Machine learning for machine health monitoring in IoT
Maintenance has always been an integral part of today’s world. Constant breakage of machines with subsequent repairs have proven to be a huge toll economically. The evolution of maintenance has been present since many decades ago. Preventive maintenance for machines has been practiced till today....
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| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
2018
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| Online Access: | http://hdl.handle.net/10356/76359 |
| _version_ | 1826127896966594560 |
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| author | Chen, Wei Jie |
| author2 | Arindam Basu |
| author_facet | Arindam Basu Chen, Wei Jie |
| author_sort | Chen, Wei Jie |
| collection | NTU |
| description | Maintenance has always been an integral part of today’s world. Constant breakage of machines with subsequent repairs have proven to be a huge toll economically. The evolution of maintenance has been present since many decades ago.
Preventive maintenance for machines has been practiced till today. It is fairly successful but costly with regular maintenance to check for defects in the machine. With the advancement of technology, it is prudent to investigate newer ways of maintenance such as predictive maintenance where external systems are able to predict if the machine is going to be defective or not.
The project will combine machine learning with the specifications of the machines, and incorporate it into a system which can instantaneously predict the health of the machines. |
| first_indexed | 2024-10-01T07:16:22Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/76359 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:16:22Z |
| publishDate | 2018 |
| record_format | dspace |
| spelling | ntu-10356/763592023-07-07T17:32:43Z Machine learning for machine health monitoring in IoT Chen, Wei Jie Arindam Basu School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering Maintenance has always been an integral part of today’s world. Constant breakage of machines with subsequent repairs have proven to be a huge toll economically. The evolution of maintenance has been present since many decades ago. Preventive maintenance for machines has been practiced till today. It is fairly successful but costly with regular maintenance to check for defects in the machine. With the advancement of technology, it is prudent to investigate newer ways of maintenance such as predictive maintenance where external systems are able to predict if the machine is going to be defective or not. The project will combine machine learning with the specifications of the machines, and incorporate it into a system which can instantaneously predict the health of the machines. Bachelor of Engineering (Electrical and Electronic Engineering) 2018-12-20T03:10:38Z 2018-12-20T03:10:38Z 2018 Final Year Project (FYP) http://hdl.handle.net/10356/76359 en Nanyang Technological University 51 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Electrical and electronic engineering Chen, Wei Jie Machine learning for machine health monitoring in IoT |
| title | Machine learning for machine health monitoring in IoT |
| title_full | Machine learning for machine health monitoring in IoT |
| title_fullStr | Machine learning for machine health monitoring in IoT |
| title_full_unstemmed | Machine learning for machine health monitoring in IoT |
| title_short | Machine learning for machine health monitoring in IoT |
| title_sort | machine learning for machine health monitoring in iot |
| topic | DRNTU::Engineering::Electrical and electronic engineering |
| url | http://hdl.handle.net/10356/76359 |
| work_keys_str_mv | AT chenweijie machinelearningformachinehealthmonitoringiniot |