S&P Global and AspenTech transform refining decision-making on the cloud
summary
S&P Global moves its Excel-based Refinery Cost and Margin Analytics into AWS with Databricks, Snowflake and AspenTech PIMS via APIs, replacing manual batching with an automated cloud pipeline that runs 40,000 cases in 4–5 hours (about two seconds per case) instead of days. The solution exposes PIMS as the LP engine through a browser UI so non-LP specialists can run netback and crude-evaluation what‑ifs, and it adds real‑time yield and margin analyses with live turnaround alerts plus roadmaps for biofuels and petchem integration.
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chapters (12)
- 0:00Introduction and speakers
- 1:06S&P Global and AspenTech overview
- 2:31Refinery Cost and Margin Analytics challenges
- 4:18Aspen PIMS optimization model
- 6:04Moving to cloud and scaling solutions
- 8:29Legacy vs modern PIMS performance
- 9:32Democratizing LP modeling
- 12:01Data challenges and importance
- 14:48Barriers to refining modeling
- 16:13Future roadmap and features
- 17:15Measuring success and milestones
- 18:20Industry predictions and live turnarounds
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