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Artificial Neural Network Prediction of Aluminium Metal Matrix Composite with Silicon Carbide Particles Developed Using Stir Casting Method

Babalola, P.O. and Bolu, Christian and Inegbenebor, A.O. (2015) Artificial Neural Network Prediction of Aluminium Metal Matrix Composite with Silicon Carbide Particles Developed Using Stir Casting Method. International Journal of Mechanical & Mechatronics Engineering, 15 (2).

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Abstract

Aluminium matrix composites (AMCs) are range of advanced engineering materials used for a wide range of applications. AMCs consist of a non-metallic reinforcement incorporated into Aluminium matrix providing advantageous properties over base metal alloys. In this paper, artificial neural network (ANN) is used to predict the micro-hardness, yield strength, tensile extension, modulus, ultimate tensile strength and stress, time to fracture, load at maximum extension, tenacity, electrical resistivity and conductivity. Information obtained from ANN model predictions can be used as guidelines during the conceptual design and optimisation of manufacturing processes; thus, reducing time and costs.

Item Type: Article
Uncontrolled Keywords: Artificial Neural Network Aluminium Matrix Composites Modelling Mechanical Properties
Subjects: T Technology > TJ Mechanical engineering and machinery
Divisions: Faculty of Engineering, Science and Mathematics > School of Engineering Sciences
Depositing User: Mrs Patricia Nwokealisi
Date Deposited: 16 Nov 2015 15:23
Last Modified: 16 Nov 2015 15:23
URI: http://eprints.covenantuniversity.edu.ng/id/eprint/5650

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