Search

The present research was focussed to investigate the influence of liquid-gaseous dielectric on debris formation in magnetic field-assisted electrical discharge machining. The air and argon gas were used to make two-phase dielectric fluids such as liquid-air and liquid-argon gas, respectively. Experimentation was conducted to compare the effect of different liquid-gaseous dielectric environments on debris formation. The morphology and diameter distribution of debris were analyzed. In addition, the effect on elemental analysis, phase transformation and magnetic property of debris was investigated. The experimental results showed the exothermic reaction due to air from liquid–air dielectric, and inert property of argon gas from liquid-gaseous dielectric affected the formation of debris. The XRD results confirmed the formation of oxides in the debris produced using liquid-air mixed dielectric. The oxide-free debris formed while using the argon gas. Low saturation of magnetization was found in the debris, formed in the liquid–air dielectric which showed the weak attraction toward magnet when compared with that in the liquid–argon gas mixed dielectric. [ABSTRACT FROM AUTHOR]

Electrical discharge machining is an alternative process for machining complex and intricate shapes. In this paper, an inter-relationship of various electrical discharge machining parameters, namely discharge current, pulse on and off time and dielectric flow rate on material removal rate (MRR), tool wear rate (TWR), surface finish (a) and dimensional tolerance using a Taguchi-Grey relational analysis. The response surface methodology is used to develop a second order model for MRR, TWR and a in terms of process parameters. Finally, a multi-objective optimization problem is formulated by using MRR, TWR and a. The multi-objective problem is then optimized through a modified particle swarm optimization (PSO) algorithm to find the optimum level of parameters. In this research, the results of the proposed method are validated through confirmation experiment. The work piece material used for experimentation is stainless steel of S304 grade. [ABSTRACT FROM AUTHOR]

In the present work, an investigation has been made into the electrical discharge machining process during machining of precipitation hardening stainless steel PH17-4. Taguchi method is used to formulate the experimental layout, to analyze the effect of each process parameter on machining characteristics and to predict the optimal choice for each electrical discharge machining process parameters namely, peak current, pulse on time and pulse off time that give up optimal process performance characteristics such as material removal rate, surface roughness, tool wear rate and surface hardness. To identify the significance of parameters on measured response, the analysis of variance has been done. It is found that parameters peak current and pulse on time have the significant affect on material removal rate, surface roughness, tool wear rate and surface hardness. However, parameter pulse off time has significant affect on material removal rate. Confirmation tests are conducted at their respective optimum parametric settings to verify the predicted optimal values of performance characteristics. [ABSTRACT FROM AUTHOR]

The energy distribution in the electric discharge machining process influences the material removal rate, relative wear ratio and the surface roughness of the machined surface and the effective energy is the part of energy which is distributed toward workpiece to be machined. The theoretical modeling of the process is based upon the heat transfer equations and one of the important parameter is fraction of energy transferred to the workpiece. The model first calculates the temperature distribution in the workpiece material using ANSYS Finite element coding and then volume removed due to single spark is estimated from the temperature profiles. Theoretical material removal rate at different input parameters are compared with the experimental results, making it possible to determine the portion of energy that enters AISI H13 tool steel workpiece. The effect of input parameters (discharge current, voltage, pulse on time) on temperature distributions along the radius and depth of the workpiece has been reported. [ABSTRACT FROM AUTHOR]