A comparison of supervisory control algorithms for tool/process disturbance tracking

Author

Braun, M.W. ; Jenkins, S.T. ; Patel, N.S.

Author_Institution

Texas Instrum. Inc., Dallas, TX, USA

Volume

3

fYear

2003

fDate

4-6 June 2003

Firstpage

2626

Abstract

The performance of four supervisory algorithms: segregated exponentially weighted moving average, exponentially weighted moving average, adaptive exponentially weighted moving average, and recursive least squares, are compared in Monte-Carlo simulation of an example system dataset, as well as on real industrial data from a photolithography process. Advantages and disadvantages of the algorithms are compared with specific focus on practical issues of interest to the user.

Keywords

Monte Carlo methods; least mean squares methods; moving average processes; photolithography; process control; recursive estimation; semiconductor device manufacture; Monte Carlo simulation; adaptive exponentially weighted moving average; photolithography process; process disturbance tracking; recursive least squares; segregated exponentially weighted moving average; supervisory control; system dataset; tool disturbance tracking; Conductors; Electrical equipment industry; Filtering algorithms; Instruments; Integrated circuit modeling; Least squares methods; Lithography; Profitability; Signal processing algorithms; Supervisory control;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference, 2003. Proceedings of the 2003

ISSN

0743-1619

Print_ISBN

0-7803-7896-2

Type

conf

DOI

10.1109/ACC.2003.1243473

Filename

1243473