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Abstract

The near net shaped manufacturing ability of squeeze casting process requiresto set the process variable combinations at their optimal

levels to obtain both aesthetic appearance and internal soundness of the cast parts. The aesthetic and internal soundness of cast parts deal

with surface roughness and tensile strength those can readily put the part in service without the requirement of costly secondary

manufacturing processes (like polishing, shot blasting, plating, hear treatment etc.). It is difficult to determine the levels of the process

variable (that is, pressure duration, squeeze pressure, pouring temperature and die temperature) combinations for extreme values of the

responses (that is, surface roughness, yield strength and ultimate tensile strength) due to conflicting requirements. In the present

manuscript, three population based search and optimization methods, namely genetic algorithm (GA), particle swarm optimization (PSO)

and multi-objective particle swarm optimization based on crowding distance (MOPSO-CD) methods have been used to optimize multiple

outputs simultaneously. Further, validation test has been conducted for the optimal casting conditions suggested by GA, PSO and

MOPSO-CD. The results showed that PSO outperformed GA with regard to computation time.

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Authors and Affiliations

G.C.M. Patel
P. Krishna
P.R. Vundavilli
M.B. Parappagoudar

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