Share Email Print

Proceedings Paper

Machine learning for fab automated diagnostics
Author(s): Manuel Giollo; Auguste Lam; Dimitra Gkorou; Xing Lan Liu; Richard van Haren
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Process optimization depends largely on field engineer’s knowledge and expertise. However, this practice turns out to be less sustainable due to the fab complexity which is continuously increasing in order to support the extreme miniaturization of Integrated Circuits. On the one hand, process optimization and root cause analysis of tools is necessary for a smooth fab operation. On the other hand, the growth in number of wafer processing steps is adding a considerable new source of noise which may have a significant impact at the nanometer scale. This paper explores the ability of historical process data and Machine Learning to support field engineers in production analysis and monitoring. We implement an automated workflow in order to analyze a large volume of information, and build a predictive model of overlay variation. The proposed workflow addresses significant problems that are typical in fab production, like missing measurements, small number of samples, confounding effects due to heterogeneity of data, and subpopulation effects. We evaluate the proposed workflow on a real usecase and we show that it is able to predict overlay excursions observed in Integrated Circuits manufacturing. The chosen design focuses on linear and interpretable models of the wafer history, which highlight the process steps that are causing defective products. This is a fundamental feature for diagnostics, as it supports process engineers in the continuous improvement of the production line.

Paper Details

Date Published: 28 September 2017
PDF: 8 pages
Proc. SPIE 10446, 33rd European Mask and Lithography Conference, 104460O (28 September 2017);
Show Author Affiliations
Manuel Giollo, ASML Netherlands B.V. (Netherlands)
Auguste Lam, STMicroelectronics (France)
Dimitra Gkorou, ASML Netherlands B.V. (Netherlands)
Xing Lan Liu, ASML Netherlands B.V. (Netherlands)
Richard van Haren, ASML Netherlands B.V. (Netherlands)

Published in SPIE Proceedings Vol. 10446:
33rd European Mask and Lithography Conference
Uwe F.W. Behringer; Jo Finders, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?