Influence of Energy Parameters on Plasma Radius, Energy Fraction and Plasma Flushing Efficiency for a Single Discharge in EDM

An electrical discharge forms a crater on the workpiece surface. The crater morphology estimates the performance parameters of the electrical discharge machining process. The energy parameters (gap voltage, discharge current and the pulse on time), the plasma channel radius and the energy fraction coming to the workpiece determine the molten cavity radius and depth. The plasma flushes away a portion of material from the molten cavity forming a crater and resolidification of the remaining molten material forms a recast layer. The plasma flushing efficiency determines the crater’s radius and depth. Few researchers have successfully expressed the plasma radius, energy fraction and plasma flushing efficiency in relation to two of the energy parameters, namely, discharge current and pulse on time but not as a gap voltage function. This work attempted to develop a thermo-physical model to express plasma radius, energy fraction and plasma flushing efficiency as a function of all three energy parameters, such as gap voltage, discharge current and pulse on time. Plasma flushing efficiency was calculated and plasma radius and energy fraction were estimated by inverse finite element method from the measured values of crater radius, crater depth and recast layer thickness. The expressions for plasma radius, energy fraction and plasma flushing efficiency were found out from the regression equations obtained from the designed data set using the Taguchi method. Validation shows that the modeled and experimental values of crater radius, crater depth, and recast layer thickness agree well.

A study on Electrical Discharge Machining of Titanium Grade2 with experimental and theoretical analysis

Titanium alloys, due to their unique properties, are utilized in numerous modern high-end applications. Electrical Discharge Machining (EDM) is a non-conventional machining process, commonly used in machining of hard-to-cut materials. The current paper, presents an experimental study regarding the machining of Titanium Grade2 with EDM, coupled with the development of a simulation model. The machining performance indexes of Material Removal Rate, Tool Wear Ratio, and Average White Layer Thickness were measured and calculated for different pulse-on currents and pulse-on times. Moreover, the developed model that integrates a heat transfer analysis with deformed geometry, allows to estimate the power distribution between the electrode and the workpiece, as well as the Plasma Flushing Efficiency, giving an insight view of the process. Finally, by employing the Response Surface Methodology, educed regression models that correlate the machining parameters with the corresponding results, while for all the aforementioned indexes, ANOVA was performed.

Multi-optimization of process parameters for machining of a non-conductive SiC ceramic composite by non-conventional machining method

The objective of the study is to predict the optimized set of the input parameters for the machining of non-conductive silicon carbide (SiC) by electric discharge machining (EDM). The insulated SiC ceramic composite machining was performed with 4 volumes (by percentage) of carbon nano (CNT) the SiC, which makes it electrically conductive. SiC has very good mechanical properties due to its widespread application in the aerospace, MEMS, and bio-sensor industries. This application requires a highly precise machining hole with a good surface quality that can be processed by machining processes such as EDM. The input parameters in this study are differing by three levels and the experimentation has been done by L27 orthogonal array. Four output parameters such as material removal rate (MRR), plasma flushing efficiency (PFE), surface-roughness (SR) and recast layer thickness (Rlt) for has been calculated for the detailed experimental analyses. In this research, a comparative analysis between the Multi-attribute management mechanisms (MADM) i.e. WPCA, MOORA & MOORA, and WPCA was conducted. The statistical analysis was also conducted to determine the impact of input parameters on performance measures. The study concluded that by integrating MOORA 's method with a PCA, the highest MRRs of 2.56 mm3/min & 78% PFE, lowest SR 2.1 µm, and Rlt 2.56 µm were obtained, with an experimental testing error of 5 percent.

Tool wear estimating model considering modeling improvement factors in electrical discharge machining process based on physical properties of tool electrodes

A comprehensive numerical model is introduced in this article for estimating the tool wear based on finite element model and inverse heat conduction techniques considering the interactive and direct effects of the experimental factors of recast layer thickness, anode energy fraction and plasma flushing efficiency. The individual and interactive effects of the major thermo-physical and electro-physical parameters have been modeled to improve the introduced tool wear estimation procedure. Comparison of the numerical results with the experimental observations indicated that the developed finite element model and inverse heat conduction process was capable of predicting the tool wear with high accuracy. Additionally, application of analysis of variance technique showed that the introduced mathematical models for estimating anode energy fraction, plasma flushing efficiency and recast layer thickness are statistically significant and adequate which means that the proposed equations can be used for a variety of physical, electrical and thermal variables’ combinations.

Electro-Thermal Modelling for Material Removal Study in Electric Discharge Machining Process

In the present study, an attempt has been made to model the electric discharge machining process using the numerical simulation technique. Realistic parameters are added in the model such as variable fraction of heat going to the electrodes, and variation in the plasma flushing efficiency with the process parameters. Gaussian distributed heat flux is applied at the spark location and the two-dimensional heat conduction equation is solved with the help of finite element analysis technique to determine the temperature distribution within the two-dimensional process continuum, using averaged thermo-physical properties of the work material. Melting isotherms are determined and the material removed during a single discharge is obtained from it. Material removal rate is determined using a regression model for the plasma flushing efficiency. Experimental validation is made with the help of highly precise AGIE SIT experimental data. The material removal rate is also compared with state of the art research of other researchers. It has been observed that, at low value of the discharge energies, the proposed model is able to predict the experimental material removal rate better than that of the model proposed by other researchers. However, as the discharge energy increases, the accuracy of prediction decreases. The model can be used for achieving process parameter optimization hence saving both the costs and large lead times associated with determining optimized parameters experimentally.