Title: Detecting Composite Deviations during Molding with Real-Time Sensor Data

Authors: Nicholas Ecke , John Puentes, Josef Ketels , Johannes Roth, Phil Gralla , Alec Redmann

DOI: 10.33599/nasampe/s.24.0066

Abstract: This work studied whether dielectric and statistical parameters could detect composite deviation due to material handling before and during production. Researchers used in-situ monitoring of dielectric signals and cavity temperature using in-mold sensors, dielectric analysis (DEA), kinetic models, and statistical analysis. The study found that resistivity, the reciprocal of ion conductivity (sometimes simplified as ion viscosity), could highlight mixing ratio variations. Also, dielectric properties capture aging. Curing kinetics based on kinetic models and measured temperature data could not capture these effects.

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Conference: SAMPE 2024

Publication Date: 2024/05/20

SKU: TP24-0000000066

Pages: 8

Price: $16.00