TCAD-Enabled Machine Learning—An Efficient Framework to Build Highly Accurate and Reliable Models for Semiconductor Technology Development and Fabrication-Reference-Cited by-同舟云学术

TCAD-Enabled Machine Learning—An Efficient Framework to Build Highly Accurate and Reliable Models for Semiconductor Technology Development and Fabrication

Published:2023-05 Issue:2 Volume:36 Page:268-278
ISSN:0894-6507
Container-title:IEEE Transactions on Semiconductor Manufacturing
language:
Short-container-title:IEEE Trans. Semicond. Manufact.

Author:

Jungmann Paul¹^ORCID,Johnson Jeffrey B.²,Silva Eduardo C.²^ORCID,Taylor William²,Khan Abdul Hanan²,Kumar Akash³^ORCID

Affiliation:

1. Yield Engineering, GlobalFoundries Inc., Dresden, Germany

2. Global Engineering, GlobalFoundries Inc., Malta, NY, USA

3. Chair for Processor Design and Germany and the Center for Advancing Electronics Dresden, Technische Universität Dresden, Dresden, Germany

Funder

Freistaat Sachsen

European Funds for Regional Development (EFRE) through Project ARAMID

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Condensed Matter Physics,Electronic, Optical and Magnetic Materials

Link

http://xplorestaging.ieee.org/ielx7/66/10119187/10035476.pdf?arnumber=10035476

Reference49 articles.

1. A Literature Review on Sampling Techniques in Semiconductor Manufacturing

2. A review of yield modelling techniques for semiconductor manufacturing

3. Real-Time TCAD: a new paradigm for TCAD in the artificial intelligence era

4. From Moore's Law to Function Density Law

5. An overview of manufacturing yield and reliability modeling for semiconductor products

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