Photonic sensors-assisted ML pipeline for precise control of curing process in advanced thermosetting composite manufacturing

Evrydiki Kyriazi; Georgios Petsinis; Ioannis Poulopoulos; Georgios Syriopoulos; Thenia Prousalidi; Geoffrey Neale; Mehdi Asareh; Panagiotis Toumasis; Charalampos Zervos; Alexandros A. Skordos; Hercules Avramopoulos

doi:10.1117/12.3022433

20 June 2024 Photonic sensors-assisted ML pipeline for precise control of curing process in advanced thermosetting composite manufacturing

Evrydiki Kyriazi, Georgios Petsinis, Ioannis Poulopoulos, Georgios Syriopoulos, Thenia Prousalidi, Geoffrey Neale, Mehdi Asareh, Panagiotis Toumasis, Charalampos Zervos, Alexandros A. Skordos, Hercules Avramopoulos

Author Affiliations +

Proceedings Volume 12999, Optical Sensing and Detection VIII; 129990W (2024) https://doi.org/10.1117/12.3022433
Event: SPIE Photonics Europe, 2024, Strasbourg, France

Abstract

This study introduces an innovative approach to enhance the utilization of carbon fiber thermosetting composites in advanced structural engineering by addressing the challenges of high manufacturing costs and limited production rates. We develop, deploy and test an ML pipeline utilizing PIC-based sensors (SOI technology, 220 nm thick, fabricated at IMEC’s MPW). They are based on a Bragg structure, packaged using ball lenses and suitable for operating at 180 degrees Celsius and 5 bar pressure. The focus is on accurately predicting two crucial parameters: Cure time and Temperature Overshoot, vital for determining the process duration and part quality. Using advanced tools and sensors, this study achieves a high prediction accuracy of 98% in millisecond scale while effectively handling the outliers. The ML pipeline allows the real-time process optimization of manufacturing process, minimizing the cost, and providing insights into the quality of the composite part through the in-depth monitoring of the process.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Evrydiki Kyriazi, Georgios Petsinis, Ioannis Poulopoulos, Georgios Syriopoulos, Thenia Prousalidi, Geoffrey Neale, Mehdi Asareh, Panagiotis Toumasis, Charalampos Zervos, Alexandros A. Skordos, and Hercules Avramopoulos "Photonic sensors-assisted ML pipeline for precise control of curing process in advanced thermosetting composite manufacturing", Proc. SPIE 12999, Optical Sensing and Detection VIII, 129990W (20 June 2024); https://doi.org/10.1117/12.3022433

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