An Assessment of Local Geometric Uncertainties in Polysilicon MEMS: A Genetic Algorithm and POD-Kriging Surrogate Modeling Approach

On the way toward MEMS miniaturization, the quantification of geometric uncertainties stands as a primary challenge. In this paper, an approach that combines genetic algorithms and proper orthogonal decomposition with kriging surrogate modeling was proposed to accurately predict over-etch measures t...

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Bibliographic Details

Published in:	Micromachines
Main Authors:	Ananya Roy, Francesco Rizzini, Gabriele Gattere, Carlo Valzasina, Aldo Ghisi, Stefano Mariani
Format:	Article
Language:	English
Published:	MDPI AG 2025-01-01
Subjects:	micro electro-mechanical systems (MEMS) over-etching uncertainty quantification proper orthogonal decomposition (POD) kriging interpolation genetic algorithm (GA)
Online Access:	https://www.mdpi.com/2072-666X/16/2/127