Micro genetic algorithm based optimal gate positioning in injection molding design

Jongsoo Lee, Jonghun Kim

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

The paper deals with the optimization of runner system in injection molding design. The design objective is to locate gate positions by minimizing both maximum injection pressure at the injection port and maximum pressure difference among all the gates on a product with constraints on shear stress and/or weld-line. The analysis of filling process is conducted by a finite element based program for polymer flow. Micro genetic algorithm (mGA) is used as a global optimization tool due to the nature of inherent nonlinearlity in flow analysis. Four different design applications in injection molds are explored to examine the proposed design strategies. The paper shows the effectiveness of mGA in the context of optimization of runner system in injection molding design.

Original languageEnglish
Pages (from-to)789-798
Number of pages10
JournalJournal of Mechanical Science and Technology
Volume21
Issue number5
DOIs
Publication statusPublished - 2007 May 1

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Injection molding
Genetic algorithms
Molds
Global optimization
Shear stress
Welds
Polymers

All Science Journal Classification (ASJC) codes

  • Mechanics of Materials
  • Mechanical Engineering

Cite this

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Micro genetic algorithm based optimal gate positioning in injection molding design. / Lee, Jongsoo; Kim, Jonghun.

In: Journal of Mechanical Science and Technology, Vol. 21, No. 5, 01.05.2007, p. 789-798.

Research output: Contribution to journalArticle

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