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Original scientific paper

Modeling and experimental investigation of LM26 pressure die cast process parameters using multi objective genetic algorithm (MOGA)

N. Zeelanbasha ; Department of Mechanical Engineering, Coimbatore Institute of Technology, India
V. Senthil ; Department of Mechanical Engineering, Coimbatore Institute of Technology, India
B. Sharon Sylvester ; Department of Mechanical Engineering, Info Institute of Engineering, India
N. Balamurugan ; Department of Mechanical Engineering, Kumaraguru College of Technology, India

Fulltext: english, pdf (304 KB) pages 307-310 downloads: 323* cite
APA 6th Edition
Zeelanbasha, N., Senthil, V., Sharon Sylvester, B. & Balamurugan, N. (2017). Modeling and experimental investigation of LM26 pressure die cast process parameters using multi objective genetic algorithm (MOGA). Metalurgija, 56 (3-4), 307-310. Retrieved from https://hrcak.srce.hr/180969
MLA 8th Edition
Zeelanbasha, N., et al. "Modeling and experimental investigation of LM26 pressure die cast process parameters using multi objective genetic algorithm (MOGA)." Metalurgija, vol. 56, no. 3-4, 2017, pp. 307-310. https://hrcak.srce.hr/180969. Accessed 19 Feb. 2020.
Chicago 17th Edition
Zeelanbasha, N., V. Senthil, B. Sharon Sylvester and N. Balamurugan. "Modeling and experimental investigation of LM26 pressure die cast process parameters using multi objective genetic algorithm (MOGA)." Metalurgija 56, no. 3-4 (2017): 307-310. https://hrcak.srce.hr/180969
Harvard
Zeelanbasha, N., et al. (2017). 'Modeling and experimental investigation of LM26 pressure die cast process parameters using multi objective genetic algorithm (MOGA)', Metalurgija, 56(3-4), pp. 307-310. Available at: https://hrcak.srce.hr/180969 (Accessed 19 February 2020)
Vancouver
Zeelanbasha N, Senthil V, Sharon Sylvester B, Balamurugan N. Modeling and experimental investigation of LM26 pressure die cast process parameters using multi objective genetic algorithm (MOGA). Metalurgija [Internet]. 2017 [cited 2020 February 19];56(3-4):307-310. Available from: https://hrcak.srce.hr/180969
IEEE
N. Zeelanbasha, V. Senthil, B. Sharon Sylvester and N. Balamurugan, "Modeling and experimental investigation of LM26 pressure die cast process parameters using multi objective genetic algorithm (MOGA)", Metalurgija, vol.56, no. 3-4, pp. 307-310, 2017. [Online]. Available: https://hrcak.srce.hr/180969. [Accessed: 19 February 2020]

Abstracts
This present investigation deals with pressure die casting process to produce an automotive valve closer component with better mechanical properties such as micro-hardness(HV), surface roughness (μm) and porosity (%) on LM26 by varying intensification pressure (α) Kgf/cm2, shot velocity (β) m/s and pouring temperature (γ) °C. Using response surface methodology (RSM), the optimal parametric combination is found to be α (186,68) Kgf/cm2, β (0,599) m/s and γ (662,93) °C for multi responses (121,18) HV, (0,93) μm and 0,017 % can be achieved corresponding to highest desirability of 0,73. The optimized results were obtained by the Pareto-optimal solutions using multi objective genetic algorithm (MOGA) provides flexibility to select the best setting depending on suitable applications.

Keywords
aluminium alloy; casting die, properties; mathematical model

Hrčak ID: 180969

URI
https://hrcak.srce.hr/180969

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