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Reliability, Availability, and Maintainability Assessment-Based Sustainability-Informed Maintenance Optimization in Power Transmission Networks

Author

Listed:
  • Motahareh Sagharidooz

    (Department of Management, Faculty of Economics and Administrative Sciences, Ferdowsi University of Mashhad, Mashhad 9177948974, Iran)

  • Hamzeh Soltanali

    (Department of Industrial Engineering, Imam Hossein University, Tehran 1698715861, Iran)

  • José Torres Farinha

    (RCM2+ Research Centre for Asset Management and Systems Engineering, Polytechnic Institute of Coimbra, Coimbra Institute of Engineering, Rua Pedro Nunes—Quinta da Nora, 3030-199 Coimbra, Portugal)

  • Hugo D. N. Raposo

    (RCM2+ Research Centre for Asset Management and Systems Engineering, Polytechnic Institute of Coimbra, Coimbra Institute of Engineering, Rua Pedro Nunes—Quinta da Nora, 3030-199 Coimbra, Portugal)

  • José Edmundo de-Almeida-e-Pais

    (RCM2+ Research Centre for Asset Management and Systems Engineering, Polytechnic Institute of Coimbra, Coimbra Institute of Engineering, Rua Pedro Nunes—Quinta da Nora, 3030-199 Coimbra, Portugal
    RCM2+ Research Centre for Asset Management and Systems Engineering, Lusófona University, Campo Grande 376, 1749-024 Lisboa, Portugal
    CISE—Electromechatronic Systems Research Centre, University of Beira Interior, 6201-001 Covilhã, Portugal)

Abstract

Reliable and resilient power transmission networks serve as vital for sustainable development and uninterrupted electricity supply. Effective maintenance programs are necessary to comply with reliability and sustainability requirements in the power sector. To that end, RAM (reliability, availability, and maintainability) assessments can provide efficient maintenance services that minimize adverse consequences and increase productivity at the lowest possible cost. We employ a statistical framework to evaluate RAM principles, including data acquisition, homogenization, trend hypothesis validation, and parameter estimation. The RAM evaluation of power transmission networks identifies primary bottlenecks in subsystems based on failure and repair behavior trends, which should be prioritized. To find the optimal maintenance policies for each subsystem, we adapt a Multi-Attribute Utility Theory (MAUT) approach, taking costs, availability, and dependability into account. The results of this approach can help improve the operational performance and sustainability of power transmission networks.

Suggested Citation

  • Motahareh Sagharidooz & Hamzeh Soltanali & José Torres Farinha & Hugo D. N. Raposo & José Edmundo de-Almeida-e-Pais, 2024. "Reliability, Availability, and Maintainability Assessment-Based Sustainability-Informed Maintenance Optimization in Power Transmission Networks," Sustainability, MDPI, vol. 16(15), pages 1-22, July.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:15:p:6489-:d:1445511
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    References listed on IDEAS

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    1. Yousif Munadhil Ibrahim & Norsiah Hami & Siti Norezam Othman, 2019. "Integrating Sustainable Maintenance into Sustainable Manufacturing Practices and its Relationship with Sustainability Performance: A Conceptual Framework," International Journal of Energy Economics and Policy, Econjournals, vol. 9(4), pages 30-39.
    2. Pramod R. Sonawane & Sheetal Bhandari & Rajkumar Bhimgonda Patil & Sameer Al-Dahidi, 2023. "Reliability and Criticality Analysis of a Large-Scale Solar Photovoltaic System Using Fault Tree Analysis Approach," Sustainability, MDPI, vol. 15(5), pages 1-24, March.
    3. Garmabaki, A.H.S. & Ahmadi, Alireza & Block, Jan & Pham, Hoang & Kumar, Uday, 2016. "A reliability decision framework for multiple repairable units," Reliability Engineering and System Safety, Elsevier, vol. 150(C), pages 78-88.
    4. Alrabghi, Abdullah & Tiwari, Ashutosh, 2016. "A novel approach for modelling complex maintenance systems using discrete event simulation," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 160-170.
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    Cited by:

    1. Huiying (Cynthia) Hou, 2025. "Utility Theory Application in Decision-Making Behavior for Energy Use and Management: A Systematic Review," Energies, MDPI, vol. 18(8), pages 1-19, April.

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