Development of Advanced Predictive Maintenance System
Unplanned or unnecessary maintenance of the equipment and instruments leads to waste of money and time in production or manufacturing plants. Current predictive maintenance techniques make use of offline data and basic prognostics tools that provide insufficiently accurate predictions. Moreover, exi...
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| Format: | Final Year Project |
| Language: | English |
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IRC
2019
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| Online Access: | http://utpedia.utp.edu.my/id/eprint/20133/1/Final%20Dissertation.pdf http://utpedia.utp.edu.my/id/eprint/20133/ |
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oai:utpedia.utp.edu.my:201332023-03-17T03:44:48Z http://utpedia.utp.edu.my/id/eprint/20133/ Development of Advanced Predictive Maintenance System Babakulyyev, Rustam Unplanned or unnecessary maintenance of the equipment and instruments leads to waste of money and time in production or manufacturing plants. Current predictive maintenance techniques make use of offline data and basic prognostics tools that provide insufficiently accurate predictions. Moreover, existing predictive maintenance systems developed by external vendors are only accessible by large firms due to their high price. This project was initiated to develop an online, open-source and relatively accurate predictive maintenance system that employs Autoregressive Moving Average (ARMA) statistical prognostics method for small-sized companies that aim to supply products with the least waste of time and money in the process. In this project, the proposed system was applied on 5 cases including current, voltage, active power, cold air temperature and discharge pressure of a process plant. IRC 2019 Final Year Project NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/id/eprint/20133/1/Final%20Dissertation.pdf Babakulyyev, Rustam (2019) Development of Advanced Predictive Maintenance System. [Final Year Project] (Submitted) |
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Universiti Teknologi Petronas |
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UTP Resource Centre |
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| continent |
Asia |
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Malaysia |
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Universiti Teknologi Petronas |
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http://utpedia.utp.edu.my/ |
| language |
English |
| description |
Unplanned or unnecessary maintenance of the equipment and instruments leads to waste of money and time in production or manufacturing plants. Current predictive maintenance techniques make use of offline data and basic prognostics tools that provide insufficiently accurate predictions. Moreover, existing predictive maintenance systems developed by external vendors are only accessible by large firms due to their high price. This project was initiated to develop an online, open-source and relatively accurate predictive maintenance system that employs Autoregressive Moving Average (ARMA) statistical prognostics method for small-sized companies that aim to supply products with the least waste of time and money in the process.
In this project, the proposed system was applied on 5 cases including current, voltage, active power, cold air temperature and discharge pressure of a process plant. |
| format |
Final Year Project |
| author |
Babakulyyev, Rustam |
| spellingShingle |
Babakulyyev, Rustam Development of Advanced Predictive Maintenance System |
| author_facet |
Babakulyyev, Rustam |
| author_sort |
Babakulyyev, Rustam |
| title |
Development of Advanced Predictive Maintenance System |
| title_short |
Development of Advanced Predictive Maintenance System |
| title_full |
Development of Advanced Predictive Maintenance System |
| title_fullStr |
Development of Advanced Predictive Maintenance System |
| title_full_unstemmed |
Development of Advanced Predictive Maintenance System |
| title_sort |
development of advanced predictive maintenance system |
| publisher |
IRC |
| publishDate |
2019 |
| url |
http://utpedia.utp.edu.my/id/eprint/20133/1/Final%20Dissertation.pdf http://utpedia.utp.edu.my/id/eprint/20133/ |
| _version_ |
1761620909198671872 |
| score |
13.211869 |