the electrode changes due to electrode wear, it can be repaired efficiently because of the simple electrode shape. In order to analyze the machining error caused by electrode wear under different machining parameters, a geometry simulation model of the block division EDM process is established. In this simulation model, the shapes of electrode and workpiece are represented by three-dimensional matrix. The electrode motion, the spark gap, and the electrode wear ratio are taken into account. Finally, confirmatory experiments are carried out. It is shown that laidback fan-shaped holes, one type of diffuser shaped film cooling holes can be efficiently formed by the proposed process.

Adaptive neuro fuzzy inference system modelling of multi-objective optimisation of electrical discharge machining process using single-wall carbon nanotubes

Electrical discharge machining (EDM) has new avenues for finishing of hard and brittle materials with nano surface finish, high tolerance and accuracy. The single-wall carbon nanotube (SWCNT) is mixed with kerosene dielectric fluid in die sinking EDM process. The analysis of surface characteristics like surface roughness and metal removal rate of AISID2 tool steel materials were carried out and an excellent machined nano finish can be obtained by setting the machining parameters at optimum level. This study deals with modelling of surface roughness with SWCNT-based EDM using adaptive neuro fuzzy inference system approach. The first-order Sugeno-type fuzzy interference modelling has been used to predict the output parameters and compared with experimental values. The R2 value of regression model for with CNT is 0.706 and for without CNT is 0.652. The high R2 indicate that better model fit the data very well using CNT-based machining. The proposed model can also be used for estimating surface roughness and metal removal rate online.

Modeling and Analysis of Micro-hole in Die-sinking EDM Process through Response Surface Method based on the Central Composite Design

Electrical discharge machining (EDM) is common used process in aviation industries for machining micro-hole on the blade in aeroenging.Ti-6Al-4V is widely applied in frontier for its excellent properties such as a high strength-weight ratio, great heat stability and exceptional corrosion resistance. The micro-hole plays an important role in the micro-parts. In the present study, the mathematics models have been developed for relating the responses as the tool wear ratio and white layer thickness to input parameters like pules-on time, pule-off time and discharge current in a die-sinking EDM process. The response surface methodology has been applied for developing the models using the technique of design of experiment (DOE). The experiment plan adopts the centered central composite design (CCD). The experimental and predicted values were in a good agreement.

Improvement of dry EDM process characteristics using artificial soft computing methodologies

Dry electrical discharge machining (EDM) is an environmentally-friendly alternative of die-sinking EDM process, which it uses gaseous medium instead of liquid as a dielectric. Due to contribution of too many parameters in this process, selection of optimal parameters to increase the process performances is a really crucial concern. In this work, a predictive model based on back-propagation neural network has been applied to correlate the inputs and outputs of dry EDM process. Herein, the inputs were gap voltage, pulse current, pulse on time, duty factor, air intake pressure and rotational speed of tool, and also the main outputs were material removal rate (MRR) and surface roughness (SR). Firstly a back-propagation (BP) and radial basis function neural network have been developed based on data generated from literature [Saha and Choudhary Int J Mach Tools Manuf 49:297–308 (2009)]. Then, the accuracy of proposed models has been checked by their values of error percent via testing data. Hereafter, the most accurate model was served as an objective function to optimize the process using artificial bee colony (ABC) algorithm. In optimization stage, firstly a single objective optimization was fulfilled to determine the optimal factors related to each output separately. Then a multi-objective optimization was implemented to calculate the best solutions in the case of higher MRR and lower SR simultaneously. Results indicated that the predictive model can estimate the dry EDM process precisely, and also the ABC algorithm could find the optimal solution sets logically.

Mathematical modeling of aerosol emission from die sinking electrical discharge machining process

Emission of toxic gases and aerosol is an important hazard associated with the electrical discharge machining (EDM) process, one of the most widely used non-conventional manufacturing processes. These emissions can cause adverse health effects to the operators and has a direct impact on the environment. The emission from this process is directly related to the temperature at the process location. This paper was aimed at developing a model that quantifies the aerosol generated from the die sinking EDM process while machining steel workpiece with copper electrode. The model developed in this paper made use of energy balance and heat transfer equations. The modeling results were then validated using experimentally obtained values of the emission rate of aerosol from this process. The results showed a close correlation of +0.89 with experimental results. The model developed in this paper can predict the level of emissions at different process locations; thereby reducing the direct cost and time associated with experimentation.