President
Enzo Pasquale Scilingo
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Administrative Office
Department of Ingegneria dell'informazione
Overview and objectives of the PhD course
The universities of Florence, Pisa and Siena offer the PhD course in SMART INDUSTRY, focused on the Industry 4.0 paradigm (I4.0). The PhD course will have training and research initiatives in the 9 interdisciplinary enabling technologies of I4.0 (Advanced Manufacturing; Additive Manufacturing; Augmented Reality; Simulation; Horizontal / Vertical Integration; Industrial Internet; Cloud; Cybersecurity; Big Data & Analytics) with the aim of training young researchers capable of investigating and experimenting innovative industrial processes and systems that draw competitiveness from the integration of advanced information processing components and methods. The cultural roots of industrial and information engineering will enable opportunities for cross-fertilization and research that will have value both through their integration and autonomously.
The course is jointly offered by the three universities in synergy with the industrial research initiatives already underway in Tuscany. A strong research collaboration will be promoted with the industrial sector in which the development of the I4.0 paradigm will be able to innovate portions of the production process or entire supply chains and enable new products, services, business models.
The methodology will consist of: a training offer that creates the scientific and methodological starting point; an individual specialization in areas with adequate scientific and research depth; an aggregation of the areas on the I4.0 objectives.
Course objectives:
The objectives of the course are the training of high-profile technical-scientific professionals, competent on specific technological aspects, but also and above all competent in the methodologies for the integration of technological innovation in industrial processes, and in particular in the following enabling interdisciplinary technologies :
- Advanced Manufacturing Solutions: advanced automation systems for manufacturing and autonomous cooperative and collaborative robots, which allow increasing the automation and productivity of the lines without losing flexibility, and with reduced and accessible investments also to SMEs;
- Additive Manufacturing: additive printing, which allows redesigning production processes and reducing Time-to-Market, thanks to the rapid prototyping of new products, new production models (digital manufacturing, cloud manufacturing), and new forms of product life cycle support (digital spare parts management);
- Augmented Reality: virtual and / or mixed reality, or the set of technologies, devices and algorithms for augmented reality, virtual reality and computer vision that enable new forms of interaction and control between man and machine (HMI) , for training, assistance, control, and automation processes;
- Simulation: simulation environments, for the creation of digital models of machines and processes (digital twin), through which the performance of a system or process can be analyzed and optimized;
- Horizontal / Vertical Integration: the integration of information flows both vertically, through architectures and automation systems and manufacturing process control (MES, Manufacturing Execution System), and horizontally, along the value chain (Supply Chain Management);
- Industrial Internet: the Internet of Things in the industrial field, which uses sensorization and connectivity of machines and systems to create large amounts of data on which to base the development of new information and knowledge;
- Cloud Computing: the virtualization of infrastructures for data management and software applications, which enables the integration of "data lakes" and the development of collaboration platforms between companies in the value chain (business ecosystem);
- Cybersecurity: the systems, technologies and algorithms that make it possible to manage the exchange of sensitive and confidential data in a safe and secure way;
- Big Data & Analytics: advanced solutions and algorithms for the development of analytics and predictive models, such as cognitive systems, machine learning, artificial intelligence and deep learning applications, specifically oriented to use in industrial production, which they make the acquisition of knowledge from large amounts of data much more effective through guided or autonomous training processes.
Regolamento interno del corso di dottorato (only in Italian)
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