Virtual metrology enabled early stage prediction for enhanced control of multi-stage fabrication processes

Gian Antonio Susto*, Adrian B. Johnston, Paul G. O'Hara, Sean McLoone

*Corresponding author for this work

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

15 Citations (Scopus)

Abstract

Semiconductor fabrication involves several sequential processing steps with the result that critical production variables are often affected by a superposition of affects over multiple steps. In this paper a Virtual Metrology (VM) system for early stage measurement of such variables is presented; the VM system seeks to express the contribution to the output variability that is due to a defined observable part of the production line. The outputs of the processed system may be used for process monitoring and control purposes. A second contribution of this work is the introduction of Elastic Nets, a regularization and variable selection technique for the modelling of highly-correlated datasets, as a technique for the development of VM models. Elastic Nets and the proposed VM system are illustrated using real data from a multi-stage etch process used in the fabrication of disk drive read/write heads.

Original languageEnglish
Title of host publicationIEEE International Conference on Automation Science and Engineering
Pages201-206
Number of pages6
DOIs
Publication statusPublished - 01 Dec 2013
Event2013 IEEE International Conference on Automation Science and Engineering, CASE 2013 - WI, Madison, United States
Duration: 17 Aug 201320 Aug 2013

Conference

Conference2013 IEEE International Conference on Automation Science and Engineering, CASE 2013
CountryUnited States
CityMadison
Period17/08/201320/08/2013

Keywords

  • Elastic Nets
  • LASSO
  • Regularization Methods
  • Ridge Regression
  • Semiconductor Manufacturing
  • System Identification
  • Virtual Metrology

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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  • Cite this

    Susto, G. A., Johnston, A. B., O'Hara, P. G., & McLoone, S. (2013). Virtual metrology enabled early stage prediction for enhanced control of multi-stage fabrication processes. In IEEE International Conference on Automation Science and Engineering (pp. 201-206). [6653980] https://doi.org/10.1109/CoASE.2013.6653980