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Predicting Powder-Polymer Mixture Properties for PIM Design

Identifieur interne : 000046 ( Main/Exploration ); précédent : 000045; suivant : 000047

Predicting Powder-Polymer Mixture Properties for PIM Design

Auteurs : Kunal H. Kate [États-Unis] ; Ravi K. Enneti [États-Unis] ; Seong-Jin Park [Corée du Sud] ; Randall M. German [États-Unis] ; Sundar V. Atre [États-Unis]

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Mots-clés :

Abstract

Powder injection molding (PIM) is a high-volume manufacturing technique for fabricating ceramic and metal components that have complex shapes. In PIM design, it is important to know the injection molding behavior at different powder-polymer compositions so as to understand the trade-offs between ease-of-fabrication, process throughput, and part quality at the design stage. A limited database of materials properties at different powder-polymer compositions is a significant challenge that needs to be addressed in order to conduct accurate computer simulations that aid part and mold design in PIM. However, accurate material property measurements are expensive and time-consuming. In order to resolve these conflicting challenges it is hypothesized that experimental measurements of material properties of a filled polymer at a specific filler content combined with similar measurements of unfilled polymer will be adequate to estimate the dependence of properties on filler content using rule-of-mixture models. To this end, this article focuses on a literature review of experimental data obtained from measurements of rheological, thermal, and mechanical properties for a wide range of powder-polymer mixtures at various filler volume fractions. The experimental data were compared to property estimates using various predictive models. It is expected that the current review will be valuable in selecting appropriate predictive models for estimating properties based on the input data requirements for commercially available mold-filling simulation platforms such as Moldflow® and PIMSolver®. The combined protocol will be useful to design new materials and component geometries as well as optimize process parameters while eliminating expensive and time-consuming trial-and-error practices prevalent in PIM.


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<div type="abstract" xml:lang="en">Powder injection molding (PIM) is a high-volume manufacturing technique for fabricating ceramic and metal components that have complex shapes. In PIM design, it is important to know the injection molding behavior at different powder-polymer compositions so as to understand the trade-offs between ease-of-fabrication, process throughput, and part quality at the design stage. A limited database of materials properties at different powder-polymer compositions is a significant challenge that needs to be addressed in order to conduct accurate computer simulations that aid part and mold design in PIM. However, accurate material property measurements are expensive and time-consuming. In order to resolve these conflicting challenges it is hypothesized that experimental measurements of material properties of a filled polymer at a specific filler content combined with similar measurements of unfilled polymer will be adequate to estimate the dependence of properties on filler content using rule-of-mixture models. To this end, this article focuses on a literature review of experimental data obtained from measurements of rheological, thermal, and mechanical properties for a wide range of powder-polymer mixtures at various filler volume fractions. The experimental data were compared to property estimates using various predictive models. It is expected that the current review will be valuable in selecting appropriate predictive models for estimating properties based on the input data requirements for commercially available mold-filling simulation platforms such as Moldflow® and PIMSolver®. The combined protocol will be useful to design new materials and component geometries as well as optimize process parameters while eliminating expensive and time-consuming trial-and-error practices prevalent in PIM.</div>
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