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Genomic Model Predictive Control Tools for Evolutionary Plants

Timeframe : 2014

The IMET2AL project proposes a genomic Model Predictive Control (MPC) based software prototype tool that supports the industrial engineers to study and design control system configurations for automated factory production systems characterized by a fast evolutionary behaviour. The obtained control solutions are optimized on the base of key performance indexes like flow production, peak of the absorbed electrical power and the total energy consumed by the plant and they are able to impress to the production system the desired functional behaviour.

There are two major benefits coming from the IMET2AL project:

  • The first and most important one regards the sharing and the development among the project partners of the knowledge on advanced model predictivecontrol techniques to be applied to manufacturing industrial plants. These methodologies are typically used in the process industry but not in the manufacturing one and will open the manufacturing industry to new production system scenarios characterized by optimized and high efficiency performances.
  • The second benefit concerns the development of a prototype software platform tool useful to support the industrial production system engineer in designing the plant automation system based on an abstract genomic control model so as to characterize the whole automated factory production system according to its evolutionary behaviour.

Keywords: manufacturing automation, control infrastructure, automated factory production systems

Financial support by: National Research Council of Italy (Flagship Project "Factory of the Future")

Coordinator of the IEIIT unit in the project: Ivan Cibrario Bertolotti