Electro Discharge Machining Process Research Articles

Predictive modeling of MRR, TWR, and SR in spark-EDM of Al-4.5Cu–SiC using ANN and GEP

In this study, Al-4.5Cu alloy was reinforced with varying weight percentages of SiC particles (2%, 4%, 6%, and 8%) to create metal matrix composites via the stir casting method. The formation of intermetallic compounds was confirmed through energy dispersive spectroscopy and x-ray diffraction analysis. This article compares the performance of Artificial Neural Network (ANN) and Gene Expression Programming (GEP) models in predicting the Metal Removal Rate (MRR), tool wear rate, and surface roughness in the die-sinking electro-discharge machining (EDM) process of the ex-situ developed Al-4.5%Cu–SiC composites. The study considers three machine parameters—pulse on time (TON), pulse off time (TOFF), and current (I)—along with the weight fraction of SiC particles as input variables for the models. Both ANN and GEP models demonstrated high predictive accuracy for the EDM performance metrics, with correlation coefficients (R) ranging from 0.973 68 to 0.980 65 for the ANN model and 0.980 11 to 0.982 59 for the GEP model. Notably, the GEP model exhibited superior predictive capability, as evidenced by its higher correlation coefficients and lower root mean square error, indicating greater effectiveness in predicting the EDM process outcomes than the ANN model.

Parametric Investigation of Die-Sinking EDM of Ti6Al4V Using the Hybrid Taguchi-RAMS-RATMI Method

Ti6Al4V is a widely used alloy due to its excellent mechanical qualities and resistance to corrosion, which make it fit for automotive, aerospace, defense, and biomedical sectors. Due to its high strength and limited heat conductivity, it is difficult to machine. Both the workpiece’s and the electrode’s conductivity are important factors that impact the electro-discharge machining (EDM) process. In this case, the machining efficiency is also influenced by the electrode selection. As a result, choosing the right electrode and machining parameters is essential to improving EDM performance on the Ti6Al4V alloy. Research on EDM for Ti6Al4V is limited, with little focus on electrode material selection and shape. The impact of EDM settings on MRR, TWR, and surface roughness is complex, and a comprehensive optimization strategy is needed. Copper electrodes are widely used, but further investigation is needed on EDM’s effects on Ti6Al4V’s surface properties and surface integrity. Addressing these research gaps will improve the understanding and application of EDM for Ti6Al4V, focusing on parameter optimization, surface integrity, and thermal and mechanical effects. By employing copper tools to optimize four crucial EDM process parameters—peak current, duty cycle, discharge current, and pulse-on time—this research aims to increase surface integrity and machining performance. A comprehensive Taguchi experimental design is used to systematically alter the EDM settings. By optimizing parameters using tolerance intervals and response modelling, the recently developed RAMS-RATMI approach improves the dependability of the EDM process and increases machining efficiency. With the optimized EDM settings, there were notable gains in depth of cut enhancement, surface roughness minimization, tool wear rate (TWR) reduction, and material removal rate (MRR). The results of the surface integrity examination showed fewer heat-affected zones, fewer microcracks, and a thinner recast layer. Analysis of variance was used to verify the impact and resilience of the optimized parameters. Superior machining performance, higher surface quality, and increased operational dependability were attained with the Ti6Al4V-optimized EDM process, providing industry practitioners with insightful information and useful recommendations.

Understanding the machined material’s behaviour in electro-discharge machining (EDM) using a multi-phase smoothed particle hydrodynamics (SPH) modelling

