Improve the quality and reliability of semiconductors used in automotive, medical, and high volume applications by detecting and removing “outliers” from your production shipments. Some of the techniques used in outlier removal include:

  • Part Average Testing at wafer sort vs. final test
  • Spatial techniques like Good Die in a Bad Neighborhood and Nearest Neighbor Residual for determining wafer-level defects
  • Feeding back outlier data to the manufacturing process to improve yield by better process centering and/or eliminating assembly related defects

Learn how industry leaders are improving the quality and reliability of high volume parts with intelligent outlier removal in this paper.