Erosion Machining Research Articles

Experimental Investigation on Wire Electric Erosion Behaviour of Silicon Dioxide Particulate Reinforced Composite

The intend of current study was focused on the prediction of material removal rate (MRR) and surface roughness (SR) for the AA7050-SiO2 composite during wire electric erosion or discharge machining (WEDM) process using a brass (Br) wire electrode. Here, stir casting process was employed to develop the AA7050 matrix composite with inclusion of 10wt.% SiO2 particle reinforcement. The multi-objective optimization method of Technique for order preference by similarity to ideal solution (TOPSIS) approach has been applied to find out the optimal setting of input machining parameters such as peak current (Ip), pulse-on time (Ton) and pulse-off time (Toff). Furthermore, the significant effects of parameters were identified by analysis of variance (ANOVA). Taguchi L9 (33) orthogonal design has been formulated to perform the experimental work. TOP SIS results stated that the optimal setting of Ip at 30 amps, Ton of 130 μs and Toff of 55 μs provide the better MRR with lesser SR. The ANOVA results noticed that Ip has the prime noteworthy parameter over the adopted responses having a contribution of 45.67%, followed by Ton (32.34%) and Toff (12.26%), respectively. The confirmation test was carried out by the optimal parameters setting to verify the predicted results. Finally, the scanning electron microscopy (SEM) test was carried out for the machined surface of the composite specimen and it was reveals that the formation of craters and recast layer thickness in the machined surfaces.

Slurry Erosion Resistance, Morphology, and Machine Learning Modeling of Plasma-Sprayed Si3N4+TiC+VC and CrNi based Ceramic Coatings

This study presents a comprehensive analysis of the morphology, mechanical properties, erosion resistance, and machine learning modeling of Si3N4+TiC+VC and CrNi based ceramic coatings deposited via plasma spraying. The cross-sectional morphology analysis revealed good mechanical interlocking between the coatings and the substrate, with pores predominantly observed in the Si3N4+TiC+VC coating. The coating thicknesses were measured as follows: 260 μm for Si3N4+TiC+VC, 243 μm for Si3N4+TiC+VC blended with CrNi, and 232 μm for pure CrNi coating. Mechanical characterization showed that microhardness values ranged from 1933 HV for Si3N4+TiC+VC coating to 499 HV for pure CrNi coatings. Slurry erosion tests demonstrated that pure Si3N4+TiC+VC coating exhibited superior erosion resistance at 90º impingement angle compared to other coatings. Additionally, a rigorous evaluation of over 20 machine learning regression models revealed that Gaussian Process Regressors and Artificial Neural Network (ANN) with a layer size of 20, displayed satisfactory performance in modeling mass loss prediction. The erosion mechanisms observed in the coatings provided valuable insights into their response to slurry erosion, highlighting the influence of coating composition and impingement angles. The findings underscore the potential of Si3N4+TiC+VC ceramic coatings to enhance the erosion resistance of stainless steel, offering promising applications in various industries.

Optimization of wire spark erosion machining of Grade 9 titanium alloy (Grade 9) using a hybrid learning algorithm

Manufacturing has grown challenging because of the increased usage of harder materials, such as titanium alloys, in many industries, such as aerospace, automobiles, and marine. Conventional material removal procedures are not suitable for these tough materials due to their increased hardness and slow machinability. Wire Electrical discharge machining (WEDM) is a modern approach for material removal, particularly for harder materials, such as titanium alloys, nickel alloys, hard particle reinforced metal matrix composites, etc. The research design was performed by deeming the independent factors, such as duration of pulse and applied current. The removal rate of material, surface roughness of the machined region, dimensional deviation, and tolerance errors in form/orientation are considered performance metrics. Taguchi’s approach was engaged to assess the process variables, and the importance of the process factors was established using analysis of variance approach. The purpose of this research is to create an AI based decision making tool, which can be utilized to anticipate the various parameters that impact the WEDM material removal process. The discoveries of the present exploration allowing the manufacturers to make better-informed decisions with a developed model’s capability by demonstrating that the model’s predicted values were in close confirmation to the actual values.

