15 February 1994 Empirical models in semiconductor processing: optimization and assessment as simulators
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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.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Steve W. Lavelle, Steve W. Lavelle, David Wood, David Wood, A. J. Hydes, A. J. Hydes, } "Empirical models in semiconductor processing: optimization and assessment as simulators", Proc. SPIE 2091, Microelectronic Processes, Sensors, and Controls, (15 February 1994); doi: 10.1117/12.167365; https://doi.org/10.1117/12.167365

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