Identifying systematic spatial failure patterns through wafer clustering

Published

Conference Paper

© 2016 IEEE. In this paper, we propose a novel methodology for detecting systematic spatial failure patterns at wafer level for yield learning. Our proposed methodology takes the testing results (i.e., pass or fail) of a number of dies over different wafers, cluster all these wafers according to their failures, and eventually identify the underlying spatial failure patterns. Several novel machine learning algorithms, including singular value decomposition, hierarchical clustering, dictionary learning, etc., are developed in order to make the proposed methodology robust to random failures. The efficacy of our proposed approach is demonstrated by an industrial data set.

Full Text

Duke Authors

Cited Authors

  • Alawieh, MB; Wang, F; Li, X

Published Date

  • July 29, 2016

Published In

Volume / Issue

  • 2016-July /

Start / End Page

  • 910 - 913

International Standard Serial Number (ISSN)

  • 0271-4310

International Standard Book Number 13 (ISBN-13)

  • 9781479953400

Digital Object Identifier (DOI)

  • 10.1109/ISCAS.2016.7527389

Citation Source

  • Scopus