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.
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