B.J. Bombay

EECS Department, University of California, Berkeley

Technical Report No. UCB/ERL M92/113

, 1992

http://www2.eecs.berkeley.edu/Pubs/TechRpts/1992/ERL-92-113.pdf

Accurate control and monitoring of manufacturing equipment is essential to integrated circuit production. Such a control scheme can take advantage of equipment models for the various steps involved in the production process. Unfortunately, the equipment used in integrated circuit manufacturing often changes with time and is always subject to various disturbances which in turn introduce significant fluctuation in performance. This report includes an adaptive regression model which evaluates itself and determines whether it should be corrected to better reflect equipment behavior. The model is modified through recursive estimation based on in-line wafer measurements. Decisions for model changes are based on formal statistical tests which use the principles of the regression control chart. This strategy has been tested on the photolithography sequence in the Berkeley Microfabrication Laboratory. In addition, a control scheme has been implemented which uses equipment models for feedback and feed-forward control of a manufacturing workcell. Included in this implementation are editing and generation functions for equipment setting recipes, a model editor, and interfaces to other Berkeley Computer-Aided Manufacturing (BCAM) applications. This implementation, named the BCAM Control and Monitoring Environment, is described in this thesis. Also included in this report are an instruction manual for use of the environment and a programming manual for further development of the code.

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BibTeX citation:

@techreport{Bombay:M92/113,
    Author= {Bombay, B.J.},
    Title= {The BCAM Control and Monitoring Environment},
    Year= {1992},
    Month= {Sep},
    Url= {http://www2.eecs.berkeley.edu/Pubs/TechRpts/1992/2186.html},
    Number= {UCB/ERL M92/113},
    Abstract= {Accurate control and monitoring of manufacturing equipment is
essential to integrated circuit production. Such a control scheme can
take advantage of equipment models for the various steps involved
in the production process. Unfortunately, the equipment used in
integrated circuit manufacturing often changes with time and is
always subject to various disturbances which in turn introduce
significant fluctuation in performance. This report includes an
adaptive regression model which evaluates itself and determines
whether it should be corrected to better reflect equipment
behavior. The model is modified through recursive estimation
based on in-line wafer measurements. Decisions for model changes
are based on formal statistical tests which use the principles
of the regression control chart. This strategy has been tested
on the photolithography sequence in the Berkeley Microfabrication
Laboratory. In addition, a control scheme has been implemented which
uses equipment models for feedback and feed-forward control of a
manufacturing workcell. Included in this implementation are editing
and generation functions for equipment setting recipes, a model
editor, and interfaces to other Berkeley Computer-Aided Manufacturing
(BCAM) applications. This implementation, named the BCAM Control and
Monitoring Environment, is described in this thesis. Also included
in this report are an instruction manual for use of the environment
and a programming manual for further development of the code.},
}

EndNote citation:

%0 Report
%A Bombay, B.J. 
%T The BCAM Control and Monitoring Environment
%I EECS Department, University of California, Berkeley
%D 1992
%@ UCB/ERL M92/113
%U http://www2.eecs.berkeley.edu/Pubs/TechRpts/1992/2186.html
%F Bombay:M92/113