What We Did:
We analyzed a set of thermocouple readings from two distinct areas of our RTM-6 material embedded with carbon fiber. This deep dive allowed us to understand the heating and cooling cycles intimately.Using our ML/Ai framework we demonstrated very accurate predictions in near real-time.

💡 Key Insights:

  1. The upper and lower parts of the material exhibit different thermal behaviors. This understanding can help in optimizing the curing process tailored to each section.
  2. By leveraging a predictive model, we gauged the cure time and overshoot temperature resulting in a strong validation with real-world data, reinforcing the model’s reliability.

🚀 Why This Matters :

🔍 Validation with Real Data:
Our partners and collaborators greatly enchanced our validation process with real data , showcasing the model’s robustness and reliability. We now plan for an even bigger run with a more diverse dataset. We need to highlight that these results are in almost sub-second time .

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