On the use of decision tree induction for discovery of interactions in a photolithographic process

Dan Braha, Armin Shmilovici

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

This paper delineates a comprehensive and successful application of decision tree induction to 1054 records of production lots taken from a lithographic process with 45 processing steps. Complex interaction effects among manufacturing equipment that lead to increased product variability have been detected. The extracted information has been confirmed by the process engineers, and used to improve the lithographic process. The paper suggests that decision tree induction may be particularly useful when data is multidimensional, and the various process parameters and machinery exhibit highly complex interactions. Another implication is that on-line monitoring of the manufacturing process (e.g., closed-loop critical dimensions control) using data mining may be highly effective.

Original languageEnglish
Pages (from-to)644-652
Number of pages9
JournalIEEE Transactions on Semiconductor Manufacturing
Volume16
Issue number4
DOIs
StatePublished - 1 Nov 2003

Keywords

  • Data mining
  • Decision tree induction
  • Photolithography
  • Semiconductor process control
  • Yield management

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering

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