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Process parameters optimization of injection molding using a fast strip analysis as a surrogate model.
- Source :
- International Journal of Advanced Manufacturing Technology; Aug2010, Vol. 49 Issue 9-12, p949-959, 11p, 1 Black and White Photograph, 6 Diagrams, 2 Charts, 5 Graphs
- Publication Year :
- 2010
-
Abstract
- Injection molding process parameters such as injection temperature, mold temperature, and injection time have direct influence on the quality and cost of products. However, the optimization of these parameters is a complex and difficult task. In this paper, a novel surrogate-based evolutionary algorithm for process parameters optimization is proposed. Considering that most injection molded parts have a sheet like geometry, a fast strip analysis model is adopted as a surrogate model to approximate the time-consuming computer simulation software for predicating the filling characteristics of injection molding, in which the original part is represented by a rectangular strip, and a finite difference method is adopted to solve one dimensional flow in the strip. Having established the surrogate model, a particle swarm optimization algorithm is employed to find out the optimum process parameters over a space of all feasible process parameters. Case studies show that the proposed optimization algorithm can optimize the process parameters effectively. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 02683768
- Volume :
- 49
- Issue :
- 9-12
- Database :
- Complementary Index
- Journal :
- International Journal of Advanced Manufacturing Technology
- Publication Type :
- Academic Journal
- Accession number :
- 52836364
- Full Text :
- https://doi.org/10.1007/s00170-009-2435-7