Using Unsupervised Machine Learning for Plasma Etching Endpoint Detection

Imen Chakroun; Thomas J. Ashby; Sayantan Das; Sandip Halder; Roel Wuyts; Wilfried Verachtert

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Paper

Using Unsupervised Machine Learning for Plasma Etching Endpoint Detection

Topics: Industry Related Applications

In Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods ICPRAM - Volume 1, 273-279, 2020 , Valletta, Malta

Authors: Imen Chakroun ¹ ; Thomas J. Ashby ¹ ; Sayantan Das ² ; Sandip Halder ² ; Roel Wuyts ¹ and Wilfried Verachtert ¹

Affiliations: ¹ Exascience Life Lab, IMEC, Leuven, Belgium ; ² Advanced patterning, IMEC, Leuven, Belgium

Keyword(s): Plasma Etch, Endpoint Detection, Principal Component Analysis, Clustering Algorithms.

Abstract: Much has been discussed around the advent of Industry 4.0 tools to improve yield across front-end and backend semiconductor manufacturers. One of these tools is the etch endpoint detection (EPD) systems. It is essential to optimize the etch process by precisely landing on the underlying layers, because over-etching can cause underlying layer damage. In this work, we explore unsupervised machine learning for automatically identifying the endpoint during plasma etching of low open-area wafers using optical emission spectroscopy.

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Paper citation in several formats:

Chakroun, I.; Ashby, T.; Das, S.; Halder, S.; Wuyts, R. and Verachtert, W. (2020). Using Unsupervised Machine Learning for Plasma Etching Endpoint Detection. In Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-397-1; ISSN 2184-4313, SciTePress, pages 273-279. DOI: 10.5220/0008877502730279

@conference{icpram20,
author={Imen Chakroun. and Thomas J. Ashby. and Sayantan Das. and Sandip Halder. and Roel Wuyts. and Wilfried Verachtert.},
title={Using Unsupervised Machine Learning for Plasma Etching Endpoint Detection},
booktitle={Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2020},
pages={273-279},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008877502730279},
isbn={978-989-758-397-1},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Using Unsupervised Machine Learning for Plasma Etching Endpoint Detection
SN - 978-989-758-397-1
IS - 2184-4313
AU - Chakroun, I.
AU - Ashby, T.
AU - Das, S.
AU - Halder, S.
AU - Wuyts, R.
AU - Verachtert, W.
PY - 2020
SP - 273
EP - 279
DO - 10.5220/0008877502730279
PB - SciTePress