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Using multiobjective evolutionary algorithms in the optimization of operating conditions of polymer injection molding
Author(s) -
Fernandes C.,
Pontes A.J.,
Viana J.C.,
GasparCunha A.
Publication year - 2010
Publication title -
polymer engineering and science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.503
H-Index - 111
eISSN - 1548-2634
pISSN - 0032-3888
DOI - 10.1002/pen.21652
Subject(s) - molding (decorative) , materials science , multi objective optimization , process (computing) , genetic algorithm , shrinkage , pareto principle , set (abstract data type) , work (physics) , process optimization , mathematical optimization , computer science , algorithm , mechanical engineering , process engineering , mathematics , composite material , engineering , chemical engineering , programming language , operating system
A Multiobjective Optimization Genetic Algorithm, denoted as Reduced Pareto Set Genetic Algorithm with Elitism (RPSGAe), has been applied to the optimization of the polymer injection molding process. The aim is to implement an automatic optimization scheme capable of defining the values of important process operating conditions (such as melt and mould temperatures, injection time, and holding pressure), yielding the best performance in terms of prescribed criteria (such as temperature difference on the molding at the end of filling, the maximum cavity pressure, the pressure work, the volumetric shrinkage and the cycle time). The methodology proposed was applied to some case studies. The results produced have physical meaning and correspond to a successful process optimization. POLYM. ENG. SCI., 50:1667–1678, 2010. © 2010 Society of Plastics Engineers