Validation of three on-line flow simulations for injection molding

Polymer process control is limited by a lack of observability of the distributed and transient polymer states. Three simulations of varying complexity are validated for on‐line simulation of an injection molding process with a two drop hot runner system to predict the state of the polymer melt in re...

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Published inPolymer engineering and science Vol. 46; no. 3; pp. 274 - 288
Main Authors Kazmer, David O., Nageri, Ranjan, Kudchakar, Vijay, Fan, Bingfeng, Gao, Robert
Format Journal Article
LanguageEnglish
Published Hoboken Wiley Subscription Services, Inc., A Wiley Company 01.03.2006
Wiley Subscription Services
Society of Plastics Engineers, Inc
Blackwell Publishing Ltd
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Summary:Polymer process control is limited by a lack of observability of the distributed and transient polymer states. Three simulations of varying complexity are validated for on‐line simulation of an injection molding process with a two drop hot runner system to predict the state of the polymer melt in real time and thereby improve product quality in situ. The simplest simulation is a Newtonian model, which predicts flow rates given the inlet and outlet pressures. An intermediate non‐Newtonian and nonisothermal simulation utilizes a modified Ellis model that expresses the viscosity as a function of the shear stress in which the modeling of the heat transfer utilizes a Bessel series expansion to include effects of heat conduction, heat convection, and internal shear heating. A numerical simulation was also developed that utilizes a hybrid finite difference and finite element scheme to simultaneously solve the mass, momentum, and heat equations. Numerical verification indicates that the flow rate predictions of the described simulations compare well with the results from a commercial mold filling simulation. However, empirical validation utilizing a design of experiments indicates that the described analyses are qualitatively useful, but do not possess sufficient accuracy for quantitative process and quality control. Specifically, off‐line validation using optimal transducer calibration with well characterized materials provided a coefficient of regression, R2, of ∼0.8. However, blind validation with previously untested materials and no transducer re‐calibration provided a regression coefficient of ∼0.4. While the direction of the main effects was usually correct, the magnitudes of the effects were frequently outside the confidence interval of the observed behavior. Several sources of variance are discussed, including sensor calibration, constitutive modeling of the polymer melt, and numerical analysis. POLYM. ENG. SCI. 46:274–288, 2006. © 2006 Society of Plastics Engineers
Bibliography:This work does not represent the opinions of Mold-Masters, the National Science Foundation, nor the United States government.
istex:9D60D6557CF2472B3FB162B46A2E504C61AD134C
ArticleID:PEN20463
Manufacturing Machines and Equipment Program of the National Science Foundation - No. DMI-0428669
Mold-Masters Ltd.
ark:/67375/WNG-0LBGJ8R3-K
This work does not represent the opinions of Mold‐Masters, the National Science Foundation, nor the United States government.
ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0032-3888
1548-2634
DOI:10.1002/pen.20463