Influence of Process Parameters on the Microstructural Characteristics and Mechanical Properties of Recast Layer Thickness Coating on Die Steel Machined Surface after Electrical Discharge Machining

Nickel-based alloys are finding a wide range of applications due to their superior properties of maintaining hardness at elevated temperatures, low thermal conductivity and resistance to corrosion. These materials are used in aircraft, power-generation turbines, rocket engines, automobiles, nuclear power and chemical processing plants. Machining of such alloys is difficult using conventional processes. Wire-cut electrical discharge machining is one of the advanced machining processes, which can cut any electrically conductive material irrespective of its hardness. One of the major disadvantages of this process is formation of recast layer as it affects the properties of the machined surfaces. In this study, experimental investigation has been carried out to study the effect of wire-cut electrical discharge machining process parameters on micro-hardness, surface roughness and recast layer while machining Inconel-690 material. Interestingly, hardness of the machined surface was found to be lower than that of the bulk material. The micro-hardness and recast layer thickness are inversely related to the variation of process parameters. Recast layer thickness, surface roughness and hardness of the wire-cut electrical discharge machined surfaces of Inconel-690 are found to be in the range of 10–50 µm, 0.276–3.253 µm and 122–171 HV, respectively, for different conditions. The research findings and the data generated for the first time on hardness and recast layer thickness for Inconel-690 will be useful to the industry.

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Analysis of recast layer thickness and martensitic layer thickness in wire electrical discharge machining

Materials Today Proceedings ◽

10.1016/j.matpr.2021.01.698 ◽

2021 ◽

Author(s):

Khuvendra Yadav ◽

Sharad K. Pradhan

Keyword(s):

Layer Thickness ◽

Electrical Discharge ◽

Electrical Discharge Machining ◽

Recast Layer ◽

Wire Electrical Discharge Machining ◽

Recast Layer Thickness

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Optimization and surface modification in electrical discharge machining of AA 6061/SiCp composite using Cu–W electrode

Proceedings of the Institution of Mechanical Engineers Part L Journal of Materials Design and Applications ◽

10.1177/1464420715596544 ◽

2015 ◽

Vol 231 (3) ◽

pp. 332-348 ◽

Cited By ~ 4

Author(s):

Balbir Singh ◽

Jatinder Kumar ◽

Sudhir Kumar

Keyword(s):

Process Parameters ◽

Electrical Discharge Machining ◽

Removal Rate ◽

Surface Characteristics ◽

Electrode Wear ◽

Material Transfer ◽

Machined Surface ◽

Recast Layer Thickness ◽

Pulse On Time ◽

Pulse Off Time

This paper presents the experimental investigation on the electro-discharge machining of aluminum alloy 6061 reinforced with SiC particles using sintered Cu–W electrode. Experiments have been designed as per central composite rotatable design, using response surface methodology. Machining characteristics such as material removal rate (MRR), electrode wear ratio (EWR), and surface roughness (SR) have been investigated under the influence of four electrical process parameters; namely peak current, pulse on time, pulse off time, and gap voltage. The process parameters have been optimized to obtain optimal combination of MRR, EWR, and SR. Further, the influence of sintered Cu–W electrode on surface characteristics has been analyzed with scanning electron microscopy, energy dispersive spectroscopy, and Vicker microhardness tests. The results revealed that all the process parameters significantly affect MRR, EWR, and SR. The machined surface properties are modified as a result of material transfer from the electrode. The recast layer thickness is increased at higher setting of electrical parameters. The hardness across the machined surface is also increased by the use of sintered Cu–W electrode.

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Surfactant and graphite powder–assisted electrical discharge machining of titanium alloy

Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture ◽

10.1177/0954405415579019 ◽

2016 ◽

Vol 231 (4) ◽

pp. 641-657 ◽

Cited By ~ 21

Author(s):

Murahari Kolli ◽

Adepu Kumar

Keyword(s):

Surface Roughness ◽

Titanium Alloy ◽

Electrical Discharge ◽

Material Removal ◽

Electrical Discharge Machining ◽

Removal Rate ◽

Graphite Powder ◽

Recast Layer ◽

Dielectric Fluid ◽

Recast Layer Thickness

Surfactant and graphite powder–assisted electrical discharge machining was proposed and experiments were performed on titanium alloy in this investigation. Analysis was carried out to observe changes in dielectric fluid behaviour, material removal rate, surface roughness, recast layer thickness, surface topography and energy-dispersive X-ray spectroscopy. It was found out that the addition of surfactant to dielectric fluid (electrical discharge machining oil + graphite powder) improved the material removal rate and surface roughness. It was noticed to have reduced the recast layer thickness and agglomeration of graphite and sediment particles. Biface material migrations between the electrode and the workpiece surface were identified, and migration behaviour was powerfully inhibited by the mixing of surfactant. Surfactant added into dielectric fluid played an important role in the discharge gap, which increased the conductivity, and suspended debris particles in dielectric fluid reduced the abnormal discharge conditions of the machine and improved the overall machining efficiency.

