Case Study: Semiconductors Company improves wafer yield with Falkonry Time Series AI

How Falkonry Enables Yield Improvement

A semiconductors company was facing significant challenges with wafer defect density analysis. The expensive and delayed inspection process was causing reduced fab throughput, revenue loss, and high costs. Falkonry was engaged to help address this critical yield loss issue.

Falkonry implemented its advanced anomaly detection to analyze time series data from 75 signals like voltage, pressure, and temperature. Using unsupervised AI modeling, Falkonry discovered correlations between sensor readings and defect density, enabling the customer to create a better sampling plan. This solution decreased the total inspection sampling rate and cost while reducing the risk of missing major defects.