Process parameters optimization of injection molding using a fast strip analysis as a surrogate mod.pdf
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Process parameters optimization of injection molding using a fast strip analysis as a surrogate mod
ORIGINAL ARTICLE
Process parameters optimization of injection molding
using a fast strip analysis as a surrogate model
Peng Zhao Huamin Zhou Yang Li Dequn Li
Received: 6 May 2009 /Accepted: 9 November 2009 /Published online: 28 November 2009
# Springer-Verlag London Limited 2009
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 parame-
ters 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.
Keywords Injection molding . Parameters optimization .
Surrogate model . Evolutionary algorithm .
Fast strip analysis . Particle swarm optimization
1 Introduction
Injection molding is the most widely used process for
producing plastic products. During this process, many
parameters such as injection temperature, mold tempera-
ture, and injection time are very important, which have
direct influence on the quality and cost of the products.
However, the optimization of process parameters is a
complex and difficult task [1–3]. An increase in injection
temperature causes a decrease in melt viscosity, which
results in reduced cavity pressure and
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