Digital Twins & Predictive Maintenance AI

Overview

This talk explores how digital twin technology combined with AI is transforming maintenance strategies across energy infrastructure. We examine machine learning algorithms that process sensor data and environmental conditions to predict equipment failures before they occur. The session covers deep learning for vibration analysis, computer vision for automated inspection, and reinforcement learning for optimizing maintenance scheduling. Real-world case studies demonstrate significant cost savings and improved reliability, while we discuss the integration of IoT sensors with AI analytics platforms and implementing digital twins for legacy energy infrastructure.