Spark erosion behavior in the machining of MoSi2–SiC ceramic composites for improving dimensional accuracy

The novel applications of MoSi2 and SiC as matrix and reinforcing materials in the creation of high-performance composites were investigated in this work. In particular, Spark Erosion Machining's geometric tolerances were studied in order to shed light on the technique's potential for precision manufacture in the realm of MoSi2–SiC composites. Our research focused on evaluating critical parameters and their impact on machining performance, including material removal rate, surface roughness, wear rate and drilled hole accuracy. In-depth research revealed the critical input factors that had the greatest impact on the machining procedure. Notably, parameters such as current (32%), sparking on time (23%), sparking gap voltage (12%), dielectric pressure (12%), and sparking off time (17%) emerged as the most influential factors, as determined by ANOVA analysis. These findings provide valuable insights into optimizing the Sparking EDM approach for MoSi2–SiC composite materials. This study further demonstrated the improvement in composite desirability ratings across multiple performance criteria, highlighting the effectiveness of Sparking EDM in enhancing machining outcomes (e.g., from 0.8523 to 0.9527). Correlations between the EDM's output responses were found to be quite high when geometric tolerances and the coefficient of determination (R2) were used (0.7858, 0.9625, 0.8427, 0.8678, 0.8474, 0.8368, 0.8344, 0.8671). Consider that, for the sake of a more complete understanding of the procedure's approach, the emphasis is on the methodology rather than the multifaceted metal removal mechanisms involved. This research doesn't dive further into the physical concerns of Spark Erosion Machining, but it does provide insights into the practical application of this technique in the precision manufacturing of MoSi2–SiC composite materials. For real-world medical applications such implanted devices, dental implants, surgical instruments, biological sensors and diagnostics, this study provides a valuable and encouraging approach. A validation experiment verifies the results, proving the feasibility of improved spark erosion in high-precision production. The results of this research show that EDM methods can be fine-tuned to produce ceramic composites with much greater MRR, superior surface finishes and a marked decrease in subsurface cracking and microstructural modifications. This is essential for protecting the integrity of materials used in life-saving medical equipment.

Optimization of spark erosion machining on synthesized boron carbide based bronze composite

The development and research is about advanced composite that is been highly increased in all sectors of all modern industries. The material with reinforcement of carbides has provided the exceptional substance properties. Boron carbide reinforced bronze composite is synthesized using stir casting route. A weight proportion of B4C with 1.5% were considered for the investigation. The present investigation and the objective is to optimize by Taguchi approach on synthesized boron-carbide based bronze composite. The evaluation of substance properties and characterization were investigated. The characterization studies and confirmation of elemental role were investigated by Scanning electron microscope (SEM). The machinability behaviors of synthesized bronze composite are analyzed by EDM process with copper chromium tool. The machined surface was investigated using atomic force microscopy.

Analyzing the geometrical errors of silicon nitride-titanium nitride on performing electric discharge machining using response surface methodology

Ceramic materials that find their applications in die extrusion and the balls used in bearings have a longer service life compared to that of traditional materials. Since ceramic materials are having high hardness properties, they cannot be machined traditionally, because traditional machining processes rely on the relative hardness of the tool material to the workpiece material. However, electric discharge machining aids in the machining of ceramic composites with good surface integrity performed by the copper electrodes. As a result, Spark Erosion Machining was used to investigate the geometrical tolerance of Si3N4-TiN composites. Electric discharge machining parameters range over five levels, like current from 2 to 6 A, voltage from 30 to 50 V, dielectric pressure (kg/cm2) from 16 to 24 kg/cm2, pulse on time (µs) from 15 to 19 μs, and pulse off time (µs) from 7 to 11 μs have been analyzed through an L25 orthogonal array. Main effect plots and two-dimensional and three-dimensional interaction plots have been drawn to investigate the effect of the input parameter on the output parameters like circularity, cylindricity, perpendicularity, runout, top radial overcut, and bottom radial overcut. The grey relational analysis is employed in finding the significant parameters through analysis of variance, and for each model, the regression coefficient is found. The optimal input parameters for the desired output parameters are found to be a current of 5.855 A; pulse-on time of 16.55 µs; pulse-off time of 7.22 µs; dielectric pressure of 16.32 kg/cm2; and a voltage of 40.3729 V. This research will help to enhance the geometric accuracy and precision of machined holes in Si3N4-TiN composites. The results are finally estimated using a residual data analysis, which shows that spark erosion can be improved.

