Intelligent risk-based maintenance approach for steam boilers: Real case
Maintenance acts as a significant role in smoothening the operations in power plants. Risk and failure are some of the common problems in power plant leading to unexpected outages such as boiler shutdown or tube leakage. The rectification of these problems requires ceasing operations of the boiler w...
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my.uniten.dspace-256272023-05-29T16:11:54Z Intelligent risk-based maintenance approach for steam boilers: Real case Fuzi N.F.A. Alnaimi F.B.I. Nasif M.S. 57211807166 58027086700 55188481100 Maintenance acts as a significant role in smoothening the operations in power plants. Risk and failure are some of the common problems in power plant leading to unexpected outages such as boiler shutdown or tube leakage. The rectification of these problems requires ceasing operations of the boiler which leads to a loss in the revenue annually. Therefore, this work was focused on prioritizing the maintenance activities and optimize the operational duration and cost by implementing risk-based maintenance (RBM) and particle swarm optimization (PSO). Previous literature implores that, RBM is commonly used in oil and gas industries to predict the risk or failure of the equipment. In this work, the RBM method was adopted accordingly to the power plant industries. The methodology is segregated into two main phases. First, the ranking and prioritization maintenance activities were performed using RBM. Then, the optimization of the operational duration and cost were simulated by PSO approached in MATLAB. The main outcome of this research is to act as a reference in adopting the best approaches to improve the power plant performance. � Universiti Putra Malaysia Press. Final 2023-05-29T08:11:54Z 2023-05-29T08:11:54Z 2020 Article 2-s2.0-85100188742 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100188742&partnerID=40&md5=2e0da6008127e7879e8b3243b3061afe https://irepository.uniten.edu.my/handle/123456789/25627 28 Special Issue 1 69 81 Universiti Putra Malaysia Press Scopus |
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Maintenance acts as a significant role in smoothening the operations in power plants. Risk and failure are some of the common problems in power plant leading to unexpected outages such as boiler shutdown or tube leakage. The rectification of these problems requires ceasing operations of the boiler which leads to a loss in the revenue annually. Therefore, this work was focused on prioritizing the maintenance activities and optimize the operational duration and cost by implementing risk-based maintenance (RBM) and particle swarm optimization (PSO). Previous literature implores that, RBM is commonly used in oil and gas industries to predict the risk or failure of the equipment. In this work, the RBM method was adopted accordingly to the power plant industries. The methodology is segregated into two main phases. First, the ranking and prioritization maintenance activities were performed using RBM. Then, the optimization of the operational duration and cost were simulated by PSO approached in MATLAB. The main outcome of this research is to act as a reference in adopting the best approaches to improve the power plant performance. � Universiti Putra Malaysia Press. |
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57211807166 Fuzi N.F.A. Alnaimi F.B.I. Nasif M.S. |
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Fuzi N.F.A. Alnaimi F.B.I. Nasif M.S. |
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Fuzi N.F.A. Alnaimi F.B.I. Nasif M.S. Intelligent risk-based maintenance approach for steam boilers: Real case |
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Fuzi N.F.A. |
title |
Intelligent risk-based maintenance approach for steam boilers: Real case |
title_short |
Intelligent risk-based maintenance approach for steam boilers: Real case |
title_full |
Intelligent risk-based maintenance approach for steam boilers: Real case |
title_fullStr |
Intelligent risk-based maintenance approach for steam boilers: Real case |
title_full_unstemmed |
Intelligent risk-based maintenance approach for steam boilers: Real case |
title_sort |
intelligent risk-based maintenance approach for steam boilers: real case |
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Universiti Putra Malaysia Press |
publishDate |
2023 |
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1806427297063895040 |
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13.19449 |