Meeting ultra-low sulphur diesel (ULSD) norms often forces operators to run with wide safety margins, leading to higher hydrogen use, faster catalyst aging, and higher costs.
This case study shows how AI-driven sulphur prediction provided real-time visibility, reduced hydrogen consumption, and improved catalyst utilization
What’s Inside:
3–5% reduction in hydrogen consumption
Longer catalyst cycle life
Reliable sulphur prediction aligned with lab results
Why It Worked:
Built on plant data, validated with lab samples
Developed with SMEs, engineers, and data scientists
Deployed seamlessly into operations
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AI applied to refining. Proven. Measurable.
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