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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM22967

Automation and AI in Downstream Oil and Gas Logistics: Enhancing Efficiency and Resilience

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Subject:

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Paper ID:

10.55041/IJSREM22967

Volume:

7 |

6 |

Jun 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

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License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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MV

Manykandaprebou Vaitinadin

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Abstract

The downstream oil and gas industry plays a crucial role in refining, distributing, and delivering petroleum products to end-users. However, the complexity of supply chain logistics, volatile market conditions, and regulatory challenges present major obstacles. Automation and Artificial Intelligence (AI) are transforming logistics by optimizing efficiency, reducing costs, and improving safety and resilience. This paper examines the role of AI and automation in downstream logistics, highlighting key challenges, mitigation strategies, and future trends. AI-powered predictive analytics, real-time tracking, robotic process automation (RPA), and machine learning algorithms are reshaping distribution networks, reducing downtime, and enhancing decision-making capabilities. The study explores key AI-driven logistics solutions, evaluates risks, and suggests best practices for effective implementation in the downstream oil and gas sector.

KEYWORDS

Automation AI downstream oil and gas supply chain logistics predictive analytics robotic process automation digital transformation real-time tracking.

Cite This Article

Manykandaprebou Vaitinadin, "Automation and AI in Downstream Oil and Gas Logistics: Enhancing Efficiency and Resilience," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 6, Jun 2023. https://doi.org/10.55041/IJSREM22967

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6/26/2023

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