In-Situ Co-Extrusion: Additive Manufacturing of Continuous Reinforced Thermoplastic Composites

2018 ◽  
Author(s):  
JAMES GAROFALO ◽  
DANIEL WALCZYK
Keyword(s):  
Additive Manufacturing ◽  
Thermoplastic Composites

scholarly journals Additive Manufacturing-Based In Situ Consolidation of Continuous Carbon Fibre-Reinforced Polycarbonate

Materials ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2450
Author(s):  
Andreas Borowski ◽  
Christian Vogel ◽  
Thomas Behnisch ◽  
Vinzenz Geske ◽  
Maik Gude ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Carbon Fibre ◽  
Bending Test ◽  
Thermoplastic Composites ◽  
Experimental Investigations ◽  
Material Structure ◽  
Three Point Bending ◽  
Continuous Fibre ◽  
Local Material

Continuous carbon fibre-reinforced thermoplastic composites have convincing anisotropic properties, which can be used to strengthen structural components in a local, variable and efficient way. In this study, an additive manufacturing (AM) process is introduced to fabricate in situ consolidated continuous fibre-reinforced polycarbonate. Specimens with three different nozzle temperatures were in situ consolidated and tested in a three-point bending test. Computed tomography (CT) is used for a detailed analysis of the local material structure and resulting material porosity, thus the results can be put into context with process parameters. In addition, a highly curved test structure was fabricated that demonstrates the limits of the process and dependent fibre strand folding behaviours. These experimental investigations present the potential and the challenges of additive manufacturing-based in situ consolidated continuous fibre-reinforced polycarbonate.

An investigation of in situ impregnation for additive manufacturing of thermoplastic composites

2021 ◽  
Vol 64 ◽  
pp. 972-981
Author(s):  
Daniel Kaczmarek ◽  
Daniel Walczyk ◽  
James Garofalo ◽  
Margaret Sobkowicz-Kline
Keyword(s):  
Additive Manufacturing ◽  
Thermoplastic Composites

scholarly journals Adhesion Studies during Generative Hybridization of Textile-Reinforced Thermoplastic Composites via Additive Manufacturing

Materials ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 3888
Author(s):  
Johanna Maier ◽  
Christian Vogel ◽  
Tobias Lebelt ◽  
Vinzenz Geske ◽  
Thomas Behnisch ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Polyamide 6 ◽  
Thermoplastic Composites ◽  
Efficient Production ◽  
Angle Measurements ◽  
Small Series ◽  
Contact Angle Measurements ◽  
Static Tensile ◽  
Pre Treatment ◽  
Manufacturing Technologies

Generative hybridization enables the efficient production of lightweight structures by combining classic manufacturing processes with additive manufacturing technologies. This type of functionalization process allows components with high geometric complexity and high mechanical properties to be produced efficiently in small series without the need for additional molds. In this study, hybrid specimens were generated by additively depositing PA6 (polyamide 6) via fused layer modeling (FLM) onto continuous woven fiber GF/PA6 (glass fiber/polyamide 6) flat preforms. Specifically, the effects of surface pre-treatment and process-induced surface interactions were investigated using optical microscopy for contact angle measurements as well as laser profilometry and thermal analytics. The bonding characteristic at the interface was evaluated via quasi-static tensile pull-off tests. Results indicate that both the bond strength and corresponding failure type vary with pre-treatment settings and process parameters during generative hybridization. It is shown that both the base substrate temperature and the FLM nozzle distance have a significant influence on the adhesive tensile strength. In particular, it can be seen that surface activation by plasma can significantly improve the specific adhesion in generative hybridization.

scholarly journals Review: Filament Winding and Automated Fiber Placement with In Situ Consolidation for Fiber Reinforced Thermoplastic Polymer Composites

Polymers ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 1951
Author(s):  
Yi Di Boon ◽  
Sunil Chandrakant Joshi ◽  
Somen Kumar Bhudolia
Keyword(s):  
Processing Parameters ◽  
Filament Winding ◽  
Reference Points ◽  
Thermoplastic Composites ◽  
Manufacturing Processes ◽  
Fiber Reinforced ◽  
Consolidation Process ◽  
Fiber Placement ◽  
Automated Fiber Placement

Fiber reinforced thermoplastic composites are gaining popularity in many industries due to their short consolidation cycles, among other advantages over thermoset-based composites. Computer aided manufacturing processes, such as filament winding and automated fiber placement, have been used conventionally for thermoset-based composites. The automated processes can be adapted to include in situ consolidation for the fabrication of thermoplastic-based composites. In this paper, a detailed literature review on the factors affecting the in situ consolidation process is presented. The models used to study the various aspects of the in situ consolidation process are discussed. The processing parameters that gave good consolidation results in past studies are compiled and highlighted. The parameters can be used as reference points for future studies to further improve the automated manufacturing processes.

Towards process consistency and in-situ evaluation of porosity during laser powder bed additive manufacturing

2020 ◽  
Vol 25 (8) ◽  
pp. 679-689
Author(s):  
J. Raplee ◽  
J. Gockel ◽  
F. List ◽  
K. Carver ◽  
S. Foster ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Powder Bed

scholarly journals Automated Testing and Characterization of Additive Manufacturing (ATCAM)

2021 ◽  
Author(s):  
Arash Alex Mazhari ◽  
Randall Ticknor ◽  
Sean Swei ◽  
Stanley Krzesniak ◽  
Mircea Teodorescu
Keyword(s):  
Additive Manufacturing ◽  
Fused Deposition Modeling ◽  
Cell System ◽  
Automated Testing ◽  
Fused Deposition ◽  
Deposition Modeling ◽  
Machine Calibration

AbstractThe sensitivity of additive manufacturing (AM) to the variability of feedstock quality, machine calibration, and accuracy drives the need for frequent characterization of fabricated objects for a robust material process. The constant testing is fiscally and logistically intensive, often requiring coupons that are manufactured and tested in independent facilities. As a step toward integrating testing and characterization into the AM process while reducing cost, we propose the automated testing and characterization of AM (ATCAM). ATCAM is configured for fused deposition modeling (FDM) and introduces the concept of dynamic coupons to generate large quantities of basic AM samples. An in situ actuator is printed on the build surface to deploy coupons through impact, which is sensed by a load cell system utilizing machine learning (ML) to correlate AM data. We test ATCAM’s ability to distinguish the quality of three PLA feedstock at differing price points by generating and comparing 3000 dynamic coupons in 10 repetitions of 100 coupon cycles per material. ATCAM correlated the quality of each feedstock and visualized fatigue of in situ actuators over each testing cycle. Three ML algorithms were then compared, with Gradient Boost regression demonstrating a 71% correlation of dynamic coupons to their parent feedstock and provided confidence for the quality of AM data ATCAM generates.

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