The solution enabled bonded wafer analysis by coupling electrical data, pixel-level data, and test structures into a unified framework. This allowed precise correlation of failing bonded die, bridging ASIC performance with pixel behavior.
Engineers can drill down to individual data elements to identify root causes of yield loss, including parametric drift, spatial anomalies, and dead or dim pixels—linking failures directly to process variations, bonding issues, or physical defect.
AI enabled data analysis that digs deeper into the data and finds anomalies that were previously not detected.
Parametric wafer maps, heat maps, defect maps, histograms, box plots, and trend charts—along with statistical calculations such as quartile and interquartile range (IQR)—were enhanced for greater accuracy and reliability.
Improvements to chart rendering, data grouping, limit handling, and die-level filtering ensured consistent analysis and robust, production-ready workflows