🎙️Lecture: DRL First Winter Workshop organised by Defense Reliability Laboratory
Date:
The Defense Reliability Laboratory (DRL) First Winter Workshop was a pivotal platform where I had the opportunity to share insights on AI-driven predictive maintenance and reliability engineering. As a keynote speaker, I presented cutting-edge research on how AI and machine learning can revolutionize fault detection, diagnostics, and system reliability in defense applications.
Topic: A Workshop on Data-Driven PHM Methodologies- A Hands-on Application 
Key Highlights from My Lecture
📍 My lecture focused on the integration of Deep Learning, Signal Processing, and Sensor Fusion techniques to enhance the remaining useful life (RUL) estimation of critical defense components. My lectures centered on practical appreoaches to data-driven prognostics and health management of mechanical, electrical and electronic components.
Core Discussion Points:
AI for Predictive Maintenance: How deep learning models enhance failure prediction accuracy.
Sensor Fusion for Health Monitoring: Combining multi-sensor data for precise diagnostics.
Anomaly Detection with Machine Learning: Identifying critical failures before they occur.
Case Studies: Real-world applications in aerospace, military vehicles, and advanced weaponry systems.
Engagement & Hands-On Sessions: Participants engaged in practical sessions on data-driven reliability models and had the opportunity to explore live demonstrations of AI-powered diagnostic tools.