Selecting a condition monitoring system for enhancing effectiveness of power transformer maintenance

Author:

Hernandez Maria Del Pilar Colin,Labib Ashraf

Abstract

Purpose The purpose of this paper is to propose a model for assisting in the decision-making process for acquiring a condition monitoring (CM) system for an oil-immersed power transformer in order to improve its maintainability. Design/methodology/approach The proposed model is based on the analytic hierarchy process. The assessment was performed by pairwise comparisons, and a sensitivity analysis (what-if analysis) was used to identify the implications of changing the criteria weights. In order to select the criteria and alternatives, a search was conducted for the power transformer failure modes, monitored parameters and CM technologies. Findings The proposed model provides a structured solution for a complex problem: deciding the best combination of technologies for CM of power transformers. Research limitations/implications Because the pairwise comparisons were done only by the author, the results may need to be improved with the assessment of more experts. Also, it was done for a specific type of transformer; it might be necessary to customise the alternatives for other cases. Finally, as a future consideration, more levels can be added to the hierarchy to improve the accuracy of the model. Practical implications The power transformer is an asset where the most appropriate maintenance strategy for it is condition-based maintenance. In order to improve its maintainability, it is recommendable to improve its testability and diagnosability. For achieving this goal, the maintenance personnel have to decide the best combination of technologies for CM. The methodology developed can assist the decision makers to select the most appropriate cost-benefit strategy. Originality/value The paper presents a structured and generic method of selecting the most appropriate CM system for power transformers.

Publisher

Emerald

Subject

Industrial and Manufacturing Engineering,Strategy and Management,Safety, Risk, Reliability and Quality

Reference26 articles.

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