Process engineers are under pressure to optimize production while managing variable feedstock and shifting process conditions. Aspen Hybrid Models™ simplifies the use of machine learning in process simulation, delivering faster, more accurate models that provide timely insights to guide operations decisions.

Join Saud Alghwainem, Lead Scientist at SABIC, as he shares how hybrid modeling is helping SABIC streamline grade transitions, enhance online property predictions, and update reactor models more efficiently through the combined use of plant data, first‑principles knowledge and AI.

In this session, you’ll hear how SABIC:

• Improved operational insight with hybrid models that track process behavior and anticipate transitions
• Cut model run times to enable real‑time what‑if analysis and quicker operator decisions
• Enhanced catalyst model accuracy using first‑principles‑driven hybrid modeling with limited data

Register today to learn how SABIC is scaling hybrid modeling across their network—and how your teams can replicate their success.

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