The PRONTO project is funded from the Marie Skłodowska Curie H2020 ITN (Innovative Training Networks) scheme. It runs from 1 Jan 2016 to 31 Dec 2019.

PRONTO is integrating information about equipment condition into all aspects of the process network operation, enabling decisions to be supported by the most up to date and relevant information. Results from the project show how equipment condition monitoring leads to enhanced operation and optimization of existing plants.

PRONTO involves end-user companies (BASF, Acciai Speciali Terni, Equinor, Ineos, Petronor, ), companies that supply technology and training (ABB R&D in Norway, Poland and Germany), and universities (Imperial College London as coordinator, Akademia Górniczo-Hutnicza Kraków, Cranfield University, Carnegie Mellon, Technische Universität Dortmund, Norwegian University of Science and Technology, Universidad de Valladolid).

The consortium has expertise in electrical machinery, compressors and pumps, modelling and optimization, instrumentation, signal analysis, equipment condition monitoring, and automation of oil and gas, steel and chemical processes.
 

Scientific objectives for the project

The project has four themes:
  • Detection and diagnosis of change of condition, combining data from heterogeneous sources and accounting for varying production regimes
  • Models for change of condition capturing factors influencing change of condition, and enabling integration of condition monitoring with process operation and control
  • Condition-aware operation and scheduling taking equipment condition and predicted degradation into account, optimizing production and maintenance
  • Adjustments to mitigate for change of condition, reducing uncertainty and enabling corrective actions to mitigate for changes
PRONTO has provided academic-industrial PhD training for a cohort of Marie Skłodowska-Curie Early Stage Researchers (ESRs) with PhD studies and either employment or a long placement in industry. They have identified, analysed and solved operational challenges in the process industries of Europe and demonstrated results in an industrial context. They have presented their work at workshops and many conferences.

Contact us

Nina Thornhill, ABB/RAEng Professor of Process Automation
Centre for Process Systems Engineering
Department of Chemical Engineering
Imperial College London
South Kensington Campus, London SW7 2AZ

Tel: +44 (0)20 7594 6622
Email: n.thornhill@imperial.ac.uk