Increasing productivity in the process industries through the use of artificial intelligence and machine learning for the optimisation of distillation operations

  • Smith, Robin (Participant)
  • Megan Benton (Participant)
  • Zhang, Nan (Participant)
  • Lluvia Ochoa-Estopier (Participant)

Impact: Economic, Environmental

Narrative

Research into novel approaches for operational optimisation at the University of Manchester’s research centre, the Centre for Process Integration, has led to increased productivity in industrial chemical processes. Operational optimisation adjusts process variables to improve the efficiency and cost effectiveness of the equipment, increasing process yields and decreasing energy use.
This research is commercially applied through a spin-out consultancy company Process Integration Ltd (PIL). The impact in this REF period has been employment of 8 additional staff, a consolidated turnover of at least GBP5,500,000, and consultancy services to more than 20 different companies worldwide. Within the impact window, the interventions detailed in this case study have resulted in client savings in excess of USD48,000,000 (GBP36,800,000).
Impact date1 Aug 2013 → 31 Jul 2020
Category of impactEconomic, Environmental
Impact levelAdoption

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