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Emilia Romagna


AI-enhanced control strategy for production environment

(Domenico Guida @ ART-ER)

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NEED for AI:

Application of deep-learning paradigms for enhanced prescriptive maintenance and for homogeneous wear lever across parallel-working tools/machines and optimization of the production tool.

There is a need to exploit novel AI-related techniques:

  • to optimize the production times and the personnel efforts

  • to improve the instrument quality consistency

  • to collect imaging data from machines and analyse them



To exploit and leverage on novel imaging techniques for quality check and management, embedding AI-enhanced software; it will support the development of algorithms, procedures and support platforms for deployment of intelligent control systems, integrating automatic control techniques with AI-related knowledge.

It will also foster and incentivize the development of concepts and prototypes of collaborative robots and workstations, or part of them, whose capabilities complement those of human workers, thus allowing for safe and comfortable working environments.



  • reduction of production time

  • enhancement of prescriptive maintenance

  • optimization of personnel efforts

  • enhance homogeneous wear lever across parallel working tools/machines; workers’ cognitive and physical effort when interacting with a complex system

EMILIA ROMAGNA region DIH experiment is focused on the setup of a facility lab for deep learning enhanced industrial production controlling, with a special focus on Image processing related techniques

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