Case Study
Simulation-Powered Deep Learning Achieves 25.05% Energy Savings in Distillation Column Optimisation
28 Aug 2024
Goals
The alkylation of 1-butene to produce octane and dodecane is a common refining process in the petrochemical industry. This study aims to:
Optimise the process using the Orbital foundation model within the DWSIM simulator, comparing its performance against best-in-class alternatives, including Linear Programming and Ensemble methods.
Leverage Orbital’s recommendation engine to optimise for reduced total input energy while maintaining consistent product quality specifications.
Results
25.05% energy consumption reduction
$116,645.02 annual cost savings
952.12 metric tonnes of CO2 emissions reduction annually
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