Optimization of the injection molding process for short-fiber-reinforced composites

A fast and effective methodology integrating the finite-element and Taguchi methods is presented to determine the optimal design conditions of the injection molding process for short-fiber-reinforced polycarbonate composites. The finite-element-based flow simulation software, M-flow, was employed to...

Full description

Saved in:
Bibliographic Details
Published in:Mechanics of composite materials 2011-07, Vol.47 (3), p.359-368
Main Authors: Chen, Ch.-Sh, Chen, T.-J., Chen, Sh.-Ch, Chien, R.-D.
Format: Article
Language:English
Subjects:
Ceramics
Characterization and Evaluation of Materials
Chemistry and Materials Science
Classical Mechanics
Composite materials industry
Composites
Fiber orientation
Glass
Injection molding
Materials Science
Mathematical analysis
Mathematical optimization
Molds
Natural Materials
Optimization
Polymer matrix composites
Shear layers
Simulation
Software
Solid Mechanics
Synthetic training devices
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:A fast and effective methodology integrating the finite-element and Taguchi methods is presented to determine the optimal design conditions of the injection molding process for short-fiber-reinforced polycarbonate composites. The finite-element-based flow simulation software, M-flow, was employed to simulate the molding process to obtain the fiber orientation distributions required. The Taguchi optimization technique was used to identify the optimal settings of injection molding parameters to maximize the shear layer thickness. The effects of four main parameters — the filling time, melt temperature, mold temperature, and injection speed — on the fiber orientation or the shear layer thickness were investigated and discussed. It is found that the dominant parameter is the filling time. The best levels of the four parameters to acquire the thickest shear layer are also identified.
ISSN:0191-5665
1573-8922
DOI:10.1007/s11029-011-9214-x