Machinability assessment of AA7075 composite reinforced with rice husk ash using spark erosion machining process

ABSTRACT In this present study, stir cast AA7075 composite containing 5 wt.% quantity of rice husk ash was machined through electrical discharge machining process. The effects of variation of different process variables including peak current, pulse on time, and gap voltage along with constant duty cycle on performance attributes such as material removal rate (MRR), tool wear rate (TWR), and surface roughness (SR) were evaluated by differing one parameter at a time. Analysis of results revealed that MRR showed directly proportional relationship with current and decreased with increasing gap voltages. MRR also varied directly with pulse on time upto 300 µs and decreased afterwards. TWR enhanced with increasing peak current and pulse duration whereas insignificant variation of TWR with changing gap voltages was observed. SR was found to be significantly exhibiting increasing trend with increasing current and pulse duration. However, SR exhibited a fluctuating trend with increase in gap voltage. EDM surface was also characterised through SEM.

Evolution of regression and ANFIS models for wire spark erosion machining of aluminium metal matrix composites for aerospace applications

Evolution of regression and ANFIS models for wire spark erosion machining of aluminium metal matrix composites for aerospace applications

Критерий оценки электроэрозионной стойкости материалов

The article describes a method for obtaining a criterion for the electrical erosion resistance of materials used for the manufacture of electrodes for electric erosion machining. The assessment of the electrical erosion resistance of materials according to the Palatnik criterion was found to be inaccurate. It is shown that the electrical erosion resistance is inversely related to the material density and that the material thermal conductivity and not its melting temperature exerts the greatest effect on it. Further research will be aimed at obtaining a universal high-precision mathematical model of the criterion for the material electrical erosion resistance according to its thermophysical characteristics.

Surface integrity analysis of machined surface of Ni-Ti shape memory alloy during wire spark erosion machining

PurposeThe purpose of this paper is to analyze the surface integrity, including recast layer thickness, surface crack density, X-ray diffractions study and microhardness for Ni53.49Ti46.51 shape memory alloy (SMA) during wire-spark erosion machining.Design/methodology/approachFour persuasive process parameters, that is, spark on time (SON), spark off time (SOFF), wire feed (WF) and spark gap voltage (SV), have been chosen for the current investigation. Efforts have been done to explore the effects of above said parameters on the machined surface of Ni-Ti SMA by embracing box Behnken design of response surface methodology (RSM). Cutting speed and ten-point mean roughness (Rz) has been taken into account as response variables. Analysis of variance test was also performed for both response parameters with the coefficient of determination (R2) 0.9610 for cutting speed and 0.9252 for ten-point mean Rz.FindingsThe recast layer thickness from 7.83 to 12.13 µm was developed near the machined surface at different parametric settings. The least surface crack density was found at the lowest value of ten-point mean Rz, while most surface crack density was identified at the highest value of cutting speed. The microhardness near the machined surface was increased by approximately 1.8 times bulk-hardness of Ni53.49Ti46.51 SMA.Originality/valueSome researchers have done a study on average surface roughness, but very few investigators concentrated on ten-point mean Rz. Surface crack density is an essential aspect of machined parts; other researchers have seldom reported it. The novelty of this research work is that the influence of SON, SV, WF and SOFF on cutting speed, Rz, recast layer thickness, micro-hardness and surface crack density proximate the machined surface while machining workpiece material.

