Designing Predictive Maintenance Models for SCADA-Enabled Energy Infrastructure Assets

• Author(s): Ebimor Yinka Gbabo ; Odira Kingsley Okenwa ; Possible Emeka Chima
• Paper ID: 1709048
• Page: 272-283
• Published Date: 31-08-2021
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 5 Issue 2 August-2021

Abstract

The increasing complexity and criticality of energy infrastructure assets necessitate advanced maintenance strategies to ensure reliability and operational efficiency. Supervisory Control and Data Acquisition (SCADA) systems provide continuous, real-time monitoring capabilities, generating vast amounts of data essential for condition-based management. This paper explores the design of predictive maintenance models tailored for SCADA-enabled energy assets, emphasizing data-driven methodologies that leverage sensor, operational, and environmental inputs. It presents an overview of SCADA system architecture, data acquisition mechanisms, and their integral role in asset management. The fundamentals of predictive maintenance are discussed, highlighting its advantages over traditional maintenance approaches. Key considerations in model development—including data preprocessing, feature engineering, model selection, and evaluation metrics—are thoroughly examined to guide practitioners in creating robust and actionable predictive solutions. The paper concludes by outlining future research directions focused on data integration, model interpretability, and real-time deployment. These insights aim to advance the adoption of predictive maintenance in energy sectors, fostering resilient, efficient, and sustainable infrastructure management.

Keywords

Predictive Maintenance, SCADA Systems, Energy Infrastructure, Data-Driven Models, Asset Management, Machine Learning

Citations

IRE Journals:
Ebimor Yinka Gbabo , Odira Kingsley Okenwa , Possible Emeka Chima "Designing Predictive Maintenance Models for SCADA-Enabled Energy Infrastructure Assets" Iconic Research And Engineering Journals Volume 5 Issue 2 2021 Page 272-283

IEEE:
Ebimor Yinka Gbabo , Odira Kingsley Okenwa , Possible Emeka Chima "Designing Predictive Maintenance Models for SCADA-Enabled Energy Infrastructure Assets" Iconic Research And Engineering Journals, 5(2)