Experimental study of distribution of energy during EDM process for utilization in thermal models

Singh, Harminder

doi:10.1016/j.ijheatmasstransfer.2012.05.004

Cited by 127 publications

(59 citation statements)

References 31 publications

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“…Shabgard et al [19] presented that the fraction of heat going into the cathode was a function of pulse current and pulse duration. Harminder [24,25] performed an experiment to study the fraction of energy transferred to the workpiece utilizing heat transfer equations. And it is clearly shown that energy distribution varies with variation of either pulse duration or pulse current.…”

Section: Femmentioning

confidence: 99%

“…Joshi and Pande [17] introduced three energy zones, and each zone has a different distribution factor. Harminder [24,25] performed an experiment to study the fraction of energy transferred to the workpiece. In order to increase the accuracy of the theoretical thermal models used for the prediction of machining characteristics (MRR, Ra), value of f c needs to be varied with variation of input parameters (I, T on ).…”

Section: Heat Distributionmentioning

confidence: 99%

“…In this present work, the experimental results obtained by Harminder [24] are used to model the correlation between f c and I and T on . Considering the difference of machining conditions, discharge voltage, and work-tool materials, especially the thermal conductivity of AISI W1 (K t = 48 Wm −1 K −1 ) is smaller than Tungsten-Carbide (K t = 84.02 Wm −1 K −1 ) [24], the proportionality coefficient K p which equal to 0.833 is simply assumed.…”

Section: Heat Distributionmentioning

confidence: 99%

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A hybrid process model for EDM based on finite-element method and Gaussian process regression

Ming

Zhang

et al. 2014

Int J Adv Manuf Technol

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This paper proposed a hybrid intelligent process model, based on finite-element method (FEM) and Gaussian process regression (GPR), for electrical discharge machining (EDM) process. A model of single-spark EDM process has been constructed based on FEM method, considering the latent heat, variable heat distribution coefficient of cathode (f c ), and plasma flushing efficiency (PFE), to predict material removal rate (MRR) and surface roughness (Ra). This model was validated using reported analytical and experimental results. Then, a GPR model was proposed to establish relationship between input process parameters (pulse current, pulse duration, and discharge voltage) and the process responses (MRR and Ra) for EDM process. The GPR model was trained, tested, and tuned using the

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Section: Femmentioning

confidence: 99%

Section: Heat Distributionmentioning

confidence: 99%

Section: Heat Distributionmentioning

confidence: 99%

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A hybrid process model for EDM based on finite-element method and Gaussian process regression

Ming

Zhang

et al. 2014

Int J Adv Manuf Technol

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“…This undesirable effect is described in detail by Shahane and Kapoor [11,12], and the solution of this problem is considered to be the application of a low-temperature machining mode with cooling of a dielectric fluid. In this context, Singh stresses the need to take account of the heat load at the point of electric discharge by a suitable choice of working gap flushing intensity [13]. This is decisive for the application of full cuts of large cross-sections where the thermal energy accumulates at the point of electric discharge, i.e., in working gap.…”

Section: Introductionmentioning

confidence: 99%

Prediction of the Geometrical Accuracy of the Machined Surface of the Tool Steel EN X30WCrV9-3 after Electrical Discharge Machining with CuZn37 Wire Electrode

Straka

Čorný

Piteľ

2017

Metals

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Abstract:The geometrical accuracy of the machined surface can generally be understood mainly as accuracy of shape, orientation, position and run-out. As a general rule; it is quantified by the corresponding deviations from the nominal area. The size of the geometric deviation from the nominal area may in practice affect the conventionally measured value of the dimension, even if the required dimensional tolerance is adhered to. Since electro-erosive machining technology belongs to very precise finishing technologies; even the small geometrical accuracy deviation has a negative impact on the resulting quality of machined surfaces. The aim of the experiments was to contribute to the knowledge database, which defines the influence of the process parameters at electrical discharge machining with the CuZn37 tool electrode on errors of geometrical accuracy of the machined surface. On the basis of the results of the experimental measurements, graphical dependencies were determined which predict geometrical accuracy of the machined surface in terms of the maximum deviation of flatness after electrical discharge machining of tool steel EN X30WCrV9-3 (W.-Nr. 1.2581) with CuZn37 wire electrode of 0.20 mm diameter to determine the appropriate combination of process parameters.

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“…Energy distribution factor  is another important factor in the model, governing the percentage of the total heat input from the plasma discharge channel. The different values of energy distribution factor were proposed by many researchers [2,5,7,11], ranging from 0.18-0.45. Comparing the experimental and analytical results, the constant value of  (0.3) has been adopted to estimate the temperature distribution in the model.…”

Section: Figure 1 An Axisymmetric Thermal Model For the Edm Processmentioning

confidence: 99%

Effect of Discharge Location on Temperature Distribution during Electrical Discharge Machining

Xie¹,

Zhang²,

Zhang³

et al. 2015

IJSEIA

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Experimental study of distribution of energy during EDM process for utilization in thermal models

Cited by 127 publications

References 31 publications

A hybrid process model for EDM based on finite-element method and Gaussian process regression

A hybrid process model for EDM based on finite-element method and Gaussian process regression

Prediction of the Geometrical Accuracy of the Machined Surface of the Tool Steel EN X30WCrV9-3 after Electrical Discharge Machining with CuZn37 Wire Electrode

Effect of Discharge Location on Temperature Distribution during Electrical Discharge Machining

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