- Detailed explanation of the proposed solution - How it addresses the problem - Innovation and uniqueness of the solution

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This project focuses on transforming sparse and noisy engine-health data into actionable prognostics. By employing a physics-informed digital twin, it aims to detect faults before they reach unsafe limits, estimate the remaining useful life (RUL) of components, and adapt to varying altitude and load conditions. The ultimate goal is to enhance operational safety and efficiency through advanced diagnostics and predictive maintenance.