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Modeling of Recast Layer in Micro-Electrical Discharge Machining

Journal of Manufacturing Science and Engineering ◽

10.1115/1.4001480 ◽

2010 ◽

Vol 132 (3) ◽

Cited By ~ 12

Author(s):

P. C. Tan ◽

S. H. Yeo

Keyword(s):

Numerical Model ◽

Electrical Discharge ◽

Prediction Models ◽

Electrical Discharge Machining ◽

Performance Measure ◽

Recast Layer ◽

Micro Edm ◽

Machined Surface ◽

Functional Layer ◽

Pulse On Time

The thickness of recast layers produced during electrical discharge machining (EDM) is an important process performance measure as it may indicate an extent of crack propagation in a machined surface or thickness of a functional layer alloyed onto a machined surface. Thus, the availability of the recast layer thickness prediction models is needed to allow better control of machining outcomes, which becomes more vital for micro-EDM due to the microscale of machined features. The proposed numerical model, based on a multiple discharge approach for recast layer prediction, is developed to fill an existing gap in micro-EDM. The multiple discharge approach accounts for the overlapping nature by which craters are generated on the machined surface and considers the recast layer to be a combination of individual recast regions from individual craters. The numerical analysis, based on finite element methods, is used to determine the melting isotherms due to heat inputs on overlapping crater profiles. Then, a hemispherical-capped crater profile is estimated by applying a recast plasma flushing efficiency to the amount of molten material bounded by the melting isotherm. Finally, the recast region is defined to be bounded by the melting isotherm and crater profile. The model, developed for a peak discharge current of 1.45 A and pulse on time between 166 ns and 606 ns, predicted recast layer thicknesses of between 1.0 μm and 1.82 μm. It is then validated at pulse on time settings of 244 ns and 458 ns, which generated average recast layer thicknesses of 1.18 μm and 1.56 μm, respectively. Thus, the numerical model developed using the multiple discharge approach is suitable for estimation of recast layer thicknesses in micro-EDM.

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Surface Study in a Non-conventional (Electrical Discharge Machining) Process for Grade 6 Titanium Material

Jurnal Teknologi ◽

10.11113/jt.v68.1670 ◽

2014 ◽

Vol 68 (1) ◽

Author(s):

Md. Ashikur Rahman Khan ◽

M. M. Rahman

Keyword(s):

Surface Roughness ◽

Process Parameters ◽

Electrical Discharge ◽

Electrical Discharge Machining ◽

Machining Process ◽

Machined Surface ◽

Titanium Material ◽

Pulse On Time ◽

Pulse Off Time ◽

Off Time

Electrical discharge machining (EDM) produces complex shapes and permits high-precision machining of any hard or difficult-to-cut materials. The performance characteristics such as surface roughness and microstructure of the machined face are influenced by numerous parameters. The selection of parameters becomes complicated. Thus, the surface roughness (Ra) and microstructure of the machined surface in EDM on Grade 6 titanium alloy are studied is this study. The experimental work is performed using copper as electrode material. The polarity of the electrode is maintained as negative. The process parameters taken into account in this study are peak current (Ip), pulse-on time (Ton), pulse-off time (Toff), and servo-voltage (Sv). A smooth surface finish is found at low pulse current, small on-time and high off-time. The servo-voltage affects the roughness diversely however, a finish surface is found at 80 V Sv. Craters, cracks and globules of debris are appeared in the microstructure of the machined part. The size and degree of craters as well as cracks increase with increasing in energy level. Low discharge energy yields an even surface. This approach helps in selecting proper process parameters resulting in economic EDM machining.

