Parametric optimisation of high speed turning operation of hybrid aluminium composites using Taguchi-based grey relational analysis
by A. Thirumoorthy; T.V. Arjunan; M. Arulraj; R. Kumaravelan; T.C.R. Dinesh
International Journal of Computational Materials Science and Surface Engineering (IJCMSSE), Vol. 9, No. 4, 2020

Abstract: In the field of metal matrix composites (MMCs), most of researches are being carried out with carbide, alumina and boride as reinforcement. Nitrides and oxides are also suitable candidates to be used as reinforcement. There is a huge scope to study the effect of nitride and oxide on the mechanical and machining behaviour of composite materials. Therefore, this paper has set the primary objective of developing the hybrid aluminium-based composite and studying the hardness and machining behaviour of high hardness hybrid composite of MMCs by reinforcing with nitride and oxide. The composition chosen are the first sample composition with 6% of silicon nitride (Si₃N₄) and 3% of magnesium oxide and another with 3% Si₃N₄ and 3% MgO. Al6061 matrix with blended magnesium oxide and silicon nitride is produced using stir casting process. Computer numerical control (CNC) turning operation has been carried out on the composite developed. The main responses considered in this study are surface roughness (SR) and material removal rate (MRR) and machining parameters such as feed rate, depth of cut and cutting speed, are chosen. Among these, feed and depth of cut are most influencing factor for the machining of hybrid composites.

Online publication date: Mon, 01-Feb-2021

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