Investigation of Process Parameters for Optimum Thermal Energy Distribution in Spark Erosion Process

In the Spark Erosion machining process, the electrical energy in the inter-electrode gap gets converted into thermal energy. Whatever thermal energy generated in inter electrode gap gets distributed among anode, cathode and the dielectric fluid. The workpiece in spark erosion process is kept as anode and the fraction of the total energy which is going to the anode (workpiece) should be maximum. As this thermal energy is responsible for the melting of material on the workpiece. This fraction of energy is the important parameter used to predict the effective use of total heat energy generated between tool and workpiece. The fraction of energy that is going to workpiece changes with change in machine parameter. It has been observed from the literature that the researcher simply considered a variation of spark voltage in analysis as a significant parameter in deciding material removal rate. In this work is variation of fraction of energy is experimentally determined with process parameters by using heat transfer equations during the spark erosion process of EN-31. The results showed that the ratio of amount of energy going to workpiece and total energy generated at inter electrode gap ranges from 9.56% to 18.97%. So, fraction of energy which is going to workpiece at different machining process parameter changes significantly, which proves that the it has significant impact on material removal rate and should be considered in study of spark erosion process.

Developing Meso and Microholes by Spark-Erosion Based Drilling Processes: A Critical Review.

The increased demand for miniature components has drawn the attention of researchers, engineers, and industry users to manufacture precision micro and mesoholes on foils, sheets, and plates made from a variety of engineering materials. These days, micro-drilling is extensively being adopted as a fundamental operation in all kinds of smart manufacturing industries to make different types of microholes, such as through holes, blind holes, and taper holes on micro-parts and components. Drilled holes with a diameter of less than 1 mm are referred to as microholes, while drilled holes whose diameter ranges between 1 and 10 mm are known as mesoholes. Meso and microholes are commonly referred to as fine-holes. Modern or advanced drilling processes are mostly used to drill microholes from a variety of materials. This paper presents an extensive review of the previous research conducted on the drilling of fine holes (meso and micro size) by spark- erosion-based processes along with highlighting work and tool electrode materials, specifications of drilled holes, types of microholes (through or blind holes), process parameters, performance measures, and key findings. The paper aims to facilitate researchers and scholars by highlighting the capabilities of spark erosion machining, drilling, and its variants to fabricate miniature holes. The paper ends with a conclusion and future research directions to encourage further work in this area.

Investigation of The Effects of Processing Parameters on Measuring Accuracy in Electro Erosion Machining of Ti-6Al-4V Alloy

Titanium alloys are one of the materials that are difficult to process due to their high strength, high hardness and low thermal conductivity, wherefore low tool life and surface quality and high energy consumption are involved in shaping them with traditional manufacturing methods. In particular, special tool geometries are required for the machining of complex geometry parts including helical groove, keyseat, micro-holes, etc. with traditional manufacturing methods, which leads to increases in machining costs. In such cases, non-traditional alternative processing methods are preferred. In this study, keyseat shaping procedures were performed according to DIN 6885 standard in the electro (die-sinking) erosion machine for Ti-4Al-6V alloy. As a result of experiments conducted in copper electrode and Belone EDM F dielectric fluid environment, the effects of different processing parameters (discharge current, pulse on time and pulse off time) on measuring accuracy were investigated. In addition, the effects of 3D surface and SEM images and processing parameters on the accuracy of the coordinate measurement were evaluated. With the low discharge current, less thermal energy is transferred to the workpiece and smaller particles are removed from the workpiece, obtained in closer results to the targeted values. The biggest difference between the targeted keyseat depth, width and length and the measured value was 18.13%, 4.24% and 0.625%, respectively. The results closest to the specified standard keyseat dimensions were obtained in Ip=9A, Ton=150μs, Toff=120μs processing parameters.

