Improvement of ductility for squeeze cast 2017 A wrought aluminum alloy using the Taguchi method

Abstract

In this paper, the influence of process parameters on the ductility during squeeze casting of 2017 A wrought aluminum alloy is studied. The Taguchi method of design of experiments was employed to optimize the process parameters and to increase the elongation percent. A 3-factor, 3-level casting experiment is conducted by Taguchi L 9 orthogonal array through the statistical design method. Then, the input parameters are considered here including squeeze pressure, melt temperature, and die preheating temperature with three levels. The optimum casting parameters to acquire higher ductility were predicted, and the individual importance of each parameter was evaluated by examining the signal-to-noise (S/N) ratio and analysis of variance (ANOVA) results. The optimum levels of the squeeze pressure, melt temperature, and die preheating temperature were found to be 90 MPa, 700, and 200°C, respectively. The ANOVA results indicated that the squeeze pressure has the higher statistical effect on the elongation percent, followed by the melt temperature and die preheating temperature. Optical microscopy and scanning electron microscopy (SEM) analysis were used to discuss the effect of pressure levels on the microstructure and the fracture characterization of the investigated alloy.

Effect of Si on Fe-rich intermetallic formation and mechanical properties of heat-treated Al–Cu–Mn–Fe alloys

“…The optimum squeeze casting parameter 2017A wrought Al alloys were revealed: squeeze pressure equal to 90 MPa, melt temperature equal to 700 °C, and die preheating temperature equal to 200 °C [29] . The semisolid slurry of wrought 5052Al alloy and AlCu5MnTi alloy were prepared by the indirect ultrasonic vibration, and then shaped by direct squeeze casting [30,31].…”

Process Parameter Optimization in TIG Welding of AISI 4340 Low Alloy Steel Welds by Genetic Algorithm

“…In addition, the percentage contribution (P) indicates the significance of process factors for the response. For a factor with a high values of P, a small variation will have a great influence on the performance (10). The graphical representation of percentage contribution is presented in Figure 4, it observed that, current (A) was found to be a major factor affecting the welding process significantly the mean average of UTS of 38.64%.…”

Teaching learning based optimization of squeeze casting process for quality castings

“…The Statistical Taguchi method is applied to model and optimize the squeeze casting parameters (that is, applied pressure, die and pouring temperature) for higher hardness, and UTS [10], and density, and SR [11] and ductility [12]. Taguchi method applied to optimize the parameters (die materialstainless steel, brass, SG iron, and copper, die temperature, pouring temperature, squeeze pressure) for enhanced wear resistance of AC2A alloy [13].…”