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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Tretiak, Iryna
University of Bristol
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (8/8 displayed)
- 2024Characterising the Effect of Void Morphology on Composites Strength using Deep Learning
- 2024Virtual data-driven optimisation for zero defect composites manufacturecitations
- 2023Automatic process control of an automated fibre placement machinecitations
- 2023Peculiarities of the Design of Housing Parts of Large Direct Current Machinescitations
- 2023In-situ defect detection and correction using real time automated fibre placement
- 2023Manufacturing composite laminates with controlled void content through process controlcitations
- 2022The Effect of Process Parameters on First Ply Deposition in Automated Fibre Placementcitations
- 2019A parametric study of segmentation thresholds for X-ray CT porosity characterisation in composite materialscitations
Places of action
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article
Automatic process control of an automated fibre placement machine
Abstract
Deposition defects arising during automated fibre placement (AFP) reduces production rate and creates wastage from rejected parts. This issue can be alleviated by identifying and reacting to those defects in real-time during deposition. To demonstrate the concept, this study augmented an AFP process with profilometry sensors and software control. Description of the machine, its sensors, and the control system is provided. In the experiment, representative bonding defects at the tow level representative of a typical AFP layup were introduced. These defects were picked up by the profilometry sensors, and the machine automatically adjusted the process parameters when the defects reached the nip point. Microscopy revealed that such a procedure can influence the material microstructure and reduce in-plane waviness in the final cured laminate. This demonstrates the feasibility of the observe-think-react concept in AFP and provides another step toward real-time defect monitoring and correction in composites manufacturing.