Development of quality microholes by electrical discharge drilling on Al/SiC composite using of Grey-desirability approach

Electric discharge drilling (EDD) is a variant of spark erosion machining and is successfully used for the drilling of quality microholes. In present research, an attempt was made to drill microholes on Al/SiC composite. The drilling on aluminum composite was made at different machining indicators to analyze its effect on drilling rate (DR), electrode wear ratio (EWR), hole overcut (HO) and circularity (C). The input parameters selected in this work are pulse on-time (Ton), peak current (Ip) and pulse off-time (Toff). The experiments were planned as per Taguchi's L9 orthogonal array (OA). It was found that with the increase in Ton value, HO and EWR increases. However, larger values of Ip and Toff decreases the HO and EWR. Due to the combination of different quality characteristics Grey theory along with desirability has been implemented for collective response of output parameters. The optimized setting for multiple performance characteristics is Ton: 40; Ip: 3; Toff: 50. An improvement of 0.0199 is observed in grade value during optimization as compared to the maximum calculated grade value. After the implementation of proposed optimization technique, an improvement of 42.88% in DR, a reduction of 33.59% in EWR, a reduction of 4.54% in HO and 0.68% in C is observed.

Process Modelling and Optimization using ANN and RSM during WSEM of Ni51.59Ti48.41 shape memory alloy

Shape memory Ti-Ni alloys have fascinated significantly in recent years since these types of material are intelligent, shape memory and functional materials. These materials find many applications in the engineering and medical fields. In the current study, ‘Ni-Ti’ shape memory alloy (SMA) has been processed by wire spark erosion machining (WSEM). This research article explores the effects of controllable machining variables such as spark on-time, spark off-time, wire feed and servo voltage on productivity, i.e., material removal rate (MRR) and surface integrity. To assess the impact of WSEM controllable factor, a statistical analysis is done. Mathematical modelling and ANOVA study have been conducted after performing 29 experiments based on Box-Behnken design (BBD) of response surface methodology (RSM) technique. Artificial neural network (ANN) modelling technique is used for further prediction of the response. The predicted values obtained from the ANN model shows excellent agreement with experimental outcomes. In this study, the correlation coefficient (R) value is 0.9919, which is very close to unity. It is clearly showing that the prediction accuracy of ANN model is high. Furthermore, scanning electron microscope (SEM) is utilized to assess the microstructure and composition of the WSEMed surfaces. After a critical study, it has been noticed that machined surfaces contain debris, cracks, craters and spherical droplets. In addition, energy dispersive spectroscopy (EDS) analysis has been performed to check the elemental composition on the machined surface.

Review on MRR in Spark Erosion Machining (SEM) Through ANN

EDM is a modern machining technology used to machine hard material pieces that are difficult to produce using traditional machining methods. This article aims to optimize process factors to obtain maximum MRR and high surface integrity in the end cut. Using artificial neural networks, this research proposes a technique for automatically determining and optimizing processing parameters in the EDM sinking process (ANN). The availability of machining data in the industrial tool room survey is the primary issue regarding adjusted process parameters for precision machining. Experiments are conducted to investigate the effect of pulse current, pulse on time, electrode area, and gap voltage on MRR response.

Experimental investigation of different unconventional machined surface on hardox steel

Machinability and surface behaviours are playing an essential role in metal forming and manufacturing processes. Hardox 500 steel is machined by ultrasonic machining (USM) and spark erosion machining (SEM) processes. The different input factors are used in both the processes and evaluate the rate of metal removal. Current, voltage and pulse duration are the control factors for spark erosion. Power rating, slurry concentration and grit size are the control factor for USM. Scanning force microscopy (SFM) is used to investigate the surface topography of the hardox steel. The effect of input constrains on rate of metal removal (RMR) is validated by variance analysis. In SEM process, current was the most effective factor on rate of metal removal and it’s provided the maximum contribution (79.75%) than other factors such as pulse duration (16.73%) and voltage (3.43%). In USM process, slurry concentration was the most effective factor on rate of metal removal and it’s provided the maximum contribution (83.78%) than other factors. The contribution effect of grit size and power rating is 13.15% and 2.53% respectively. Based on surface plot analysis, the machined surface of SEM is better than USM surface.

