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Artificial Intelligence and Big Data Technologies for Process Industries (CSA)

The Coordination and Support Action should identify, based on a mapping of digital technologies in process industries and their level of penetration, which specific AI- and big data technologies are most relevant, and what are, or could be, the most relevant application cases and/or pilots in process industry. A roadmap should be developed for all the different sectors in the process industries to take full advantage of AI and big data and give clear and pragmatic recommendations for researchers, managers, and operators planning to harness their potential.

The roadmap should explore, inter alia, actions on:

  • Research and innovation management, planning, and design (e.g. new chemical synthesis strategies, health and safety assessments);
  • Process control: yield and accuracy enhancement;
  • Supply chain management and scheduling of connected processes, plants and/or sites (e.g. for industrial symbiosis), process flexibility;
  • Predictive maintenance;
  • Product customisation and product traceability.

The Commission considers that proposals requesting a contribution from the EU between EUR 0.4 and 0.6 million would allow this specific challenge to be addressed appropriately. Nonetheless, this does not preclude submission and selection of proposals requesting other amounts.

Process Industries are becoming increasingly digitised. The development of devices, sensors and actuators, connected through the internet of things, allows machines to acquire capabilities such as identifying and optimising solutions, or making complex decisions. Enormous amounts of data are being generated but are typically exploited locally, for a unique purpose. Artificial intelligence (AI) is acknowledged as a key enabling technology but its actual potential is much more vast than the current state of the art in industrial applications suggest.

The impacts of the CSA are, through a roadmap identifying and developing strategies:

  • Better exploitation of AI potential for all the different sectors in the process industries, and strategies for developing AI applications, including the generation of data;
  • Identification of existing and future data requirements for the development of data driven technologies (eg. ontologies and data formats, how to handle data heterogeneity, data availability, quality and reliability, access and platforms, security and confidentiality);
  • Seamless collaboration of human operators with process control systems and plants: acceptance, identification of skills gaps and ethical, legal & social implications (ELSI);
  • Implementation and further elaboration of the strategic research and innovation agenda announced in the EC Communication on Artificial Intelligence.[[