Electro-discharge machining (EDM) has been extensively employed for machining hard alloys, and its simulations have been widely conducted using finite element analysis (FEA). However, the majority of mesh-based models depended on forecasting the crater profile only based on the temperature gradient, without offering detailed data regarding the machined material properties. It is crucial to understand the behaviour of the machined material in order to accurately assess the flushing efficiency, analyse the wear on the electrode, and examine the interaction between the debris generated during machining and the remaining workpiece. This is done to ensure that no recast material is left behind after the EDM process. For the first time, a meshless smoothed particle hydrodynamics multi-phase model was implemented to gain practical insights and comprehensively understand a very intricate phenomenon that occurs within a very short time. Additionally, this approach is utilised to investigate the characteristics of the materials being machined. We utilised our SPH model to simulate both the capacitance- and transistor-based EDM of Ti–6Al–4V and AISI304 steel. Our simulation considered the temperature-dependent thermal properties and latent heats of the materials. The accuracy of our model was confirmed by comparing its results with experimental, analytical, and finite element analysis (FEA) results. The machined material was observed during its removal from the surface, and the dimensions of the resulting crater, as well as its aspect ratio and the rate at which the material was removed, were predicted with an error ranging from 2 to 22%. This error is far lower than that of the typical finite element (FE) prediction. This model lays the groundwork for a more complex model that will more accurately represent EDM and other similar manufacturing processes.

Minimization of residual stress, surface roughness and tool wear in Electro Discharge Machining of inconel 625

Electro Discharge Machining (EDM) is a well-known non-traditional machining technique which is widely used to make die castings and turbine blades out of difficult-to-cut materials like Inconel 625. The machined part's surface quality and dimensional accuracy are affected by the EDM electrode's wear. Moreover, surface roughness and residual stress augmentation of EDM-machined components can reduce the workpiece's lifespan by decreasing the fatigue life of machined parts. To enhance the precision and durability of EDM machined components, residual stress, tool wear, and surface roughness should be evaluated and minimized. The majority of published research works for the assessment and optimization of EDM machining parameters are based on experimental works which are limited to testing, workpiece materials, and machining conditions. In order to improve the quality of machined surfaces and reduce tool wear and residual stress during Inconel 625 EDM processes, a virtual machining approach has been developed in the research work. To predict the cutting temperature during EDM operations, the modified Johnson Cook model of Inconel alloys is used. The finite element approach is then used to calculate the generated residual stress during the EDM process. The proposed virtual machining approach is also applied in order to predict the surface roughness of EDM machined parts. To minimize the residual stress, tool wear, and surface roughness during EDM operations of Inconel 625, the machining parameters of gap voltage, peak current, pulse-off time, and pulse-on time are optimized using the Taguchi optimization approach. Experiments and simulations are then conducted to verify the developed virtual machining system in the study. So, using the optimal machining parameters, the residual stress, surface roughness of machined items and wear of EDM electrode are minimized by 24.5 %, 25.4 %, and 25.4 % respectively. Thus, the quality and reliability of components made using EDM processes may be enhanced by the suggested virtual machining system.

Mathematical Analysis for Optimizing Electro Discharge Machining Parameters and Enhancing Hastelloy Machining Efficiency

This study investigates the process parameter optimisation for Hastelloy electro discharge machining (EDM). The goal of the research is to increase machining accuracy and efficiency by precisely changing the EDM process factors. The most important variables affecting tool wear, surface quality, and material removal rate are identified. In order to improve the machining performance for Hastelloy components, the research highlights the importance of factors including discharge current, pulse duration, electrode material, and dielectric fluid properties. The study's conclusions give important information about how to improve EDM procedures for this tough, corrosion-resistant hastealloy. Extensive research is conducted into the features of tool wear and their connection to process parameters in an effort to increase tool life and reduce manufacturing costs. The findings of this research offer useful data for optimising the efficiency of the Hastelloy EDM process in terms of both money and time. The growing need for high-performance components in industries including aerospace, chemical, and nuclear engineering is being addressed by this study, which intends to lay the groundwork for the development of efficient and environmentally friendly machining practises for Hastelloy. To do this, one must get a thorough comprehension of the interrelationships between the various process parameters.