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Parameter optimization and experimental study on wire electrical discharge machining of porous Ni40Ti60 alloy

Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture ◽

10.1177/0954405415577710 ◽

2015 ◽

Vol 231 (6) ◽

pp. 956-970 ◽

Cited By ~ 31

Author(s):

Neeraj Sharma ◽

Tilak Raj ◽

Kamal Kumar Jangra

Keyword(s):

Process Parameters ◽

Electrical Discharge ◽

Electrical Discharge Machining ◽

Machining Process ◽

Wire Electrical Discharge Machining ◽

Influence Of Process Parameters ◽

Work Surface ◽

Pulse On Time ◽

Pulse Off Time ◽

Response Variables

NiTi is a shape memory alloy, mostly employed in cardiovascular stents, orthopedic implants, orthodontic wires, micro-electromechanical systems and so on. The effective and net shape machining of NiTi is very critical for excellent response of this material in medical and other applications. The present experimental work on wire electrical discharge machining process identifies the influence of process parameters that affect the cutting rate, dimensional shift and surface roughness while machining of porous nickel–titanium (Ni40Ti60) alloy. Porous Ni40Ti60 alloy was produced in-house using powder metallurgy technique. Response surface methodology–based central composite rotatable design has been used for the planning of experiments on wire electrical discharge machining. Empirical relations have been developed between the process parameters (pulse on-time, pulse off-time, servo voltage and peak current) and response variables. Desirability approach has been used for optimizing the three response variables simultaneously. Confirmation experiments were also performed at the optimized settings and reflect a close agreement between the predicted and experimental values (percentage error varies from −6.13% to +6.85%). Using wire electrical discharge machining, NiTi alloy can be machined easily and successfully in single-cutting operation, but after the first cut in wire electrical discharge machining, a surface projection appears on work surface which is the unmachined material on work surface.

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Modeling and Optimization of Fractal Dimension in Wire Electrical Discharge Machining of EN 31 Steel Using the ANN-GA Approach

Materials ◽

10.3390/ma12030454 ◽

2019 ◽

Vol 12 (3) ◽

pp. 454 ◽

Cited By ~ 6

Author(s):

Arkadeb Mukhopadhyay ◽

Tapan Barman ◽

Prasanta Sahoo ◽

J. Davim

Keyword(s):

Neural Network ◽

Genetic Algorithm ◽

Fractal Dimension ◽

Process Parameters ◽

Electrical Discharge ◽

Electrical Discharge Machining ◽

Wire Electrical Discharge Machining ◽

Machining Parameters ◽

Machined Surface ◽

Wedm Process

To achieve enhanced surface characteristics in wire electrical discharge machining (WEDM), the present work reports the use of an artificial neural network (ANN) combined with a genetic algorithm (GA) for the correlation and optimization of WEDM process parameters. The parameters considered are the discharge current, voltage, pulse-on time, and pulse-off time, while the response is fractal dimension. The usefulness of fractal dimension to characterize a machined surface lies in the fact that it is independent of the resolution of the instrument or length scales. Experiments were carried out based on a rotatable central composite design. A feed-forward ANN architecture trained using the Levenberg-Marquardt (L-M) back-propagation algorithm has been used to model the complex relationship between WEDM process parameters and fractal dimension. After several trials, 4-3-3-1 neural network architecture has been found to predict the fractal dimension with reasonable accuracy, having an overall R-value of 0.97. Furthermore, the genetic algorithm (GA) has been used to predict the optimal combination of machining parameters to achieve a higher fractal dimension. The predicted optimal condition is seen to be in close agreement with experimental results. Scanning electron micrography of the machined surface reveals that the combined ANN-GA method can significantly improve the surface texture produced from WEDM by reducing the formation of re-solidified globules.

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Correlation of surface roughness and recast layer thickness in electrical discharge machining

Proceedings of the Institution of Mechanical Engineers Part E Journal of Process Mechanical Engineering ◽

10.1177/0954408915600949 ◽

2015 ◽

Vol 231 (3) ◽

pp. 414-424 ◽

Cited By ~ 4

Author(s):

Yakup Yildiz ◽

Murali M Sundaram ◽

Kamlakar P Rajurkar ◽

Ahmet Altintas

Keyword(s):

Surface Roughness ◽

Layer Thickness ◽

Electrical Discharge ◽

Electrical Discharge Machining ◽

White Layer ◽

Processing Technique ◽

Recast Layer ◽

Image Processing Technique ◽

Recast Layer Thickness ◽

Two Parameters

Electrical discharge machining (EDM) is an extensively used method in the machining of electrically conductive materials. Recast or white layer formation is undesirable, but inevitable, result of EDM and needs to be understood and accurately determined to efficiently perform post-treatment processes for removing the recast layer caused by EDM process. In this study, recast layer thickness and surface roughness data obtained from experimental study were analyzed and a correlation between these two parameters has been established. Image-processing technique has been used for obtaining of recast layer thickness data. It was observed that the correlation between recast layer thickness and surface roughness increases remarkably with the increase of working current and pulse time. The correlation obtained in this study has the potential to predict the recast layer thickness on spark-eroded surfaces from simple surface roughness values instead of using the prevailing time-consuming and tedious etching and polishing method. The possible approximation of the recast layer thickness using a thermal model is also discussed.

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