open access

Optimization of machining parameters in EDM of Al7075-SiC-Al2O3 using taguchi method

  • P.V.M. Kathiresh Assistant Professor, Department of Mechanical Engineering, Velammal Institute of Technology, Chennai-601204.
  • K SivaKumar Associate Professor, Department of Mechanical Engineering, Velammal Institute of Technology, Chennai-601204
  • S Dineshkumar UG Department of Mechanical Engineering, Velammal Institute of Technology, Thiruvallur.
  • S Sundar UG Department of Mechanical Engineering, Velammal Institute of Technology, Thiruvallur
  • N Vinothbabu UG Department of Mechanical Engineering, Velammal Institute of Technology, Thiruvallur.
  • K Surya UG Department of Mechanical Engineering, Velammal Institute of Technology, Thiruvallur.

Abstract

 


The newly engineered hybrid metal matrix composite of aluminium 7075 reinforced with silicon carbide (SiC) and aluminium oxide (Al2O3) prepared by stir casting. Optimization is one of the techniques used in manufacturing sectors to arrive for the best manufacturing conditions, which is an essential need for industries towards manufacturing of quality products at lower cost. This paper aims to investigate the optimal set of machining parameters such as current, pulse ON, pulse OFF time and gap control in Electrical Discharge Machining (EDM) process to identify the variations in three performance characteristics such as rate of material removal, wear rate on tool, and surface roughness value on the work material . Based on the experiments were  conducted on L9 orthogonal array, analysis has been carried out using Grey Relational Analysis, a Taguchi method. . Signal to noise ratio (S/N) and analysis of variance (ANOVA) is used to analyze the effect of the parameters on MRR and also to identify the optimum machining parameters. Thus, the machining parameters for EDM were optimized for achieving the combined objectives of higher rate of material removal, lower wear rate on tool, and lower surface roughness value on the work material considered in this work.

Downloads

Download data is not yet available.

Most read articles by the same author(s)