Prediction of machining performances in powder mixed electro-discharge machining to process skd61 steel by response surface methodology

In electro-discharge machining (EDM) with mixing powder, it is called powder mixed electro-discharge machining (PMEDM), then machining performances- i.e. material removal rate(MRR) and tool wear rate (TWR) has great significance in evaluating the effectiveness and machining accuracy of the machining method. Therefore, in this study, response surface methodology (RSM) was utilized for estimating functions of process variables {comprising peak current (Ip), pulse on time (Ton), and powder concentration (Cp)} for the machining performances for processing SKD61 steel during EDM process with tungsten compound powder. Box-Behnken matrix was utilized for designing and conducting a series of empirical trials. Analysis of variance (ANOVA) was applied to evaluate the adequate of predictive models. The outcomes reveal that the predicted models of MRR and TWR have a high precision with R2 values of MRR and TWR being 99.2% and 99.11%, respectively. The error comparison of the predictive and empirical values for the confirmed experiments is less than 5%, this once again consolidates that the developed models' accuracy. These development models can efficiently prognosticate the desired machining performances of the PMEDM method for processing SKD61 steel

Enhancing surface integrity and performance of EDM with sustainable dielectrics and electrode modifications

A common non-traditional method for precise machining of hard materials is electro-discharge machining (EDM). The efficiency and surface quality in the EDM process are decided by the design and type of the electrodes. Because of its lightweight, cost-effectiveness and easy machinability, aluminium is employed in a wide range of applications. In this work, AlSi10Mg electrodes are manufactured by different processing routes such as 3D printing, casting, and extrusion. Different characterization techniques are carried out to determine the mechanical, electrical, and thermal properties of all differently processed aluminium alloy electrodes. The processing route influence during the EDM of Ti-6Al-4V is evaluated with different levels of operating parameters using conventional EDM oil and lemon peel biodiesel as dielectrics. The experiments are performed with 3 different levels of current (Ip) and pulse on time (Ton) with a constant voltage. The output responses viz. material removal rate (MRR), Tool wear rate (TWR), average surface roughness (Ra) and white layer thickness (WLT) are considered to compare the EDM performance exhibited by differently processed aluminium alloy electrodes. The 3D printed aluminium alloy electrode produces about 23% less TWR and 18% improved surface quality than the conventional (extruded) electrode. The performance exhibited by the cast aluminium alloy electrode is sub-optimal when compared to electrodes processed by the other two routes. The microscopic examination revealed that WLT could be reduced to the extent of about 29% and 39% with 3D printed AlSi10Mg electrodes when compared with extruded and cast electrodes. The present study concluded that a 3D printed electrode with lemon peel dielectric is the most preferable combination for high surface finish operation.

Parametric optimizing of electro-discharge machining for LM25Al/VC composite material machining using deterministic and stochastic methods

AbstractThe electro-discharge machining (EDM) process is investigated using deterministic and stochastic methods to determine and model the effects of process parameters on machining performance. The workpiece utilized for the investigation was an LM25 aluminum alloy reinforced with vanadium carbide (VC), processed through a stir casting technique. EDM process parameters like peak current, discharge voltage, and pulse on-time are considered to analyze material removal rate, electrode wearing rate, and surface roughness. This study applied four multi-criteria decision-making (MCDM) and analytical methodologies to evaluate EDM performance. Then, the MCDM scores were compared using two objective verification mechanisms. In this case, the teaching-learning-based optimization (TLBO) technique delivered the best-desired results relative to the VIKOR, Grey relational grade (GRG), and the response surface method (RSM). Also, the RSM and analytical methods are simpler than the other methods, though they produced nearly identical results as the sophisticated MDCM and deterministic methods.

