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Analogy of Thermal Properties of Polyamide 6 Reinforced with Glass Fiber and Glass Beads through FDM Process
ISSN: 0148-7191, e-ISSN: 2688-3627
Published October 11, 2019 by SAE International in United States
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Event: International Conference on Advances in Design, Materials, Manufacturing and Surface Engineering for Mobility
The essential target of this examination is to compare the morphological and thermal properties of two different polyamide composite blends with inventive thermal properties. The polyamide-6 (PA6) reinforced with 10, 20 and 30 wt. % glass fiber (GF) and PA6 reinforced with 10, 20 and 30 wt. % glass beads (GB) are the two different polyamide composite blends extruded in form of wire by twin screw extrusion process. The experimental study illustrates to print the specimens by means of Fusion Deposition Modeling (FDM) based Three-Dimensional (3D) printer. The responses like morphology, Thermal Conductivity (TC) and Heat Distortion Temperature (HDT) of composites were observed. From the scanning electron microscope (SEM) analysis equal distribution of higher 30wt% GF and GB in the PA6 matrix was observed. The results compare the increasing thermal properties of the 3D printed specimen like TC and HDT with the enhancement of beads content during the investigation. The GB are crystalline material which improves the thermal properties of the PA6 matrix and the GF are dimensionally stable material that can provide high modulus to the PA6 matrix. It was observed that, thermal property of neat PA6 matrix reinforced with 10, 20, 30 wt. % GB are comparatively higher than that of neat PA6 matrix reinforced with 10, 20, 30 wt. % GF. PA6+30% GB enhances the thermal properties and it may open new avenues for industrial applications like automotive, aerospace and electronics components.
CitationRanganathan, S., Rangasamy Suguna Thangaraj, H., Vasudevan, A., and Shanmugan, D., "Analogy of Thermal Properties of Polyamide 6 Reinforced with Glass Fiber and Glass Beads through FDM Process," SAE Technical Paper 2019-28-0137, 2019, https://doi.org/10.4271/2019-28-0137.
Data Sets - Support Documents
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