This article explains how Seeq software on AWS enables semiconductor manufacturers to implement predictive maintenance, reducing costs and downtime.

• Predictive maintenance uses IoT/sensor data to anticipate equipment failures before they occur
• Traditional preventive maintenance schedules are conservative; reactive maintenance causes unplanned downtime
• Deloitte reports predictive maintenance delivers 5-10% operational cost savings
• Seeq on AWS connects to AWS data services for real-time analytics without coding
• Engineers can build regression models in hours instead of weeks using point-and-click tools
• Models scale across equipment fleets using asset hierarchies with just clicks
• Cloud hosting enables secure sharing of analyses across global teams and sites
• New fabs can start with semi-mature predictive maintenance programs that auto-improve

Seeq powered by AWS simplifies predictive maintenance implementation for semiconductor fabs, enabling rapid model development and deployment without requiring data scientists or coding expertise.