BHARAT: A simple and effective multi-criteria decision-making method that does not need fuzzy logic, Part-2: Role in multi- and many-objective optimization problems

A simple and effective multi-attribute decision-making method, named as BHARAT method, is proposed in Part-1 of this paper and the same method is used now as a multi- and many-objective decision-making method for evaluating the Pareto optimal solutions. The proposed BHARAT method is used to identify the best compromise Pareto solution. Based on their importance for the given optimization problem, the objectives are ranked, and the weights are assigned. The weights of the objectives and the normalized values of the objectives for different Pareto optimal solutions are used to compute the total scores. The total scores are used to differentiate the alternative optimal solutions and an alternative solution that gets the highest total score is suggested as the best compromise solution. Three case studies are presented to illustrate and validate the proposed BHARAT method. The case study 1 is a multi-objective optimization problem related to cloud manufacturing with 3 objectives and 20 alternative solutions; case study 2 is a many-objective optimization problem of electro-discharge machining process with 4 objectives and 50 alternative solutions; case study 3 is a many-objective optimization of milling process parameters with 4 objectives and 100 alternative solutions. The outcomes of the suggested BHARAT method are compared with those of the other popular decision-making approaches for each of the three case studies considered. The suggested simple and more logical BHARAT method can be used in multi- and many-objective optimization problems to select the best compromise solution.

Utilizing multiple criteria decision-making optimization methods to machine LM25Al/VC material under electro-discharge machining processes

In this work, sparking electro-discharge machining (EDM) process parameters are optimized by using multiple criteria decision-making (MCDM) methods. The work piece utilized for the investigation was LM25 aluminum alloy reinforced with Vanadium carbide (VC), processed through a stir casting technique. The EDM process parameters that have been considered in this work are by peak current, pulse-on-time, and pulse-off-time, with the effects of each variable and their combinations on the performance metrics of EDM like material removal rate, electrode wearing rate, and surface roughness. In this study, three MCDM methodologies were applied to evaluate EDM performance. Then, the obtained MCDM scores were compared using two different objective verification mechanisms. In this case, the VIKOR technique delivered the best-desired results relative to TOPSIS method, and factorial analyzing method. Also, the factorial method is simpler than the other methods, though it produced nearly identical results as the sophisticated MDCM method.

Approach towards green manufacturing in Maglev EDM using different biodegradable dielectrics at variable discharge conditions

The urge to implement eco-friendly approach for modern manufacturing techniques has assisted in eliminating the hazardous effect of the undesirable byproducts released into the atmosphere. In electro-discharge machining (EDM) process, the hydrocarbon oil degradation releases various toxic gases and non-biodegradable residuals as byproducts. Several bio-dielectrics have been implemented to overcome such setbacks as an economical replacement to conventional hydrocarbon oil dielectrics. The current research demonstrates a green Maglev EDM operation on Ti-6Al-4V alloy using neem oil and canola oil as bio-dielectrics compared with EDM oil. Maglev EDM utilizes novel bipolar linear self-servo strategy for tool positioning which generates consistent machining stability by unique magnetic repulsive force balance action. The performance characteristics of all the dielectrics have been examined through machining rate (MR), tool wear rate (TWR), consumed specific energy (SE), area roughness parameters and surface morphology. The results were compared for respective bio-dielectric at variable discharge voltages (VD) i.e. 22 V, 25 V and 28 V, whereas the discharge current (ID) varied within (220-250 mA). The performance assessment depicts (25 to 28) % lower SE consumption in neem oil and (35 to 37)% in canola oil as compared to EDM oil. The surface morphology assessment portrays lower deformities and better uniformity using bio-dielectrics with huge potential for selective surface modification.

Thermo-Mechanical Treatment for Reducing the Wear Rate of CuCrZr Tool Electrodes during Electro-Discharge Machining.

The research presented in this paper focused on optimising the process of unconventional plastic forming by hydrostatic extrusion (HE) with post-processing heat treatment of a copper alloy (CuCrZr) for electro-discharge machining (EDM) applications. The treatment was carried out in such a way as to obtain a material with an improved microstructure, characterised by a significant increase in hardness and strength while maintaining a high electrical conductivity, thus achieving the main goal of reducing electrode wear in the EDM process. As part of the research, a material with an ultrafine-grained structure was obtained with an average grain size of d2 = 320 nm and a much higher strength of UTS = 645 MPa compared to the material in the initial state (UTS = 413 MPa). The post-processing treatment (ageing) allowed us to obtain a material with a high electrical conductivity after the HE process, at 78% IACS. The electrodes made of CuCrZr subjected to HE had a reduced electrical discharge wear in relation to electrodes made of the initial material. The best results were obtained for electrodes made of the material subjected to a five-stage HE process combined with ageing at 480 °C for 1 h. The electrical discharge wear in these electrodes was reduced by more than 50% compared to electrodes made of non-deformed copper.

