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  2. Aramco, Emerson deploy AI solution for higher refinery yield volume

Aramco, Emerson deploy AI solution for higher refinery yield volume

NOHA.GAD
May 4, 2026
Aramco collaborated with Emerson to deploy AI solution to achieve higher refinery yield volume and efficiencies

Riyadh - Sharikat Mubasher: Aramco, one of the world’s leading integrated energy and chemicals companies, announced the successful deployment of an AI-driven optimization solution in collaboration with the global automation leader Emerson to achieve higher refinery yield volume and efficiencies.

The collaboration commenced with the integration of Emerson’s Aspen Hybrid Models™ into Aramco’s existing refinery planning framework, resulting in achieving yield and quality prediction accuracy of up to 98.5% in key refinery units, according to the official press release.

By combining first-principles models, deep domain expertise, and purpose-built industrial AI, Aspen Hybrid Models™ capture nonlinear relationships in yield and quality responses, significantly enhancing the accuracy of refinery planning models.

Ahmad Alkudmani, Director of the Global Optimizer Department at Aramco, stated that the deployment represents a significant milestone in Aramco's AI strategy and our long-standing relationship with Emerson.

“We are committed to leveraging innovative technologies for smarter, more efficient refining optimization. With improved model accuracy, we are enhancing planning decisions, reducing the manual adjustments required from our engineers, and uncovering new value across our global assets,” Alkudmani added.

For his part, Claudio Fayad, Chief Technology Officer of Emerson's Aspen Technology business, commented: “This deployment of AI-driven Aspen Hybrid Models to optimize complex, multi-site, multi-period planning workflows demonstrates the tangible value of combining deep domain expertise with advanced AI. We're excited to expand our strategic relationship with Aramco as they advance their digital transformation goals."

This expansion is expected to further enhance model accuracy and demonstrate the scalability and robustness of this AI-driven optimization strategy across the enterprise.

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