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Proceedings Paper

Neural-network-based run-to-run controller using exposure and resist thickness adjustment
Author(s): Shane Geary; Ronan Barry
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Paper Abstract

This paper describes the development of a run-to-run control algorithm using a feedforward neural network, trained using the backpropagation training method. The algorithm is used to predict the critical dimension of the next lot using previous lot information. It is compared to a common prediction algorithm - the exponentially weighted moving average (EWMA) and is shown to give superior prediction performance in simulations. The manufacturing implementation of the final neural network showed significantly improved process capability when compared to the case where no run-to-run control was utilised.

Paper Details

Date Published: 1 July 2003
PDF: 11 pages
Proc. SPIE 5044, Advanced Process Control and Automation, (1 July 2003); doi: 10.1117/12.485298
Show Author Affiliations
Shane Geary, Analog Devices BV (Ireland)
Ronan Barry, Analog Devices BV (Ireland)


Published in SPIE Proceedings Vol. 5044:
Advanced Process Control and Automation
Matt Hankinson; Christopher P. Ausschnitt, Editor(s)

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