Publication Type:

Journal Article

Source:

Journal of Engineering Science and Technology, Taylor's University, Volume 10, Number 3, p.258-268 (2015)

URL:

http://www.scopus.com/inward/record.url?eid=2-s2.0-84923530613&partnerID=40&md5=1aafc1f688c9d4e34606d2543237405a

Abstract:

<p>This paper involves the optimisation of the process parameters for the aluminium/alumina/graphite hybrid metal matrix composite to obtain the least wear rate during dry sliding process. The tribological properties of the composite have been studied and discussed. Experiments were carried out using pin-on-disc tribometer by varying the parameters such as load, velocity, distance &amp; the alumina composition of the composite and the wear rate for each input configuration was calculated. Using this empirical data, the regression equation was obtained using Artificial Neural Networks and this function was then optimised using Genetic Algorithm. The least wear rate was obtained for the composite with an alumina composition of 5 wt% © School of Engineering, Taylor’s University.</p>

Notes:

cited By 0

Cite this Research Publication

N. Radhika, Vijaykarthik, K. T., and Shivaram, P., “Adhesive wear behaviour of aluminium hybrid metal matrix composites using genetic algorithm”, Journal of Engineering Science and Technology, vol. 10, pp. 258-268, 2015.