Advanced maintenance strategies for energy infrastructure: Lessons for optimizing rotating machinery
1 Independent Researcher, Nigeria.
2 Chevron Nigeria Limited, Nigeria.
3 Independent Researcher, Lagos Nigeria.
Review Article
Global Journal of Research in Science and Technology, 2024, 02(02), 065–093.
Article DOI: 10.58175/gjrst.2024.2.2.0073
Publication history:
Received 07 September 2024; revised on 16 October 2024; accepted on 19 October 2024
Abstract:
The reliability and efficiency of energy infrastructure depend heavily on the performance of rotating machinery, such as turbines, compressors, and pumps. Advanced maintenance strategies, particularly predictive and condition-based maintenance, have emerged as crucial approaches for optimizing the operational performance and lifespan of such machinery. This paper explores key lessons learned from implementing these advanced strategies in energy infrastructure, with a focus on how they can enhance system reliability, reduce downtime, and lower maintenance costs. By integrating digital technologies such as the Internet of Things (IoT), artificial intelligence (AI), and machine learning (ML), maintenance can be more accurately forecasted, enabling preemptive action before machinery failure occurs. The role of real-time monitoring systems and the use of vibration analysis, thermal imaging, and acoustic monitoring as diagnostic tools are examined in detail. Additionally, the paper delves into the challenges associated with the implementation of these strategies, including the need for skilled personnel, the high costs of sensor deployment, and the integration of data from diverse sources. However, despite these challenges, case studies of energy firms that have adopted advanced maintenance strategies demonstrate significant improvements in operational efficiency and machinery uptime. Lessons from industries that rely on rotating machinery, such as oil and gas, power generation, and renewable energy sectors, are highlighted, underscoring the importance of continuous innovation in maintenance techniques. The paper concludes by providing recommendations for organizations looking to optimize their rotating machinery, including prioritizing the deployment of predictive maintenance technologies, fostering collaboration between maintenance and IT departments, and continuously training personnel in the latest diagnostic tools. Ultimately, advanced maintenance strategies present a pathway for energy companies to improve asset management, enhance sustainability, and minimize the risk of unexpected failures.
Keywords:
Advanced Maintenance Strategies; Rotating Machinery; Energy Infrastructure; Predictive Maintenance; Condition-Based Maintenance; Internet of Things (Iot); Artificial Intelligence (AI); Machine Learning (ML); Real-Time Monitoring; Operational Efficiency.
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0