{"id":1017,"date":"2023-11-16T06:04:24","date_gmt":"2023-11-16T11:04:24","guid":{"rendered":"https:\/\/www.lynceus.ai\/?p=1017"},"modified":"2023-11-16T06:06:07","modified_gmt":"2023-11-16T11:06:07","slug":"new-insights-into-ic-process-defectivity","status":"publish","type":"post","link":"https:\/\/www.lynceus.ai\/new-insights-into-ic-process-defectivity\/","title":{"rendered":"New Insights Into IC Process Defectivity"},"content":{"rendered":"
The semiconductor industry is in the midst of a transformative phase, encountering unprecedented challenges in defect detection. As design margins tighten, processes evolve, and windows for manufacturing processes shorten, engineers grapple with persistent issues across various nodes and in advanced packaging. In the article, we delve into the intricate landscape of semiconductor manufacturing, exploring the innovative approaches and cutting-edge technologies being employed to address these challenges head-on.<\/p>\n
Machine Learning in the Back-End:<\/strong><\/p>\n Explore how machine learning and AI algorithms are making their mark in back-end processes during assembly and packaging, ensuring a comprehensive approach to defect prevention.<\/li>\n<\/ol>\n