Machine learning for predictive maintenance scheduling of distribution transformers
Journal of Quality in Maintenance Engineering
ISSN: 1355-2511
Article publication date: 24 January 2022
Issue publication date: 7 March 2023
Abstract
Purpose
The purpose of this paper is to describe a methodology that has been set up to schedule predictive maintenance of distribution transformers at Cauca Department (Colombia) using machine learning.
Design/methodology/approach
The proposed methodology relies on classification predictive model that finds the minimal number of distribution transformers prone to failure. To verify this, the model was implemented and tested with real data in Cauca Department Colombia.
Findings
The implementation of the methodology allows a saving of 13% in corrective maintenance expenses for the year 2020.
Originality/value
The proposed model is an effective decision-making tool that provides an ideal solution for preventive maintenance scheduling problems for distribution transformers.
Keywords
Acknowledgements
The authors would like to recognize and express their sincere gratitude to Compañia Energética de Occidente, Universidad del Valle and Universidad del Cauca, (Colombia) for the academic support granted during this project.
Citation
Alvarez Quiñones, L.I., Lozano-Moncada, C.A. and Bravo Montenegro, D.A. (2023), "Machine learning for predictive maintenance scheduling of distribution transformers", Journal of Quality in Maintenance Engineering, Vol. 29 No. 1, pp. 188-202. https://doi.org/10.1108/JQME-06-2021-0052
Publisher
:Emerald Publishing Limited
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