Advancements in predictive maintenance in the oil and gas industry: A review of AI and data science applications
1 Kennesaw State University, GA, USA.
2 Data Scientists Network (DSN), Lagos, Nigeria.
3 Department of Electrical and Computer Engineering, University of Nebraska-Lincoln, USA.
4 Department of Mechanical Engineering, University of Nebraska-Lincoln, USA.
5 Sheffield Hallam University, United Kingdom.
Review Article
World Journal of Advanced Research and Reviews, 2023, 20(03), 167–181
Article DOI: 10.30574/wjarr.2023.20.3.2432
Publication history:
Received on 18 October 2023; revised on 25 November 2023; accepted on 28 November 2023
Abstract:
This study provides a comprehensive review of the advancements in predictive maintenance within the oil and gas industry, focusing on the integration and impact of Artificial Intelligence (AI) and Data Science. The primary objective was to evaluate how AI and data science have transformed maintenance practices from traditional methods to more advanced, predictive approaches. The methodology involved a systematic literature review, utilizing databases such as IEEE Xplore, ScienceDirect, SpringerLink, and Web of Science. The search strategy was centered around keywords related to AI, data science, and predictive maintenance in the oil and gas sector, with a focus on literature published from 2010 onwards. The findings reveal that AI and data science significantly enhance predictive maintenance strategies. AI algorithms and data analytics have enabled more accurate predictions of equipment failures and optimized maintenance scheduling, leading to reduced downtime and operational costs. The study also identifies challenges, including the complexity of data management and the need for high-quality, real-time data. Opportunities for future advancements lie in developing more robust AI models capable of adapting to the industry's dynamic environment. The study recommends that industry stakeholders invest in workforce training for AI-based systems and that policymakers develop frameworks supporting ethical AI use. Future research directions include exploring the integration of AI with other emerging technologies and developing sustainable maintenance practices. The study concludes that AI's continuous evolution will play a crucial role in shaping the future of maintenance strategies in the oil and gas industry.
Keywords:
Predictive Maintenance; Artificial Intelligence; Oil and Gas Industry; Data Science
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Copyright © 2023 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0