Modelling and multi objective optimization of LM13 aluminium alloy squeeze cast process parameters using taguchi and genetic algorithm
S. Vellingiri
; Department of Mechanical Engineering, Coimbatore Institute of Technology, India
V. Senthil
; Department of Mechanical Engineering, Coimbatore Institute of Technology, India
N. Zeelanbasha
orcid.org/0000-0002-2706-8860
; Department of Mechanical Engineering, Coimbatore Institute of Technology, India
APA 6th Edition Vellingiri, S., Senthil, V. i Zeelanbasha, N. (2018). Modelling and multi objective optimization of LM13 aluminium alloy squeeze cast process parameters using taguchi and genetic algorithm. Metalurgija, 57 (1-2), 55-58. Preuzeto s https://hrcak.srce.hr/189363
MLA 8th Edition Vellingiri, S., et al. "Modelling and multi objective optimization of LM13 aluminium alloy squeeze cast process parameters using taguchi and genetic algorithm." Metalurgija, vol. 57, br. 1-2, 2018, str. 55-58. https://hrcak.srce.hr/189363. Citirano 05.12.2019.
Chicago 17th Edition Vellingiri, S., V. Senthil i N. Zeelanbasha. "Modelling and multi objective optimization of LM13 aluminium alloy squeeze cast process parameters using taguchi and genetic algorithm." Metalurgija 57, br. 1-2 (2018): 55-58. https://hrcak.srce.hr/189363
Harvard Vellingiri, S., Senthil, V., i Zeelanbasha, N. (2018). 'Modelling and multi objective optimization of LM13 aluminium alloy squeeze cast process parameters using taguchi and genetic algorithm', Metalurgija, 57(1-2), str. 55-58. Preuzeto s: https://hrcak.srce.hr/189363 (Datum pristupa: 05.12.2019.)
Vancouver Vellingiri S, Senthil V, Zeelanbasha N. Modelling and multi objective optimization of LM13 aluminium alloy squeeze cast process parameters using taguchi and genetic algorithm. Metalurgija [Internet]. 2018 [pristupljeno 05.12.2019.];57(1-2):55-58. Dostupno na: https://hrcak.srce.hr/189363
IEEE S. Vellingiri, V. Senthil i N. Zeelanbasha, "Modelling and multi objective optimization of LM13 aluminium alloy squeeze cast process parameters using taguchi and genetic algorithm", Metalurgija, vol.57, br. 1-2, str. 55-58, 2018. [Online]. Dostupno na: https://hrcak.srce.hr/189363. [Citirano: 05.12.2019.]
Sažetak This present investigation deals with squeeze casting process in order to produce a component with good mechanical properties such as micro-hardness(VH), tensile strength(Rm), and density(ρ) on LM13 by varying squeeze pressure(P), molten temperature(Tm) and die temperature(Td). Taguchi experimental design L9 orthogonal array was used to determine the signal to noise ratio. The results specified that the squeeze pressure and die preheat temperature are the most influencing parameters for mechanical properties improvement. Genetic algorithm (GA) has been applied to optimize the casting parameters that simultaneously maximize the responses.