On-Demand
Learn how Intel is using agentic AI-supported workflows in Seeq to transform maintenance operations across its global semiconductor manufacturing footprint. With thousands of critical assets across multiple sites, Intel is projecting 30% faster anomaly detection in ultrapure water systems, a 15-20% reduction in technician workload through autonomous work order generation, and more than 120,000 labor hours saved annually.
These results are powered by a shift from time-based and alarm-driven maintenance to condition-based operations. Intel leverages Seeq to continuously monitor asset health, detect abnormal conditions earlier, forecast maintenance needs, generate work orders, and provide engineers with actionable context. By codifying the expertise of its global engineering and operations teams into scalable workflows, Intel is extending institutional knowledge across facilities, improving consistency, and accelerating action. With human oversight built into every step, Intel is on a practical, governed journey toward semi-autonomous maintenance operations.
This session will explore real-world applications in ultrapure water and compressor maintenance and share practical lessons for implementing agentic AI at scale, including governance, repeatability, and scaling AI-driven reliability programs across a global manufacturing enterprise.
