MOGA optimisation of wear performance of stir cast AA7050/B4C-T6 ex-situ metal matrix composite Online publication date: Tue, 06-Oct-2020
by Arvind Kumar; Arnab Pal; Ram Naresh Rai
International Journal of Materials and Product Technology (IJMPT), Vol. 60, No. 2/3/4, 2020
Abstract: The present paper aimed to develop the AA7050-xB4C-T6 composite (x = 0, 5, 10 wt. %) through flux assisted stir casting techniques. Further to evaluate the wear performance of the composite in terms of wt. loss and coefficient of friction (COF) by the concurrent effect of process parameters such as wt. % of B4C, normal load, and sliding distance using pin-on-disc tribometer. The experiments were designed based on the full factorial design of the experiment. The results, shows that the normal load has profound influences on the wt. loss, whereas wt. % of B4C have maximum influence on the COF. Sliding distance has a significant influence on both wt. loss and COF. The quadratic regression model developed and the multi-objective genetic algorithm (MOGA) optimisation techniques used to optimise the performance parameters. The % error estimated between optimised and the experimental wt. loss, and COF are 8.13% and 3.58%, respectively. The errors are within the acceptable threshold.
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