Maximising hardness of nickel-diamond composite metal matrix using PSO
by K. Ramanathan, U. Natarajan, V.M. Periasamy, Malathy Pushpavanam
International Journal of Computational Materials Science and Surface Engineering (IJCMSSE), Vol. 3, No. 4, 2010

Abstract: This paper presents an efficient and reliable swarm intelligence-based approach, namely particle swarm optimisation (PSO) technique, to optimise the hardness and the parameters that affect the hardness in the Ni-Diamond composite coatings. Particle swarm optimisers are inherently distributed algorithms, in which the solution for a problem emerges from the interactions between many simple individuals called particles. Nickel-diamond composite coatings are produced by electro deposition using sedimentation technique on mild steel substrate at various cathode current densities, pH and temperatures. Electro deposition was carried out from a conventional Watts bath. Natural diamond powder of 6-12 μm size was used in the study. The hardness value of composite coated specimens were measured using Vickers micro indentation technique. Non-linear regression model was developed using experimental data and was used as an objective function for optimising hardness and their influencing parameters. The optimised hardness of Ni-diamond metal matrix was found to be 455 VHN at pH = 3.37, Current density = 1.86 A/dm² and temperature = 30°C.

Online publication date: Sun, 31-Oct-2010

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computational Materials Science and Surface Engineering (IJCMSSE):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email