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The current investigation aims to predict the dry sliding wear performance of AA7075-TiO 2  metal matrix composites via Taguchi based grey relational analysis. The AA7075-TiO 2  composites were produced by x wt%. of TiO 2  particles (X = 0, 5, 10 and 15 wt.%) through stir casting route. The SEM micrographs evident the TiO 2  reinforcement particles were homogeneously distributed in to the AA7075 matrix. To measure the frictional force and the mass loss of the produced composites under dry sliding conditions of pin-on-disc instrument was utilised. The experimental works were performed to as per Taguchi’s L16 orthogonal array utilising four process parameters namely reinforcement (wt.%), applied load (N), sliding velocity (m/s) and sliding distance (m). Main effect plot and analysis of variance (ANOVA) was used to determine the effect of each parameter on the wear rate and coefficient of friction (COF). From the investigations the results found that, the reinforcement weight percentage has to be more significant factor on the wear rate and COF subsequently applied load. A confirmation experiment was also conducted to confirm the prediction of the results attained by the optimum parameter combination. Finally, the SEM micrograph was used to examine the worn out surface of the composites.

Multi-objective optimisation of dry sliding wear control parameters for stir casted AA7075- TiO 2 composites using Taguchi-Grey relational approach