Application of artificial neural network in predicting the wear rate of copper surface composites produced using friction stir processing

ABSTRACT

The application of artificial neural network (ANN) to predict the wear rate of the surface composites produced using a solid-state technique called friction stir processing (FSP) is presented in this work. The copper surface composites were prepared by incorporating different sort of ceramic particles such as SiC, TiC, Al₂O₃, WC and B₄C. The design of experiments (DOE) strategy was utilised to direct the experimental work. The considered operating parameters were sort of ceramic particle, traverse speed, tool rotational speed and groove width, whereas wear rate is the response. An approximation mechanism having an arbitrary function, the ANN was consequently used for simulating the wear rate of the surface composites. The feedforward back propagation technique was employed to alter the weights of the network to minimise the mean squared error for the development of ANN models. The predicted trends were explained and studied the influence of the considered factors with the aid of observed micro structures. The lower wear rate was observed with B₄C-reinforced surface composites.

KEYWORDS:

• Copper matrix composites
• friction stir processing
• wear rate
• artificial neural network
• microstructure

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

I. Dinaharan

I. Dinaharan received his doctoral degree from Anna University, Chennai, India. He is presently doing postdoctoral research at Tsinghua University, China. His research interest includes metal matrix composite, stir casting, friction stir welding, friction stir processing and laser beam welding. He has authored more than 100 technical articles in peer reviewed international journals.

R. Palanivel

R. Palanivel received his doctoral degree from Anna University, Chennai, India. He is presently working as Assistant Professor at Shaqra University, Saudi Arabia. His research interest includes friction stir welding, friction stir processing, laser beam welding and metal matrix composites. He has authored more than 25 technical articles in peer reviewed international journals.

N. Murugan

N. Murugan received his doctorate degree from Indian Institute of Technology, Delhi, India. His research interest includes metal matrix composite, casting, fusion and solid state welding. He has published more than three hundred papers in various international journals and international conferences. Presently, he is working as professor of mechanical engineering in PSG college of Institute of Technology.

R. F. Laubscher

R. F. Laubscher received his doctorate degree from University of Johannesburg (formerly Rand Afrikaans University). His research interest includes machining of high strength materials, solid state welding and physical metallurgy. He has published more than seventy papers in various international journals and international conferences. Presently, he is working as Associate Professor of mechanical engineering in University of Johannesburg.