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Multi-Objective Optimization of Squeeze Casting Process using Genetic Algorithm and Particle Swarm Optimization

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
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.
Rocznik
Strony
172--186
Opis fizyczny
Bibliogr. 43 poz., il., rys., tab., wykr., wzory
Twórcy
  • Department of Mechanical Engineering, National Institute of Technology Karnataka, Surathkal, India
autor
  • Department of Mechanical Engineering, National Institute of Technology Karnataka, Surathkal, India
  • School of Mechanical Sciences, Indian Institute of Technology, Bhubaneswar, Odisha, India
  • Department of Mechanical Engineering, ChhatrapatiShivaji Institute of Technology, Durg, India
Bibliografia
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  • [21] Vijian, P., Arunachalam, V.P. & Charles, S. (2007). Study of surface roughness in squeeze casting LM6 aluminium alloy using Taguchi method. Indian Journal of Engineering & Materials Sciences. 14, 7-11.
  • [22] Vijian, P. & Arunachalam, V.P. (2007). Modelling and multi objective optimization of LM24 aluminium alloy squeeze cast process parameters using genetic algorithm. Journal of Materials Processing Technology. 186(1), 82-86.
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Uwagi
PL
Opracowane ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-eaa095fe-e8a4-446b-94c1-3926fbf15745
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