Title: An experimental design and theoretical analysis of squeeze casting parameters for 2017A aluminium alloy

Authors: Najib Souissi; Slim Souissi; Christophe Le Niniven; Mohamed Ben Amar; Chedly Bradai; Foued Halouani

Addresses: National Engineering School of Sfax, University of Sfax, Tunisia, (ENIS) B.P 599-3038, Tunisia ' National Engineering School of Sfax, University of Sfax, Tunisia, (ENIS) B.P 599-3038, Tunisia ' SPCTS, University of Limoges, UMR CNRS 7315, F-87068 Limoges, France ' National Engineering School of Sfax, University of Sfax, Tunisia, (ENIS) B.P 599-3038, Tunisia ' National Engineering School of Sfax, University of Sfax, Tunisia, (ENIS) B.P 599-3038, Tunisia ' National Engineering School of Sfax, University of Sfax, Tunisia, (ENIS) B.P 599-3038, Tunisia

Abstract: In this paper, the Taguchi method has been applied to evaluate the yield strength, ultimate tensile strength and microhardness tests of 2017 A aluminium alloy produced by direct squeeze casting. The control factors such as, the squeeze pressure, melt temperature and die preheating temperature, were selected as squeeze casting parameters. The optimum casting parameters for the mechanical properties were predicted, and the individual importance of each parameter on the response characteristic was evaluated by examining the signal-to-noise (S/N) ratio and analysis of variance (ANOVA) results. The statistical results revealed that the squeeze pressure has the higher effect on the mechanical properties, followed by the melt temperature. In addition, the empirical equations were applied to predict the outcomes of the experiment. The predicted values and measured values were very close to each other. Confirmation test results showed that the Taguchi method was very successful.

Keywords: Taguchi methods; squeeze casting parameters; 2017A aluminium alloys; mechanical properties; experimental design; yield strength; tensile strength; microhardness; squeeze pressure; melt temperature; die preheating temperature; signal to noise ratio; SNR; ANOVA.

DOI: 10.1504/IJMATEI.2015.069801

International Journal of Materials Engineering Innovation, 2015 Vol.6 No.1, pp.59 - 73

Received: 23 Dec 2013
Accepted: 20 Oct 2014
Published online: 12 Jun 2015 *

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