Case Study: Seagate doubles wafer yield and cuts manufacturing cycle time with Iguazio

How Seagate Runs Advanced Manufacturing at Scale With Iguazio

Seagate, the global data storage leader, needed a way to handle petabytes of sensor, parametric, and image data from its factories while reducing chip and wafer manufacturing time, capital costs, and manual inspection effort. The company’s challenge was especially acute in wafer manufacturing, where about 40% of production time was spent on measurement steps and traditional sampling methods struggled to capture complex wafer behavior. Seagate used Iguazio’s Lyve Cloud Analytics platform to support its data engineering and MLOps needs.

With Iguazio, Seagate implemented smart sampling, automated deep learning and computer vision inspection, and scalable data processing across on-prem and cloud environments. The solution combined tools like Spark, Trino, MLRun, Nuclio, and Kubernetes to automate ingestion, orchestration, model deployment, and monitoring. As a result, Seagate doubled first-pass wafer yield, eliminated contamination, reduced manufacturing steps by 40%, and improved cloud usage efficiency by 6x.

Seagate