Fadiel, A., Mohamad, M., Khalid, H., Esham, Y. (2025). The impact of using artificial intelligence techniques on the performance of turbine stations: A mini review. , 43(7), 536-545. doi: 10.30684/etj.2025.157633.1904
Ali F. A. Fadiel; Moktar A. H. Mohamad; Hafiez M. B. Khalid; Younis A. M Esham. "The impact of using artificial intelligence techniques on the performance of turbine stations: A mini review". , 43, 7, 2025, 536-545. doi: 10.30684/etj.2025.157633.1904
Fadiel, A., Mohamad, M., Khalid, H., Esham, Y. (2025). 'The impact of using artificial intelligence techniques on the performance of turbine stations: A mini review', , 43(7), pp. 536-545. doi: 10.30684/etj.2025.157633.1904
Fadiel, A., Mohamad, M., Khalid, H., Esham, Y. The impact of using artificial intelligence techniques on the performance of turbine stations: A mini review. , 2025; 43(7): 536-545. doi: 10.30684/etj.2025.157633.1904

The impact of using artificial intelligence techniques on the performance of turbine stations: A mini review

Engineering and Technology Journal
Volume 43, Issue 7, July 2025, Pages 536-545    PDF (534.67 K)
Document Type: Research Paper
DOI: 10.30684/etj.2025.157633.1904
Authors
Ali F. A. Fadiel* ; Moktar A. H. Mohamad; Hafiez M. B. Khalid; Younis A. M Esham
Department of Mechanical Engineering, Higher Institute of Science and Technology-Tobruk, Libya.
Abstract
This study aims to review the use of artificial intelligence applications in the management of gas turbine stations and their impact on enhancing and raising the efficiency of these stations, including managing the stations themselves, then improving operational efficiency, predicting faults, and developing strategies for road maintenance and precautionary maintenance while reducing the cost through a methodology that is a combination. One of several methodologies describes the factors that influence the enhancement of operational efficiency and management of turbine plants using artificial intelligence applications. The quantitative methodology in collecting data and studies that included the subject and the analytical and comparative methods in comparing studies and analyzing the most critical results reached, as the article relies on an analysis of scientific literature and recent studies to clarify the potential benefits and challenges associated with the application of artificial intelligence in this field. The review discusses the artificial intelligence tools employed, including machine learning and neural networks, and highlights future innovations that may enhance the efficiency of turbine systems. The study concludes by discussing current limitations and providing recommendations for research and development in this promising field. Most studies have indicated that artificial intelligence applications play a significant role in enhancing the management of gas turbine plants, increasing operational efficiency by 3 to 5%, and reducing operating costs by 8 to 15%.

Highlights
  • Using artificial intelligence applications in the management of gas turbine stations.
  • Turbines are subjected to high humidity, corrosion, and extreme temperatures.
  • Increased vibrations and stress on bearings, causing premature failures.
  • Preventive maintenance to avoid sudden failures through the scheduling of regular maintenance.
Keywords
Artificial intelligence applications; Gas turbines; Operational efficiency; Cost reduction; Management
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