AI on the factory floor.

Through targeted training and hands-on experience, we’re preparing our people to lead in an AI-driven world. We aim to unlock innovation, agility, and competitive advantage across our operation. As of 2024, 100% of Factory IT staff have received foundational AI training. 

Our advanced drive factory process monitoring and root cause analysis system is now powered by gen AI. It enables a new level of operational excellence. By automating complex, data-heavy tasks, we quickly detect anomalies, trace issues to their root causes, and recommend optimal responses in real time. Time-to-issue resolution has reduced from weeks or days to hours or minutes. 

Seagate's advanced AI systems in the wafer factories include a context-aware process time control solution that adapts to specific conditions and variables, enhancing process reliability and ensuring consistent outcomes. This has led to $1.7M in annual savings, highlighting the significant impact of AI in our operational efficiency. 

Our AI-powered material deviation authorization system streamlines thousands of automated decisions each week, driving annual savings of about $1M. By swiftly and accurately addressing material deviations, the system helps to reduce waste and boost efficiency. We’re now working to augment this solution with gen AI, transforming our approach and revolutionizing the processes. Early results are incredibly promising, paving the way for even greater impact. 

Our scalable Image AI solutions revolutionize defect detection and classification in manufacturing. The improvements range from inspecting up to 3 million images daily for Slider Trailing Edge defects to enabling automated defect pattern classification across multiple critical processes. These systems ensure rapid issue resolution, root cause prediction, and upstream equipment control. The solutions have delivered over $6.6 million in cumulative savings through improved yield, reduced scrap, and optimized inspection resources while safeguarding product quality. Built for scale and adaptability, these AI-driven solutions help to ensure quality across our manufacturing lines. 

By applying advanced ML and clustering techniques to upstream wafer parametric data, we optimize downstream slider performance and boost yield. With deep learning and expanded feature sets, the system significantly improves model accuracy and process control. Since 2023, it has delivered over $10M in savings through enhanced quality, yield, and cost efficiency. Two U.S. IP rights have been awarded for this innovation. 

Our smart sputter leak detection system has saved $1.95 million annually, preventing the scrap of up to 103,000 disks per year. Additionally, our patented LubeLine image analytics has resulted in $1.51 million in annual savings, including $580,000 in labor costs and $932,000 from reduced long defective material report (DMR) scrap. These technologies exemplify our commitment to leveraging AI for cost savings and operational excellence.    

Wafer factories have generated over $30 million in value over five years from an image quality solution. Initially built on a custom deep learning model, the solution evolved into a scalable, generalized approach to support diverse tools, processes, and image types. Current enhancements focus on integrating generative AI with automated classification.