Markov random fields in pattern recognition for semiconductor manufacturing

Michael Baron, Choudur K. Lakshminarayan, Zhenwu Chen

Research output: Contribution to specialist publicationArticle

5 Scopus citations

Abstract

Under the most general conditions of an anisotropic Markov random field, we model the two-dimensional spatial distribution of microchips on a silicon wafer. The proposed model improves on its predecessors as it stipulates the spatial correlation of different strengths in all eight directions. Its canonical parameters represent the intensity of failures, main effects, and interactions of neighboring chips. Explicit forms of conditional distributions are derived, and maximum pseudo-likelihood estimates of canonical parameters are obtained. This numerical characteristic summarizes general patterns of clusters of failing chips on a wafer, capturing their size, shape, direction, density, and thickness. It is used to classify incoming wafers to known root-cause categories by matching them to the closest pattern.

Original languageEnglish
Pages66-72
Number of pages7
Volume43
No1
Specialist publicationTechnometrics
DOIs
StatePublished - Feb 2001

Fingerprint

Dive into the research topics of 'Markov random fields in pattern recognition for semiconductor manufacturing'. Together they form a unique fingerprint.

Cite this