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Article Dans Une Revue MathematicS In Action Année : 2022

Classifying and explaining defects with small data for the semiconductor industry

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Franck Corset
Franck Iutzeler
Jérôme Lelong

Résumé

In this work, we present an automatic classifier of wafer defects for the semiconductor industry. Hopefully defects are rare, but this puts the classifying problem in a small data context. We propose a fast and fully reproducible approach based on decision trees. The main interest of using decision trees lies in obtaining a highly explicable classifier, which makes the origin of the defect easy to identify.
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Dates et versions

hal-03544717 , version 1 (26-01-2022)

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Jean-François Boulanger, Franck Corset, Franck Iutzeler, Jérôme Lelong. Classifying and explaining defects with small data for the semiconductor industry. MathematicS In Action, 2022, 11 (1), pp.109-114. ⟨10.5802/msia.20⟩. ⟨hal-03544717⟩
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