Machine learning in industry 4.0

Machine learning and data analysis are crucial for improving the quality of Industry 4.0enabled manufacturing systems. This research aims to identify important parameters and develop machine learning models for predicting quality and system failure in industrial settings.The Singapore Institute of M...

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Main Author: Mohamed Usman S/O Kaligul Zaman
Other Authors: Kedar Hippalgaonkar
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2023
Subjects:
Online Access:https://hdl.handle.net/10356/167004
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1670042023-05-20T16:45:33Z Machine learning in industry 4.0 Mohamed Usman S/O Kaligul Zaman Kedar Hippalgaonkar School of Materials Science and Engineering kedar@ntu.edu.sg Engineering::Materials Machine learning and data analysis are crucial for improving the quality of Industry 4.0enabled manufacturing systems. This research aims to identify important parameters and develop machine learning models for predicting quality and system failure in industrial settings.The Singapore Institute of Manufacturing Technologies (SIMTech) at A*STAR will serve as the research site. Bachelor of Engineering (Materials Engineering) 2023-05-20T13:46:34Z 2023-05-20T13:46:34Z 2023 Final Year Project (FYP) Mohamed Usman S/O Kaligul Zaman (2023). Machine learning in industry 4.0. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/167004 https://hdl.handle.net/10356/167004 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::Materials
spellingShingle Engineering::Materials
Mohamed Usman S/O Kaligul Zaman
Machine learning in industry 4.0
description Machine learning and data analysis are crucial for improving the quality of Industry 4.0enabled manufacturing systems. This research aims to identify important parameters and develop machine learning models for predicting quality and system failure in industrial settings.The Singapore Institute of Manufacturing Technologies (SIMTech) at A*STAR will serve as the research site.
author2 Kedar Hippalgaonkar
author_facet Kedar Hippalgaonkar
Mohamed Usman S/O Kaligul Zaman
format Final Year Project
author Mohamed Usman S/O Kaligul Zaman
author_sort Mohamed Usman S/O Kaligul Zaman
title Machine learning in industry 4.0
title_short Machine learning in industry 4.0
title_full Machine learning in industry 4.0
title_fullStr Machine learning in industry 4.0
title_full_unstemmed Machine learning in industry 4.0
title_sort machine learning in industry 4.0
publisher Nanyang Technological University
publishDate 2023
url https://hdl.handle.net/10356/167004
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