Optimizing energy efficiency in data center cooling towers through predictive maintenance and project management
1 Independent Researcher, Maryland, USA.
2 Hult International Business School, USA.
3 Niger Delta Power Holding Company, Akure, Nigeria.
4 FieldCore Canada, part of GE Vernova. Canada.
5 Electrical Engineering, The University of Nebraska-Lincoln, USA.
6 Department of Metallurgical and Materials Engineering, The University of Alabama, USA.
Review Article
World Journal of Advanced Research and Reviews, 2024, 21(02), 1782–1790
Article DOI: 10.30574/wjarr.2024.21.2.0619
Publication history:
Received on 14 January 2024; revised on 25 February 2024; accepted on 27 February 2024
Abstract:
Optimizing energy efficiency in data center cooling towers is crucial for reducing operational costs and environmental impact. This review explores the integration of predictive maintenance and project management to achieve this goal. By leveraging predictive maintenance techniques, data center operators can anticipate and address potential issues before they lead to costly downtime or inefficiencies. Project management plays a key role in coordinating these efforts, ensuring that maintenance activities are carried out efficiently and effectively. Predictive maintenance relies on data analytics and machine learning algorithms to monitor the condition of cooling towers in real-time. By analyzing data such as temperature, pressure, and flow rates, these algorithms can detect anomalies and predict potential failures. This proactive approach allows data center operators to schedule maintenance activities during planned downtime, minimizing disruptions to operations. Project management practices, such as Agile or Waterfall methodologies, are essential for coordinating predictive maintenance efforts. Project managers oversee the planning, execution, and monitoring of maintenance activities, ensuring that they are completed on time and within budget. They also facilitate communication between stakeholders, including maintenance teams, data analysts, and management, to ensure that everyone is aligned and working towards the same goals. By integrating predictive maintenance with project management, data center operators can achieve significant improvements in energy efficiency. By addressing maintenance issues proactively, operators can reduce energy consumption, extend the lifespan of cooling equipment, and minimize downtime. Additionally, project management practices ensure that these efforts are coordinated and effective, maximizing the benefits of predictive maintenance. In conclusion, optimizing energy efficiency in data center cooling towers requires a holistic approach that combines predictive maintenance and project management. By leveraging predictive maintenance techniques and project management practices, data center operators can achieve significant improvements in energy efficiency, reduce operational costs, and enhance environmental sustainability.
Keywords:
Optimizing; Energy Efficiency; Data Center Colling; Towers; Predictive Maintenance
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Copyright information:
Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0