Tecniche computazionali intelligenti nei sistemi di produzione

The increasing complexity of our society and economy places greater emphasis on artificial systems such as robots, smart devices and machines which can deal autonomously with our needs and with the peculiarities of the environments we inhabit and construct. This challenge is to extend systems engineering methods to deal with open-ended and frequently changing real-world environments. A primary aim is to develop system capabilities to respond intelligently to gaps in the system's knowledge and to situations or contexts that have not been specified in its design. In order to meet this challenge, a mix of innovative scientific theory and technology is needed, based on natural and artificial cognition, in conjunction with new systems design and engineering principles and implementations for machines, robots and other devices which are robust and versatile enough to deal with the real world and to behave in a user-friendly and intuitive way with people in everyday situations. Artificial cognitive systems, advanced interaction technologies and intelligent robots will help open up new opportunities for industry in Europe. Reinforcing leading edge research in these domains will help extend technologies into tomorrow’s industries and markets, in fields of potentially high socio-economic significance like industrial production, learning, healthcare, public safety, environmental monitoring, and in emerging sectors such as service robotics. Autonomous surveillance systems can, for example, save crucial time in emergencies or hazardous situations. Artificial cognitive systems and intelligent robots can extend the capabilities of people to perform routine, dangerous or tiring tasks, especially in previously inaccessible, uncharted, or remote spaces on land, sea or air. Scientific research will also improve our understanding of the mechanisms underlying artificial and natural cognition, in particular learning and the development of competences requiring goal-setting, reasoning, decision-making, language, communication and cooperation. It will enable us to build machines that can understand, learn and generate concepts and translate them across languages with degrees of robustness and versatility not possible today. And it will spur breakthroughs in advanced behaviours of robots, such as in manipulating objects and interacting socially, which are key to their further penetration into real world environments. Artificial cognitive methodologies implemented at LATP comprise: expert systems, supervise; material behaviour modelling in hot forming processes; monitoring of metal cutting processes; tool management in multiple supplier networks.