Agentic AI For Next-Generation Semiconductor Manufacturing

The session introduces Agentic AI and its applications in semiconductor manufacturing, addressing critical challenges like defect detection, yield enhancement, and process variability. Through real-world case studies, it will demonstrate how AI-driven solutions can significantly improve in fab efficiency and accuracy. The discussion will highlight the transformative potential of Agentic AI in optimizing semiconductor production, setting the stage for deeper exploration in future discussions.

The session will focus on leveraging Agentic AI for process optimization, including Smart FDC, YMS, ML Ops, and recipe optimization. Key topics will include look-ahead scheduling, line balancing, virtual metrology, and smart inspection strategies. Energy and gas management strategies are highlighted alongside AI-driven sampling optimization. Practical methods for seamlessly integrating AI into existing manufacturing systems will be explored, with an emphasis on streamlining operations to achieve autonomous manufacturing.

Sponsored by SEEQ

The session will highlight the use of Agentic AI for equipment health monitoring and predictive maintenance in fabs and sub-fabs, exploring benefits such as cost savings, improved uptime, and enhanced operational efficiency. Key topics will include smart maintenance, prognosis health monitoring, anomaly detection and techniques for estimating the remaining useful life (RUL) of equipment. The session will emphasize AI's role in optimizing maintenance practices.

Efficiency in supply chains can be significantly enhanced by deploying AI agents for fundamental tasks such as factory-level planning, floor scheduling, real-time dispatching, and monitoring manufacturing processes at remote or contract facilities. These agents can quickly issue alerts for variations in yields or shipping schedules, taking corrective actions, such as expediting or rerouting shipments to prevent delays. Given the complexity of extended global supply chains—especially those involving multiple fabrication, assembly, and testing cycles compounded by chiplet production and advanced packaging—AI agents substantially improve coordination and operational efficiency.