Effect of microstructure refinement of pure copper on improving the performance of electrodes in electro discharge machining (EDM)

The paper presents an analysis of the impact of plastic deformation using hydrostatic extrusion (HE) on the structural, mechanical and functional properties of pure copper for use as electrodes in the process of electro discharge machining (EDM). As part of the research, copper was subjected to the HE process with the maximum cumulative true strain equal to ɛcum = 3.89 obtained in 5 stages. The result was, a refinement of the microstructure with the grains elongated in the direction of extrusion, with a cross-sectional size of d2 = 228 nm. As the obtained material can be potentially used in the process of electro discharge machining, the copper specimens after the HE process were subjected to a comprehensive analysis to determine the mechanical, physical and functional properties of the material. A significant increase in strength (UTS) and yield strength (YS) of the HE-processed copper was obtained, reaching respectively UTS = 464 MPa and YS = 456 MPa at the maximum strain of ɛ = 3.89. Despite the clear strain-induced strengthening of the material, a very high electrical conductivity of not less than 97% was obtained. The electrodes made of copper after HE process have reduced erosion wear while maintaining a comparable or better quality of the machined surface. The best results were obtained for finish machining, where the electrical discharge wear was lower by 60% compared to the electrode made of non-processed copper. In addition, an improvement in the surface quality after the EDM process by 25% was observed when using the HE-processed electrodes.

Simultaneous electrochemical and electrodischarge machining process: An approach to sustainable manufacturing

Manufacturing of Net Finished Shape (NFS) microholes in Inconel 718 materials with faster machining rate can offer significant benefits in terms of reduced waste, improved efficiency, and lower production costs, which are essential for sustainable manufacturing. However, the existing manufacturing method, namely electrochemical machining (ECM), results in slow machining with uncontrolled dissolution, leading to increase production time, energy consumption, and carbon emission associated with the manufacturing process. The current manuscript investigates the reason attributes for these problems through potentiodynamic polarization test. Subsequently, a new machining process known as Simultaneous electrochemical and electrodischarge machining (SECEDM) has been proposed. This frugal manufacturing-based machining process offers high machining rate (MR) and better overall hole circularity (OHC) through the synergistic effect of anodic dissolution and electrochemical discharges. The obtained results reveal that the SECEDM process offers nearly 261 % and 141 % higher MR and 1.23 % and 3.78 % better OHC than electrochemical machining (ECM) and electrodischarge machining (EDM), respectively. Moreover, SECEDM outperforms the simultaneous micro-EDM and micro-ECM process (SEDCM) process by seven times in machining rate and promotes localized dissolution than ECM. Overall, SECEDM's benefits, including its high machining rate, superior surface quality, sustainability, eco-friendliness, and elimination of the need for secondary finishing processes, make it an ideal candidate for the next-generation manufacturing process.

