Cover Image

PREDICTIVE ANALYTICS FOR EQUIPMENT FAILURE BY USING GATED RECURRENT UNIT – GENETIC ALGORITHM (GRU – GA)

Failure is described as an inability to attain a desired goal and acknowledged to be contradictory with success. It is a scenario that happens frequently across several industries and results in either minor or severe consequences such as maintenance expenses, production disruption and safety concer...

Full description

Saved in:
Bibliographic Details
Main Author: ZAINUDDIN, ZAHIRAH
Format: Thesis
Language:English
Published: 2023
Subjects:
T Technology (General)
Online Access:http://utpedia.utp.edu.my/id/eprint/24633/1/ZahirahZainuddin_18003491.pdf
http://utpedia.utp.edu.my/id/eprint/24633/
Tags: Add Tag
No Tags, Be the first to tag this record!
id oai:utpedia.utp.edu.my:24633
record_format eprints
spelling oai:utpedia.utp.edu.my:246332023-06-30T03:06:29Z http://utpedia.utp.edu.my/id/eprint/24633/ PREDICTIVE ANALYTICS FOR EQUIPMENT FAILURE BY USING GATED RECURRENT UNIT – GENETIC ALGORITHM (GRU – GA) ZAINUDDIN, ZAHIRAH T Technology (General) Failure is described as an inability to attain a desired goal and acknowledged to be contradictory with success. It is a scenario that happens frequently across several industries and results in either minor or severe consequences such as maintenance expenses, production disruption and safety concerns. The reasons behind this issue are always related to improper predictive maintenance, prolonged equipment operating hours and many other factors. Hence, the issue can be solved by adopting a prediction activity to monitor and predict the state of equipment in advance. Prediction predicts the upcoming instance by evaluating the assertions obtained from the gears. In this case, Deep Learning (DL) is chosen to construct the prediction activity for estimating the life expectancy of an equipment. Gated Recurrent Unit (GRU) algorithm is used to cater the predicting action of equipment state based on data from an oil and gas industry. 2023-01 Thesis NonPeerReviewed text en http://utpedia.utp.edu.my/id/eprint/24633/1/ZahirahZainuddin_18003491.pdf ZAINUDDIN, ZAHIRAH (2023) PREDICTIVE ANALYTICS FOR EQUIPMENT FAILURE BY USING GATED RECURRENT UNIT – GENETIC ALGORITHM (GRU – GA). Masters thesis, UNSPECIFIED.
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Electronic and Digitized Intellectual Asset
url_provider http://utpedia.utp.edu.my/
language English
topic T Technology (General)
spellingShingle T Technology (General)
ZAINUDDIN, ZAHIRAH
PREDICTIVE ANALYTICS FOR EQUIPMENT FAILURE BY USING GATED RECURRENT UNIT – GENETIC ALGORITHM (GRU – GA)
description Failure is described as an inability to attain a desired goal and acknowledged to be contradictory with success. It is a scenario that happens frequently across several industries and results in either minor or severe consequences such as maintenance expenses, production disruption and safety concerns. The reasons behind this issue are always related to improper predictive maintenance, prolonged equipment operating hours and many other factors. Hence, the issue can be solved by adopting a prediction activity to monitor and predict the state of equipment in advance. Prediction predicts the upcoming instance by evaluating the assertions obtained from the gears. In this case, Deep Learning (DL) is chosen to construct the prediction activity for estimating the life expectancy of an equipment. Gated Recurrent Unit (GRU) algorithm is used to cater the predicting action of equipment state based on data from an oil and gas industry.
format Thesis
author ZAINUDDIN, ZAHIRAH
author_facet ZAINUDDIN, ZAHIRAH
author_sort ZAINUDDIN, ZAHIRAH
title PREDICTIVE ANALYTICS FOR EQUIPMENT FAILURE BY USING GATED RECURRENT UNIT – GENETIC ALGORITHM (GRU – GA)
title_short PREDICTIVE ANALYTICS FOR EQUIPMENT FAILURE BY USING GATED RECURRENT UNIT – GENETIC ALGORITHM (GRU – GA)
title_full PREDICTIVE ANALYTICS FOR EQUIPMENT FAILURE BY USING GATED RECURRENT UNIT – GENETIC ALGORITHM (GRU – GA)
title_fullStr PREDICTIVE ANALYTICS FOR EQUIPMENT FAILURE BY USING GATED RECURRENT UNIT – GENETIC ALGORITHM (GRU – GA)
title_full_unstemmed PREDICTIVE ANALYTICS FOR EQUIPMENT FAILURE BY USING GATED RECURRENT UNIT – GENETIC ALGORITHM (GRU – GA)
title_sort predictive analytics for equipment failure by using gated recurrent unit – genetic algorithm (gru – ga)
publishDate 2023
url http://utpedia.utp.edu.my/id/eprint/24633/1/ZahirahZainuddin_18003491.pdf
http://utpedia.utp.edu.my/id/eprint/24633/
_version_ 1770553574346981376
score 13.250246

Similar Items