Prediction of Remaining Useful Life (RUL) in Refinery using Deep Learning

The Remaining Useful Life (RUL) is typically used as the process of predicting the life span of machine before its failure. The purpose of this project is to develop a predictive analysis system of Remaining Useful Life (RUL) in refinery. It will significantly help the oil and gas industry to...

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Main Author: Baharadin, Hazirah
Format: Final Year Project
Language: English
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-utpedia.20901 /
Published: IRC 2019
Subjects:
Q Science (General)
Online Access: http://utpedia.utp.edu.my/20901/1/Hazirah_22882.pdf
http://utpedia.utp.edu.my/20901/
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id utp-utpedia.20901
recordtype eprints
spelling utp-utpedia.209012021-09-09T19:57:49Z http://utpedia.utp.edu.my/20901/ Prediction of Remaining Useful Life (RUL) in Refinery using Deep Learning Baharadin, Hazirah Q Science (General) The Remaining Useful Life (RUL) is typically used as the process of predicting the life span of machine before its failure. The purpose of this project is to develop a predictive analysis system of Remaining Useful Life (RUL) in refinery. It will significantly help the oil and gas industry to schedule a replacement or maintenance before the machines end its operation. The project is developed using Deep Learning algorithm which the functionality can be found in KNIME Analytic application. The analysis dashboard by using Microsoft Power BI which will integrate with KNIME Application, an artificial intelligence tool, will assist engineers to make informed decision to replace or need maintenance at the end of its remaining useful life of the machines IRC 2019-09 Final Year Project NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/20901/1/Hazirah_22882.pdf Baharadin, Hazirah (2019) Prediction of Remaining Useful Life (RUL) in Refinery using Deep Learning. IRC, Universiti Teknologi PETRONAS. (Submitted)
institution Universiti Teknologi Petronas
collection UTPedia
language English
topic Q Science (General)
spellingShingle Q Science (General)
Baharadin, Hazirah
Prediction of Remaining Useful Life (RUL) in Refinery using Deep Learning
description The Remaining Useful Life (RUL) is typically used as the process of predicting the life span of machine before its failure. The purpose of this project is to develop a predictive analysis system of Remaining Useful Life (RUL) in refinery. It will significantly help the oil and gas industry to schedule a replacement or maintenance before the machines end its operation. The project is developed using Deep Learning algorithm which the functionality can be found in KNIME Analytic application. The analysis dashboard by using Microsoft Power BI which will integrate with KNIME Application, an artificial intelligence tool, will assist engineers to make informed decision to replace or need maintenance at the end of its remaining useful life of the machines
format Final Year Project
author Baharadin, Hazirah
author_sort Baharadin, Hazirah
title Prediction of Remaining Useful Life (RUL) in Refinery using Deep Learning
title_short Prediction of Remaining Useful Life (RUL) in Refinery using Deep Learning
title_full Prediction of Remaining Useful Life (RUL) in Refinery using Deep Learning
title_fullStr Prediction of Remaining Useful Life (RUL) in Refinery using Deep Learning
title_full_unstemmed Prediction of Remaining Useful Life (RUL) in Refinery using Deep Learning
title_sort prediction of remaining useful life (rul) in refinery using deep learning
publisher IRC
publishDate 2019
url http://utpedia.utp.edu.my/20901/1/Hazirah_22882.pdf
http://utpedia.utp.edu.my/20901/
_version_ 1741195679594708992
score 11.62408

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