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Start date: 2020Subject: search.filters.subject.health index

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    Fuzzy Analytical Hierarchy Process-Based Multi-Criteria Decision Framework for Risk-Informed Maintenance Prioritization of Distribution Transformers
    (2026-01-01)
    Rodkumnerd, Pannathon
    ;
    Pothinun, Thunpisit
    ;
    Phumpho, Suwilai
    ;
    Watson, Neville
    ;
    Siritaratiwat, Apirat
    Effective asset management is crucial for improving the reliability, resilience, and cost efficiency of distribution networks throughout the asset life cycle. Distribution transformers are among the most critical components, as their failures can cause extensive service interruptions and substantial economic impacts. Therefore, robust and transparent maintenance prioritization strategies are essential, particularly for utilities managing several transformers. Traditional time-based maintenance, while simple to implement, often results in inefficient resource allocation. Condition-based maintenance provides a more effective alternative; however, its performance depends strongly on the reliability of indicator selection and weighting. This study proposes a systematic weighting framework for distribution transformer maintenance prioritization using a multi-criteria decision-making (MCDM) approach. Each transformer is evaluated across two dimensions, including health condition and operational impact, based on indicators identified from the literature and expert judgment. To address uncertainty and judgmental inconsistency, particularly when the consistency ratio (CR) exceeds the conventional threshold of 0.10, the Fuzzy Analytic Hierarchy Process (FAHP) is employed. Seven condition parameters characterize transformer health, while impact is quantified using five indicators reflecting failure consequences. The proposed framework offers a transparent, repeatable, and defensible decision-support tool, enabling utilities to prioritize maintenance actions, optimize resource allocation, and mitigate operational risks in distribution networks.
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    Development of a Health Index for Transformer Condition Assessment Using an Online Dashboard
    (2025-01-01)
    Sripatawasumadee, Kornchet
    ;
    Maneerat, Noppadol
    ;
    Dechothamsathit, Vorawut
    ;
    Kingkham, Sukanya
    ;
    Jeenmuang, Siwakorn
    Power transformers are critical components in electrical power systems in the transmission and distribution of electricity. Keeping them in good working condition is necessary to prevent power outages and ensure system stability. Traditional maintenance strategies, such as time-based maintenance, may not always be the best way to avoid problems or use resources efficiently. To improve this, the concept of a Health Index (HI) has been introduced as a systematic method for transformer condition assessment. By integrating various diagnostic data - such as load data, oil analysis, maintenance record, and on-load tap changer (OLTC) parts - into a unified HI score, asset managers can make informed decisions regarding maintenance prioritization and replacement planning. Furthermore, this paper proposes the development of an online dashboard system that facilitates the input, storage, and visualization of transformer health data. This user-friendly platform enables engineers to monitor condition trends in real time and supports strategic maintenance scheduling. The integration of Health Index evaluation with an accessible digital interface enhances the efficiency, transparency, and reliability of transformer asset management practices.