GENERATION OF EFFUSION HOLES ON ULTRA-HIGH TEMPERATURE ALLOY BY MICRO ELECTRO-DISCHARGE MACHINING PROCESS

Fabrication of surface features like effusion holes on ultra-high temperature (UHT) alloys with micro electro-discharge machining ([Formula: see text]-EDM) is a very convolute strategy. Due to the exceptional mechanical properties and resistance to ease brittle transformation at elevated temperatures, UHT alloys are being widely used in hot sections of aero engines. This research tailored the existing capabilities of [Formula: see text]-EDM setup by employing a copper-tungsten (Cu-W) hybrid tool electrode which has been rarely reported. This research addresses investigations, predictive modeling, and optimization during [Formula: see text]-EDM of UHT alloy, namely Inconel 718. For experimentation, the factors like inter-electrodes gap (IEG), current ([Formula: see text]), and pulse on/off time ([Formula: see text]on, [Formula: see text]off) were considered as input variables to analyze the responses like overcut (OC), tool wear rate (TWR), material removal rate (MRR), and diametric alterations in between the top and bottom shape of holes’ feature (DE). The multi-objective desirability-based artificial bee colony optimization (MOABC) projected optimal parametric settings of 5.276 A, 16.389 [Formula: see text]s, 1.77 [Formula: see text]s, and 50 [Formula: see text]m for [Formula: see text], [Formula: see text]on, [Formula: see text]off, and IEG, respectively. These settings provide MRR, TWR, OC, and DE solutions of 0.001479, −0.00038, 0.030239, and 0.047048 mm, respectively. Further, the confirmation test has been performed to validate the optimal solution. The results supported the ideal settings with error values of 0.03177, 1.31578, 0.05863, and 0.04704 for MRR, TWR, OC, and DE, respectively. Distinctive diagnostic tests assessed by several statistical parameters ([Formula: see text], [Formula: see text], [Formula: see text]2, AD-P values) confirmed that the accuracy of developed models for prediction of various performance characteristics has high degree of resemblance with experimental results and the adequacy as well as accuracy of models is also demonstrated. Moreover, the surface morphology has also been scrutinized by microscopical observation to perceive the consequences of the electro-discharge phenomenon on both electrodes. Overall, the research comprises experimentation, surface integrity study, and parametric optimization followed by a confirmation test to perform the betterment of the current [Formula: see text]-EDM approach.

Назначение рациональных режимов электроэрозионной обработки деталей из титанового сплава ВТ5 на основе решения тепловой задачи о перемещении границы фазового превращения материала

The paper presents results of theoretical studies of the VT5 titanium alloy machinability by the electrodischarge machining method based on solving the thermal problem of the material phase transformation boundary displacement (Stefan problem). It proposes a method for determining parameters of electrical pulses for the VT5 alloy electrodischarge machining in order to increase the process productivity; recommendations are provided for that purpose. Density of the heat flux and its duration were determined necessary for implementation of the VT5 alloy electrodischarge machining process. Dependences were established of the minimum value of the heat flux pulse duration, when the VT5 alloy electrodischarge machining process was possible, and of maximum value of the heat flux pulse duration ensuring maximum removal of the VT5 alloy from the workpiece in one pulse, on the heat flux density. It is shown that for the maximum productivity of the VT5 alloy electrodischarge machining at the heat flux density used, it is necessary to assign effective duration of such a flux. Dependences of the heat flux effective duration on its density were established. Besides, to assign rational modes of VT5 ally electrodischarge machining, relationships were established and provided between the VT5 alloy machinability curves (dependences of the material penetration depth on the pulse duration) and other materials, including those for which rational modes are currently defined

Experimental Study of Electro Discharge Machining (EDM) on Mild Steel (E-250) using Copper Electrode

Abstract: Electro-discharge machining is used for machining different types of hard materials which are electrically conductive and these materials are particularly challenging to manufacture using any other machining method. In electro-discharge machining electrical energy is transformed into thermal energy which is approximately 8000 to 12000 degrees Celsius and due to high thermal energy material melting and vaporising. In electro-discharge machining, three types of electrode materials are used which are copper, brass and graphite, Of all three materials, graphite has the highest electrical conductivity and brass has the lowest electrical conductivity. Electro-discharge machining process suitable for generating complex shapes and profiles. In this paper, a Copper electrode was used for machining mild steel (E-250) and analysed the MRR and Ra with a variation of discharge current keeping other variables constant and studying the consequence of different discharge currents on MRR and Ra.

