公开(公告)号：US20200312778A1

公开(公告)日：2020-10-01

申请号：US16439465

申请日：2019-06-12

Applicant: KLA-TENCOR CORPORATION

Inventor： Alex Teng Song Lim ,  Ganesh Meenakshisundaram

IPC: H01L23/544 ,  H01L21/67 ,  G01N21/95 ,  G06T7/00

Abstract: Embodiments herein include methods, systems, and apparatuses for die screening using inline defect information. Such embodiments may include receiving a plurality of defects, receiving wafersort electrical data for a plurality of dies, classifying each of the defects as a defect-of-interest or nuisance, determining a defect-of-interest confidence for each of the defects-of-interest, determining a die return index for each of the dies containing at least one of the defects-of-interest, determining a die return index cutline, and generating an inking map. Each of the defects may be associated with a die in the plurality of dies. Each of the dies may be tagged as passing a wafersort electrical test or failing the wafersort electrical test. Classifying each of the defects as a defect-of-interest or nuisance may be accomplished using a defect classification model, which may include machine learning. The inking map may be electronically communicated to an inking system.

公开(公告)号：US10930597B2

公开(公告)日：2021-02-23

申请号：US16439465

申请日：2019-06-12

Applicant: KLA-TENCOR CORPORATION

Inventor： Alex Teng Song Lim ,  Ganesh Meenakshisundaram

IPC: G06K9/00 ,  H01L23/544 ,  H01L21/67 ,  G06T7/00 ,  G01N21/95

Abstract: Embodiments herein include methods, systems, and apparatuses for die screening using inline defect information. Such embodiments may include receiving a plurality of defects, receiving wafersort electrical data for a plurality of dies, classifying each of the defects as a defect-of-interest or nuisance, determining a defect-of-interest confidence for each of the defects-of-interest, determining a die return index for each of the dies containing at least one of the defects-of-interest, determining a die return index cutline, and generating an inking map. Each of the defects may be associated with a die in the plurality of dies. Each of the dies may be tagged as passing a wafersort electrical test or failing the wafersort electrical test. Classifying each of the defects as a defect-of-interest or nuisance may be accomplished using a defect classification model, which may include machine learning. The inking map may be electronically communicated to an inking system.