Ensuring the Reliability of Gas Supply Systems by Optimizing the Overhaul Planning
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Marina Efthymiou & Katie McCarthy & Chris Markou & John F. O’Connell, 2022. "An Exploratory Research on Blockchain in Aviation: The Case of Maintenance, Repair and Overhaul (MRO) Organizations," Sustainability, MDPI, vol. 14(5), pages 1-17, February.
- Huynh, K.T., 2020. "Modeling past-dependent partial repairs for condition-based maintenance of continuously deteriorating systems," European Journal of Operational Research, Elsevier, vol. 280(1), pages 152-163.
- Martí de Castro-Cros & Manel Velasco & Cecilio Angulo, 2021. "Machine-Learning-Based Condition Assessment of Gas Turbines—A Review," Energies, MDPI, vol. 14(24), pages 1-27, December.
- Cabrales, Sergio & Valencia, Carlos & Ramírez, Carlos & Ramírez, Andrés & Herrera, Juan & Cadena, Angela, 2022. "Stochastic cost-benefit analysis to assess new infrastructure to improve the reliability of the natural gas supply," Energy, Elsevier, vol. 246(C).
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Ayman AboElHassan & Soumaya Yacout, 2023. "A digital shadow framework using distributed system concepts," Journal of Intelligent Manufacturing, Springer, vol. 34(8), pages 3579-3598, December.
- Navarro, Jorge & Fernández-Martínez, Pedro, 2021. "Redundancy in systems with heterogeneous dependent components," European Journal of Operational Research, Elsevier, vol. 290(2), pages 766-778.
- Huynh, K.T., 2021. "An adaptive predictive maintenance model for repairable deteriorating systems using inverse Gaussian degradation process," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
- Jacek Czyżewicz & Piotr Jaskólski & Paweł Ziemiański & Marian Piwowarski & Mateusz Bortkiewicz & Krzysztof Laszuk & Ireneusz Galara & Marta Pawłowska & Karol Cybulski, 2022. "Towards Designing an Innovative Industrial Fan: Developing Regression and Neural Models Based on Remote Mass Measurements," Energies, MDPI, vol. 15(7), pages 1-19, March.
- Castro, Inma T. & Basten, Rob J.I. & van Houtum, Geert-Jan, 2020. "Maintenance cost evaluation for heterogeneous complex systems under continuous monitoring," Reliability Engineering and System Safety, Elsevier, vol. 200(C).
- Cheng, Xianda & Zheng, Haoran & Yang, Qian & Zheng, Peiying & Dong, Wei, 2023. "Surrogate model-based real-time gas path fault diagnosis for gas turbines under transient conditions," Energy, Elsevier, vol. 278(PA).
- Renxi Gong & Siqiang Li & Weiyu Peng, 2020. "Research on Multi-Attribute Decision-Making in Condition-Based Maintenance for Power Transformers Based on Cloud and Kernel Vector Space Models," Energies, MDPI, vol. 13(22), pages 1-11, November.
- Huynh, K.T. & Vu, H.C. & Nguyen, T.D. & Ho, A.C., 2022. "A predictive maintenance model for k-out-of-n:F continuously deteriorating systems subject to stochastic and economic dependencies," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
- Loraine Brown & Marina Efthymiou & Caroline McMullan, 2022. "Recovering from a Major Aviation Disaster: The Airlines’ Family Assistance Centre," Sustainability, MDPI, vol. 14(7), pages 1-16, March.
- Bautista, Lucía & Castro, Inma T. & Landesa, Luis, 2022. "Condition-based maintenance for a system subject to multiple degradation processes with stochastic arrival intensity," European Journal of Operational Research, Elsevier, vol. 302(2), pages 560-574.
- Nicola Menga & Akhila Mothakani & Maria Grazia De Giorgi & Radoslaw Przysowa & Antonio Ficarella, 2022. "Extreme Learning Machine-Based Diagnostics for Component Degradation in a Microturbine," Energies, MDPI, vol. 15(19), pages 1-22, October.
- Yanzheng Liu & Jicong Tan & Zhao Wei & Ying Zhu & Shiyu Chang & Yexin Li & Shaoyi Li & Yong Guo, 2024. "Analysis of Extreme Random Uncertainty in Energy and Environment Systems for Coal-Dependent City by a Copula-Based Interval Cost–Benefit Stochastic Approach," Sustainability, MDPI, vol. 16(2), pages 1-22, January.
- Hu, Jiawen & Shen, Jingyuan & Shen, Lijuan, 2020. "Opportunistic maintenance for two-component series systems subject to dependent degradation and shock," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
- Seungju Nam & Sejong Choi & Georgia Edell & Amartya De & Woon-Kyung Song, 2023. "Comparative Analysis of the Aviation Maintenance, Repair, and Overhaul (MRO) Industry in Northeast Asian Countries: A Suggestion for the Development of Korea’s MRO Industry," Sustainability, MDPI, vol. 15(2), pages 1-15, January.
More about this item
Keywords
compressor station; energy source; energy efficiency; operational reliability;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:16:y:2023:i:2:p:986-:d:1036986. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.