Machinability study on laser-based powder bed fusion processed hypo-eutectic aluminium alloy composite (AlSi10Mg + NbC)

Understanding the machinability of additively manufactured composite materials is crucial for efficient manufacturing. The study aimed to evaluate the machinability of the composite material (AlSi10Mg + Niobium carbide (NbC)) using the Electro-discharge machining (EDM) process and to investigate the influence of different printing orientations on the EDM process. The Plackett–Burman design was initially employed to determine the significant EDM parameters. Subsequently, the Box–Behnken Design was followed to obtain the optimal settings on the EDM setup. The validation experiment based on the composite desirability approach confirmed the maximum material removal rate (MRRmax) and minimum tool wear rate (TWRmin). The identified configuration of 3 wt. % NbC reinforcement in AlSi10Mg, printed in the 0° orientation, exhibited the best performance in MRRmax: 146.43 mg/min, TWRmin: 0.00072 mg/min, and surface finish of 2.813 µm. These findings enhance the understanding of composite machinability and can assist in optimizing the EDM process for advanced materials.

Assessment of Machining of Hastelloy Using WEDM by a Multi-Objective Approach

Superalloys are a much-needed material for abundant engineering fields, such as nuclear-powered reactor components and aeronautics. Owing to their exceptional characteristics, such as higher thermal conductivity, they can be difficult to machine using conventional processes. Modern approaches to machining have evolved to utilize these materials. One of the techniques studied in this project is electrical discharge in a wire machine. This process can help to reduce the energy consumption during machining and negative impact on the environment. In addition, shortening the operation time of the machine can help to minimize its impact on the environment. The duration of the pulse and applied current are independent factors considered in this study. Material removal rate, surface roughness, dimensional deviation, and form/orientation tolerance errors are deemed as performance measures. The goal of this investigation is to reduce the time required to machine and improve the surface finish of components by implementing a Grey-based artificial neural network model. This method is useful in foretelling the conditions of the Wire Electro Discharge Machining (WEDM) process. This paper uses the Taguchi design and Analysis of Variance (ANOVA) framework to analyze the model’s variable inputs. The overall best coefficient of correlation (R = 0.9981) is fetched with an RMSE value of 0.0086. The material removal rate has been increased by decreasing the time taken for removal, which gives the possibility of consuming minimum energy. The finishing of the machined surface also improved. Moreover, this paper shows how to use an Artificial Neural Network (ANN) model with Grey Analysis. The results of the comparative analysis show that the values envisaged are closer with the actual values. The foretelling capacity of the evolved model is confirmed with the performance analysis of the developed model.

Surface morphology and drilled hole accuracy of conductive ceramic composites Si3N4–TiN and MoSi2–SiC on EDMed surfaces

Electro-discharge machining (EDM) was employed to cut conductive ceramic composites consisting of Silicon Nitride-Titanium Nitride (Si3N4–TiN) and intermetallic ceramic composite (MoSi2–SiC), with the geometrical properties of the machined hole and the measurement of performance metrics of essential concern in the EDM process being recorded. Machining characteristics including current, spark on time, spark off time, and dielectric pressure are compared for both conductive ceramic composites. For multiple responses to geometrical errors such circularity, cylindricity and perpendicularity, as well as to performance metrics like metal removal rate (MRR), electrode wear ratio (EWR), machining time and workpiece and electrode surface integrity, spark gap time is preferable. The experimental runs to determine the optimal parameters of Si3N4–TiN and MoSi2–SiC ceramic composite are carried out using Taguchi's L9 OA based on the design of experiments (DOE). SEM with EDAX analysis of the machined surface of both composites allows for in-depth research into the machining process and a comparison of the removal mechanism and surface topography. The surface textures of 9 different holes and electrodes for ceramic composites are analysed by comparing the machined surface of the best hole with the best electrode to the machined surface of the worst hole with the worst electrode. As a consequence, the EDM process seems to be a promising method for manufacturing excellent surfaces in an electrically conductive Si3N4–TiN and MoSi2–SiC composite under the slow process parameters condition of conductive ceramic composites. This was demonstrated by the comparative analysis and establishing that was previously discussed.