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 behavior. 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 behavior.
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 predictive control techniques to be applied to manufacturing industrial plants.
• 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 behavior.

The contribution of DEIB concerns the analysis and identification of most suitable distributed and hierarchical Model Predictive Control methodologies to be applied to flexible and time variant production systems which are characterized by a very fast evolution concerning the whole product and process life cycle, from the ramp‐up to the dismissing.