Metrology, which plays an important role in ensuring production quality in modern manufacturing industries, incurs substantial costs both in terms of the infrastructure required and the time needed to perform measurements. In particular, in the semiconductor manufacturing industry, measuring fundamental quantities on different sites of a wafer surface is associated with increased production time. To increase metrology efficiency, a typical strategy is to limit the number of sites measured and to exploit statistical models (soft sensing) to reconstruct the wafer profile. Moreover, for quality reasons, spatial dynamic sampling strategies may be employed to ensure that all regions of a wafer surface are checked periodically during production. In this paper, we propose a new sampling strategy, called induced start dynamic sampling (ISDS), which adapts greedy feature selection algorithms to the spatial dynamic sampling problem, such that the number of measured sites at each process run is m...

Induced Start Dynamic Sampling for Wafer Metrology Optimization

Susto G. A.;Maggipinto M.;
2020

Abstract

Metrology, which plays an important role in ensuring production quality in modern manufacturing industries, incurs substantial costs both in terms of the infrastructure required and the time needed to perform measurements. In particular, in the semiconductor manufacturing industry, measuring fundamental quantities on different sites of a wafer surface is associated with increased production time. To increase metrology efficiency, a typical strategy is to limit the number of sites measured and to exploit statistical models (soft sensing) to reconstruct the wafer profile. Moreover, for quality reasons, spatial dynamic sampling strategies may be employed to ensure that all regions of a wafer surface are checked periodically during production. In this paper, we propose a new sampling strategy, called induced start dynamic sampling (ISDS), which adapts greedy feature selection algorithms to the spatial dynamic sampling problem, such that the number of measured sites at each process run is m...
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3325148
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