A dynamic sampling methodology for plasma etch processes using Gaussian process regression

Jian Wan, Bahman Honari, Sean McLoone

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

Plasma etch is a key process in modern semiconductor manufacturing facilities as it offers process simplification and yet greater dimensional tolerances compared to wet chemical etch technology. The main challenge of operating plasma etchers is to maintain a consistent etch rate spatially and temporally for a given wafer and for successive wafers processed in the same etch tool. Etch rate measurements require expensive metrology steps and therefore in general only limited sampling is performed. Furthermore, the results of measurements are not accessible in real-time, limiting the options for run-to-run control. This paper investigates a Virtual Metrology (VM) enabled Dynamic Sampling (DS) methodology as an alternative paradigm for balancing the need to reduce costly metrology with the need to measure more frequently and in a timely fashion to enable wafer-to-wafer control. Using a Gaussian Process Regression (GPR) VM model for etch rate estimation of a plasma etch process, the proposed dynamic sampling methodology is demonstrated and evaluated for a number of different predictive dynamic sampling rules.

Original languageEnglish
Title of host publication2013 24th International Conference on Information, Communication and Automation Technologies, ICAT 2013
PublisherIEEE Computer Society
DOIs
Publication statusPublished - 01 Jan 2013
Event2013 24th International Conference on Information, Communication and Automation Technologies, ICAT 2013 - Sarajevo, Bosnia and Herzegovina
Duration: 30 Oct 201301 Nov 2013

Conference

Conference2013 24th International Conference on Information, Communication and Automation Technologies, ICAT 2013
CountryBosnia and Herzegovina
CitySarajevo
Period30/10/201301/11/2013

Keywords

  • Dynamic Sampling
  • Gaussian Processes
  • Plasma Etch
  • Virtual Metrology

ASJC Scopus subject areas

  • Computer Networks and Communications

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  • Cite this

    Wan, J., Honari, B., & McLoone, S. (2013). A dynamic sampling methodology for plasma etch processes using Gaussian process regression. In 2013 24th International Conference on Information, Communication and Automation Technologies, ICAT 2013 [6684080] IEEE Computer Society. https://doi.org/10.1109/ICAT.2013.6684080