Project Details


The main objective is to identify feasible machine learning methods that could potentially improve existing
maintenance practices, where data will lead to successful predictive decisions consistent with updated
standardization. On this regard, the following outcomes are expected:
 To develop a proof of concept based on the IEE 3007 and machine learning methods to expand
maintenance practices of industrial and commercial power systems.
 To provide a useful taxonomy where new generation of engineers could rapidly visualize suitable
techniques to take advantage of large volume of data in electrical facilities.
 To design and implement a multipurpose cloud-based interface, which allows the realistic
assessment of different scenarios related to predictive and proactive maintenance for a case study
(IEEE 3007 - 480 V Switchboard)
 To boost the interdisciplinary efforts with early student involvement into technical, practical, and
fundamental concepts that have been on the scope priority of many IAS committees

Commitments / Obligations

(2) Proceedings ICPRE 2022
(3) proceedings IEEE 2022
(1) proceedings IEEE 2023
(1) Artículo de revista – 2023
Effective start/end date2/1/232/1/24

UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):

  • SDG 8 - Decent Work and Economic Growth

Main Funding Source

  • Competitive Funds


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