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

Ekene Cynthia Onukwulu, Mercy Odochi Agho, Nsisong Louis Eyo-Udo, Aumbur Kwaghter Sule and Chima Azubuike
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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

International Journal of Research and Innovation in Applied Science, 2024, vol. 9, issue 12, 654-687

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.

Date: 2024
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