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Profitability is a significant obstacle for the refining sector due to the volatile global crude oil market, which is subject to supply and demand fluctuations. An upsurge in the price of crude oil leads to escalated expenses for fuel, diminished consumer travel, and, consequently, an adverse effect on the financial performance of refineries.

Refineries strive to optimize their operational processes to achieve a one-cent expense reduction. On the contrary, when crude oil prices decrease, there is a tendency to reorient towards complacency, whereby the implementation of streamlined operations is neglected until the subsequent increase in crude oil prices.

This series of articles aims to provide an overview of different facets of Artificial Intelligence (AI), Machine Learning (ML), Neural Network (NN), and Deep Learning (DL) technologies, as well as their current or potential applications within the downstream refining sector.

The refining industry faces significant challenges in sustaining profitability due to the unpredictable fluctuations in the global crude oil market, which are influenced by supply and demand. A surge in crude oil prices results in increased fuel costs, reduced travel by consumers, and, subsequently, a negative impact on the profitability of refineries.

An outline will be provided for each of the refinery areas affecting the refinery's profitability.

(M) Infrastructure Management
(C) Manufacturing Control
(O) Product Optimization
(R) Hydrocarbon Reconciliation

Discover a wealth of knowledge in whitepapers authored by our academy's esteemed partners and experts. These articles have been featured in reputable technical journals, as well as presented at various workshops and conferences. For your convenience, we've compiled them here, and we eagerly seek your valuable feedback.