Process control and predictive model for machine data in epitaxy growths

Semiconductor epitaxy growths are very popular in microfabrication and optoelectronic devices fabrications. In the epitaxy process, reactors generate a lot of data every second. This data could be used to improve processes through automation and analytics. This report proposes practical solutions/pr...

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Main Author:	Sim, Stanley Jia Yi
Other Authors:	Tang Xiaohong
Format:	Final Year Project
Language:	English
Published:	Nanyang Technological University 2021
Subjects:	Engineering::Electrical and electronic engineering::Semiconductors
Online Access:	https://hdl.handle.net/10356/150450
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Institution:	Nanyang Technological University
Language:	English

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spelling	sg-ntu-dr.10356-1504502023-07-07T18:21:44Z Process control and predictive model for machine data in epitaxy growths Sim, Stanley Jia Yi Tang Xiaohong School of Electrical and Electronic Engineering EXHTang@ntu.edu.sg Engineering::Electrical and electronic engineering::Semiconductors Semiconductor epitaxy growths are very popular in microfabrication and optoelectronic devices fabrications. In the epitaxy process, reactors generate a lot of data every second. This data could be used to improve processes through automation and analytics. This report proposes practical solutions/proof-of-concepts that are showcased with the wealth of open-source resources readily available online namely- Google Cloud Platform (free tier/credits) for automation and analytics, and Python libraries such as Numpy, Pandas and TensorFlow/Keras for data processing and machine learning. Bachelor of Engineering (Electrical and Electronic Engineering) 2021-06-13T14:25:48Z 2021-06-13T14:25:48Z 2021 Final Year Project (FYP) Sim, S. J. Y. (2021). Process control and predictive model for machine data in epitaxy growths. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/150450 https://hdl.handle.net/10356/150450 en application/pdf Nanyang Technological University
institution	Nanyang Technological University
building	NTU Library
continent	Asia
country	Singapore Singapore
content_provider	NTU Library
collection	DR-NTU
language	English
topic	Engineering::Electrical and electronic engineering::Semiconductors
spellingShingle	Engineering::Electrical and electronic engineering::Semiconductors Sim, Stanley Jia Yi Process control and predictive model for machine data in epitaxy growths
description	Semiconductor epitaxy growths are very popular in microfabrication and optoelectronic devices fabrications. In the epitaxy process, reactors generate a lot of data every second. This data could be used to improve processes through automation and analytics. This report proposes practical solutions/proof-of-concepts that are showcased with the wealth of open-source resources readily available online namely- Google Cloud Platform (free tier/credits) for automation and analytics, and Python libraries such as Numpy, Pandas and TensorFlow/Keras for data processing and machine learning.
author2	Tang Xiaohong
author_facet	Tang Xiaohong Sim, Stanley Jia Yi
format	Final Year Project
author	Sim, Stanley Jia Yi
author_sort	Sim, Stanley Jia Yi
title	Process control and predictive model for machine data in epitaxy growths
title_short	Process control and predictive model for machine data in epitaxy growths
title_full	Process control and predictive model for machine data in epitaxy growths
title_fullStr	Process control and predictive model for machine data in epitaxy growths
title_full_unstemmed	Process control and predictive model for machine data in epitaxy growths
title_sort	process control and predictive model for machine data in epitaxy growths
publisher	Nanyang Technological University
publishDate	2021
url	https://hdl.handle.net/10356/150450
_version_	1772828116087996416

Process control and predictive model for machine data in epitaxy growths

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