In an increasingly complex manufacturing environment, maintenance isn't just about fixing what's broken, it's about predicting what’s next. This workshop explores how predictive maintenance, powered by industrial data and AI, is transforming asset management and unlocking a new level of productivity and reliability for the connected worker.

Our dynamic workshop leaders will demonstrate how to operationalize siloed data, empower frontline teams with actionable insights, and create a connected maintenance ecosystem where workers, systems, and assets communicate in real time. Key Themes: 

• Understanding the evolution of maintenance, from reactive firefighting to data-driven foresight 
• Connecting workers to the asset ecosystem with mobile apps, AR interfaces, and digital twins to deliver real-time asset status and recommendations directly to frontline workers 
• How to break down data silos across enterprise systems, sensors, historian databases, and asset registries 
• Building a common language of data that feeds both predictive models and operator workflows 
• Designing workflows that turn predictive insights into scheduled tasks, routed to the right worker, at the right time, with the right context 
• Identifying patterns that humans can’t, predicting failure, optimizing servicing, and reducing unplanned downtime 
• Step-by-step guidance on moving from pilot to full-scale deployment