This presentation explores how modern data science methods can be used to support industrial process optimization, with a focus on applying world-model reinforcement learning to a fractionation-style process. Many industrial systems are nonlinear, dynamic, and highly interactive: a change to one controller or operating variable may influence temperatures, pressures, flows, product quality, and...
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