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

STAY UP TO DATE

Sign up for news and updates

© Kashmir Intelligence 2024

Kashmir Intelligence is a remote first company headquartered in London, UK

© Kashmir Intelligence 2024

Kashmir Intelligence is a remote first company headquartered in London, UK

© Kashmir Intelligence 2024

Kashmir Intelligence is a remote first company headquartered in London, UK