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Using silicon photonic multi-sensors, the SEER project is developing smart self-monitoring composite tools to measure process and material parameters.

The aim is to leverage machine learning to provide unprecedented reliability of the cured part while significantly cutting costs through preventive maintenance of the tools.

Specifically, the project will develop miniature photonic sensors to embed in the tool with through-the-thickness techniques that minimise alteration of the tool's structural integrity. The sensors will be capable of providing temperature, refractive index and pressure data of the composite part without compromising its structure. It will also provide a part quality fingerprint, ensuring the quality of the part based on the undergone curing process.

The SEER solution will be made compatible with existing composite manufacturing and measurement methods.

Photonics PPP Projects

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