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...
محفوظ في:
| المؤلف الرئيسي: | |
|---|---|
| التنسيق: | أطروحة |
| اللغة: | English |
| منشور في: |
2023
|
| الموضوعات: | |
| الوصول للمادة أونلاين: | http://utpedia.utp.edu.my/id/eprint/24633/1/ZahirahZainuddin_18003491.pdf http://utpedia.utp.edu.my/id/eprint/24633/ |
| الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
|
| 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 |