From Downtime to Uptime: Asset Health Management in the Digital Era

Predictive Maintenance (PdM) has become a cornerstone of Industry 4.0, enabling organizations to move from reactive fixes to proactive asset health management. This webinar demonstrates how MATLAB and Simulink provide an integrated environment for designing end-to-end PdM applications—from sensor data acquisition and preprocessing to AI/ML model training, validation, and deployment.

Participants will learn how to build PdM workflows that span the complete lifecycle: data ingestion from IoT-enabled equipment, feature engineering, machine learning model development, and deployment of predictive models to embedded devices, desktop applications, and cloud platforms. The session will also introduce best practices for managing PdM pipelines using MLOps principles, ensuring scalability, traceability, and continuous improvement of deployed models.

By showcasing real-world examples, the webinar highlights how engineers and data scientists can accelerate predictive maintenance projects, reduce unplanned downtime, and extend asset life—all within a unified MATLAB ecosystem.