Title of article :
Parametric optimization of nano powder blended electrical spark machining process on AISI D3 DIE steel employing grey relational analysis
Author/Authors :
santarao, k. gmr institute of technology(gmrit) - dept. of mechanical engineering, Rajam, India , prasad, c. l. v. r. s. v. gmr institute of technology(gmrit) - dept. of mechanical engineering, Rajam, India , swaminaidu, g. jawaharlal nehru technological university, kakinada(jntuk), vizianagaram campus - dept. of metallurgical engineering, India
Abstract :
The main objective of this research paper is to present the results of multi response optimization performed for nano powder blended electrical spark machining operations on AISI D3 Die steel based on Taguchi method coupled with grey relational analysis. Different sets of experiments planned as per Taguchi technique were carried out by varying four parameters such as peak current, pulse-on time, spark voltage and powder concentration. Material removal rate(MRR), electrode wear rate (EWR) and surface roughness (SR) are selected as output parameters for this research. Results showed that powder concentration and peak current were the influencing parameters on MRR, EWR, and SR as per Grey relational grade. The optimal combination parameters were identified as peak current at 7 A, pulse on-time at 50μs, gap voltage at 100 V and powder concentration at 0.5g/L. The confirmation test performed to validate the result obtained by grey relational analysis revealed a satisfactory enhancement in the response.
Keywords :
Grey relational analysis , Material Removal Rate , Surface Roughness , Electrode wear rate , Taguchi Method
Journal title :
Journal of Materials and Environmental Science
Journal title :
Journal of Materials and Environmental Science
