Title of article :
Investigation and optimization of the effect of input parameters on output parameters of electrical discharge machining of A356 nano-composite reinforced by SiC
Author/Authors :
Rahmani, Amir Department of Mechanical, Civil, and Architectural Engineering - Islamic Azad University Khomeinishahr Branch, Khomeinishahr/Isfahan, Iran , Mokhtarian, Ali Department of Mechanical, Civil, and Architectural Engineering - Islamic Azad University Khomeinishahr Branch, Khomeinishahr/Isfahan, Iran , Rahimi, Mojtaba Department of Mechanical, Civil, and Architectural Engineering - Islamic Azad University Khomeinishahr Branch, Khomeinishahr/Isfahan, Iran
Abstract :
In this study, the impact of input parameters of Electrical Discharge Machining (EDM) on A356 nano-composite reinforced by 6% SiC was investigated and optimized using Taguchi's method based on the L9 orthogonal array and dummy level approach. We considered voltage, current intensity, pulse on-time, and pulse off-time as the input parameters. Furthermore, material removal rate (MRR), tool wear rate (TWR), and surface roughness (SR) were taken into account as the output parameters. The analysis of results and examination of the signal-to-noise graphs (S/N) and analysis of variance (ANOVA) were performed using Minitab@16 software. Moreover, with the determination of the loss function of total normalized values of the output parameters based on assumed weight coefficients, the optimal level of each input parameter was established. Besides, the magnitude of contribution percentage of each of the input parameters in the total variance was computed through the variance analysis. According to the achieved results, the second level of the voltage (250 V), the first level of the current intensity (10 A), the third level of the pulse on-time (100 μs), and the first level of the pulse off-time (30 μs) were determined as the optimal input parameters. The contribution percentage of the input parameters for voltage, current intensity, pulse on-time, and pulse off-time was determined respectively to be 20.7, 62.06, 9.19, and 8.05.
Keywords :
Electrical Discharge Machining (EDM) , Nano-composite , Taguchi method , Variance analysis , Optimization
Journal title :
Journal of Simulation and Analysis of Novel Technologies in Mechanical Engineering