Pattern recognition in large-scale data sets: Application in integrated circuit manufacturing

Choudur K. Lakshminarayan, Michael I. Baron

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

It is important in semiconductor manufacturing to identify probable root causes, given a signature. The signature is a vector of electrical test parameters measured on a wafer. Linear discriminant analysis and artificial neural networks are used to classify a signature of test electrical measurements of a failed chip to one of several pre-determined root cause categories. An optimal decision rule that assigns a new incoming signature of a chip to a particular root cause category is employed such that the probability of misclassification is minimized. The problem of classifying patterns with missing data, outliers, collinearity, and non-normality are also addressed. The selected similarity metric in linear discriminant analysis, and the network topology, used in neural networks, result in a small number of misclassifications. An alternative classification scheme is based on the locations of failed chips on a wafer and their spatial dependence. In this case, we model the joint distribution of chips by a Markov random field, estimate its canonical parameters and use them as inputs for the artificial neural network that also classifies the patterns by matching them to the probable root causes.

Original languageEnglish
Title of host publicationBig Data Analytics - Second International Conference, BDA 2013, Proceedings
Pages185-196
Number of pages12
DOIs
StatePublished - 2013
Event2nd International Conference on Big Data Analytics, BDA 2013 - Mysore, India
Duration: 16 Dec 201318 Dec 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8302 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd International Conference on Big Data Analytics, BDA 2013
Country/TerritoryIndia
CityMysore
Period16/12/1318/12/13

Keywords

  • Back Propagation
  • Failure Analysis
  • Integrated-Circuit
  • Linear Discriminant Analysis
  • Mahalanobis Distance
  • Markov Random Fields and spatial signatures
  • Neural Networks
  • Pattern Recognition
  • Signature Analysis

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