IT@Intel: Transforming Manufacturing Yield Analysis with AI

January 22nd, 2022 |
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Intel IT is using artificial intelligence (AI) to accelerate yield ramp by clustering and classifying manufacturing failure patterns.

Expert yield analysis engineers have always performed end-of-line yield analysis at Intel’s silicon wafer factories (fabs). But as the number of products and volume grow in Intel’s manufacturing environment, a manual detection approach to yield analysis poses several challenges:

  • Limited human-hour resources prevent engineers from reviewing and documenting every issue in every wafer in every lot.
  • Detection accuracy depends on an engineer’s experience level.
  • Knowledge sharing between fabrication sites is cumbersome and slow.

Intel is changing the paradigm of yield analysis from this manual, reactive “pull” approach to a proactive “push” approach, which is helping to find problems such as failing tools, fleet mismatches and process parameter shifts, quickly and accurately. The more quickly such issues are identified, the sooner they get fixed and overall yield is improved.

The solution is characterized by the following: