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1 Archives of Computational Materials Science and Surface Engineering

1 2009

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Particle Swarm Optimisation of hardness in nickel diamond electro composites

Ramanathan K., Periasamy V.M., Pushpavanam M., Natarajan U.

Archives of Computational Materials Science and Surface Engineering

2009

Vol. 1, nr 4

232-236

Purpose: This paper presents an efficient and reliable swarm intelligence-based approach, namely particle swarm optimization (PSO) technique, to optimize the hardness and the parameters that affect the hardness in the Ni-Diamond composite coatings. Design/methodology/approach: Particle swarm optimizers 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 . Findings: 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 optimizing hardness and their influencing parameters. The optimized hardness of Ni-diamond metal matrix was found to be 431VHN at pH = 2.5, Current density = 1 A/dm2 and temperature = 300°C. Research limitations/implications: The key advantage of PSO is its computational efficiency and less parameter required to be adjusted in order to get the optimum result compared to related techniques. A non linear regression model was developed for the unconstrained optimization of hardness in Ni-diamond composite coated metal matrix using experimental data and it was used as objective function in the maximization problem. Originality/value: The proposed approach utilizes the global exploration capabilities of PSO to search for the optimal solution.