Vegetable oil based dielectric fluids for electrical discharge Machining Process: Advancements and challenges

Electrical Discharge Machining Process, also termed as Spark Erosion Machining has been effectively in practice in different industrial sectors for machining variety of hard-to-cut materials. However, this machining method is associated with number of limitations including toxic gases emissions, fire hazards, waste dielectric disposal problems, etc. With a purpose of reducing such disadvantages, new class of dielectric fluids derived from vegetable oils have been put in practice over past number of years. Common examples of vegetable based dielectrics in EDM process are Jatropha oil, sunflower oil, canola oil, neem oil, pongamia pinnata oil, etc. Use of such green dielectrics has added to the sustainability aspect while machining through EDM process. This review article highlights the effect of machining different hard materials in bio-based dielectric fluids to machining in conventional hydrocarbon oils by comparing their material removal rates, electrode wear rates, surface finish, and surface topographies. Moreover, areas in this field of green EDM which further need to be studied are also highlighted and can be taken as prospects for future study.

Evaluation of Abrasive WearRate and Machining Behaviors of Synthesized Nitinol Composite

The present investigation deals with wear and machining behaviors of manufacture nitinol composite through Vacuum Induction Melting (VIM). The major composition of nickel and titanium was reinforced with tungsten carbide (WC). Scanning Electron Microscopy (SEM) was employed to investigate the morphology of the synthesized nitinol composite. For investigating the topography of the surface of the nitinol composite was analyzed by scanning force microscopy or atomic force microscopy. Spark erosion machining has been applied to explore the machining behavior of the nitinol composite. Abrasive Wear Rate (AWR) is evaluated by using abrasion tester. Machining and wear parameters are optimized by applying taguchi approach. The contribution and the effect of input constraints on the responses are investigated by analysis of variance.Optimal abrasive wear rate was attained at 900 rpm of disc speed, 12 gm/min of abrasive flow rate and 400m of sliding distance. Disc speed was a dominant factor and it has developed 43.86% effect on abrasive wear rate. Optimal rate of metal removal was achieved at 45A of current, 200µs of pulse on time and 35V of Volts. The current was the leadingfactor and it has produced 86.38% effect on the rate of metal removal.

Surface integrity analysis in powder mixed EDM of Nimonic 263

Powder mixed Electrical Discharge machining (PMEDM) is an effective process in improving rate of material removal (MRR) and surface finish. But influence of powder mixed in the dielectric on the surface quality of the machined profile is an essential aspect of machining effectiveness. Nimonic 263 though imbibed with many advanced properties, is regarded as a difficult to machine materials by conventional methods. Spark erosion machining process is independent of the workpiece hardness and can machine any electrically conductive material. Hence EDM can be an effective alternative for machining Nimonic 263. But machining performance may vary depending upon the working medium. In this work, performance of spark erosion process in machining of Nimonic 263 has been evaluated using three different dielectric conditions. Kerosene has been taken as the dielectric fluid. Graphite micro powder as a conductive powder and alumina micro powder as a non-conductive powder have been added to the dielectric fluids for assaying their influence on the responses. Only the dielectric condition has been varied and all other parameters viz. pulse on time, peak current, gap voltage, duty factor and spark time have been kept constant at 20 µs, 6 A, 30 V, 42% and 3 s respectively. Dielectric breakdown voltage (DBV), surface topography, surface crack density (SCD), recast-layer thickness (RLT), microhardness have been considered as the performance measures in this study. Apart from these responses, 3D surface analysis has been carried out for the machined surfaces obtained by each of the dielectric conditions. Graphite powder mixed kerosene has been found to be the most suitable dielectric condition with best surface finish.