IDEAS home Printed from https://ideas.repec.org/a/bjf/journl/v9y2024i12p654-687.html
   My bibliography  Save this article

Advances in Automation and AI for Enhancing Supply Chain Productivity in Oil and Gas

Author

Listed:
  • Ekene Cynthia Onukwulu

    (Kent Business School, University of Kent, UK)

  • Mercy Odochi Agho

    (Independent Researcher, Port Harcourt Nigeria)

  • Nsisong Louis Eyo-Udo

    (Independent Researcher, Lagos Nigeria)

  • Aumbur Kwaghter Sule

    (Independent Researcher, Abuja, Nigeria)

  • Chima Azubuike

    (Guaranty Trust Bank (Nigeria) Limited)

Abstract

Advances in automation and artificial intelligence (AI) are transforming supply chain management in the oil and gas industry, driving enhanced productivity, efficiency, and cost-effectiveness. This paper explores the integration of automation and AI technologies to optimize various supply chain processes, from procurement to distribution, and improve overall operational performance. Automation tools, including robotic process automation (RPA), drones, and autonomous vehicles, are streamlining tasks such as inventory management, inspection, and transportation, reducing human error, and increasing the speed of operations. AI-powered algorithms, particularly in predictive analytics, are enabling better demand forecasting, inventory control, and predictive maintenance, thus minimizing downtime and maximizing asset utilization. The use of AI for real-time data analysis and decision-making is particularly crucial in dynamic and high-risk environments like oil and gas supply chains. By analyzing large volumes of data, AI models can identify patterns, forecast disruptions, and recommend proactive solutions, thus improving risk management and ensuring business continuity. Additionally, AI-driven supply chain optimization tools are enhancing resource allocation, improving supply chain visibility, and promoting data-driven decision-making. Automation in supply chain logistics, including the use of drones for inspection and delivery, contributes to safer and more efficient operations, reducing the need for manual intervention in hazardous environments. This paper also discusses the role of AI in enhancing supply chain resilience by predicting market fluctuations, optimizing routes, and automating procurement strategies. However, challenges such as data integration, cybersecurity concerns, and the need for skilled personnel must be addressed for successful implementation. Despite these challenges, the potential benefits of automation and AI in enhancing supply chain productivity are significant, offering substantial improvements in operational efficiency, cost savings, and risk mitigation. Ultimately, the adoption of these technologies is set to redefine the future of supply chain management in the oil and gas sector.

Suggested Citation

  • Ekene Cynthia Onukwulu & Mercy Odochi Agho & Nsisong Louis Eyo-Udo & Aumbur Kwaghter Sule & Chima Azubuike, 2024. "Advances in Automation and AI for Enhancing Supply Chain Productivity in Oil and Gas," International Journal of Research and Innovation in Applied Science, International Journal of Research and Innovation in Applied Science (IJRIAS), vol. 9(12), pages 654-687, December.
  • Handle: RePEc:bjf:journl:v:9:y:2024:i:12:p:654-687
    as

    Download full text from publisher

    File URL: https://www.rsisinternational.org/journals/ijrias/digital-library/volume-9-issue-12/654-687.pdf
    Download Restriction: no

    File URL: https://rsisinternational.org/journals/ijrias/articles/advances-in-automation-and-ai-for-enhancing-supply-chain-productivity-in-oil-and-gas/
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bjf:journl:v:9:y:2024:i:12:p:654-687. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Dr. Renu Malsaria (email available below). General contact details of provider: https://rsisinternational.org/journals/ijrias/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.