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    Item type:Publication,
    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.
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    The new developed Health Index for transformer condition assessment
    (2016-11-28)
    Wattakapaiboon, W.
    ;
    Pattanadech, N.
    Health Index (HI) technique is useful for maintenance strategy planning of transformers utilized in industrial sectors and electrical power systems. The conventional HI method requires many testing parameters to evaluate the transformer conditions. Therefore, it may lead to be an impractical task in many reality cases. Besides, some required testing parameters are not clearly defined. The aim of this paper is to represent the new method to assess the conditions of transformers by applying a new developed HI table which was improved from the conventional HI table. The new developed HI table needs only some simple testing parameters for evaluating the transformer conditions. Thirteen transformer case studies were used to evaluate the performance of the new develop HI table by comparing the score value obtained from the conventional HI table and the new developed HI table. The test results show that only 7% different score obtained from the developed HI table compared with conventional HI table. Therefore, the new developed HI technique should be useful for condition analysis of the transformers and also for transformer strategy planning. Applying the new HI technique could reduce the operation cost and adapt well for practical work.