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Proceedings Paper

Empirical models in semiconductor processing: optimization and assessment as simulators
Author(s): Steve W. Lavelle; David Wood; A. J. Hydes
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Paper Abstract

If any empirical model of an experimental system is to be used to make predictions its success as a simulator needs to be determined. This is especially so in semiconductor manufacturing where process runs are expensive making the need for a reliable process simulation even more important. With many current model assessment techniques, for example `coefficients of determination', too much information about the model's fit is hidden by the attempt to describe the model's success in terms of a single variable value. In this paper the description is given of a computational approach together with a standard visual display technique which allows the simulation capabilities of a model to be more fully understood. The method described is applicable to all modelling algorithms and as such allows the utility of competing modelling philosophies to be assessed.

Paper Details

Date Published: 15 February 1994
PDF: 8 pages
Proc. SPIE 2091, Microelectronic Processes, Sensors, and Controls, (15 February 1994); doi: 10.1117/12.167365
Show Author Affiliations
Steve W. Lavelle, Univ. of Durham (United Kingdom)
David Wood, Univ. of Durham (United Kingdom)
A. J. Hydes, Defence Research Agency (United Kingdom)


Published in SPIE Proceedings Vol. 2091:
Microelectronic Processes, Sensors, and Controls
Kiefer Elliott; John R. Hauser; James A. Bondur; Kiefer Elliott; John R. Hauser; Dim-Lee Kwong; Asit K. Ray; James A. Bondur, Editor(s)

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