Prerequisites for the admission.

Access to the Master's Degree Programme in Digital Automation Engineering requires the possession of one of the following qualifications from an Italian University, or qualifications deemed equivalent: Three-year University Degree or Diploma, Specialist Degree or Master’s Degree, pursuant to MD 509/1999 or MD 270/2004, five-year Degree (previous to MD 509/1999).

Skills associated with the function

Digital automation engineer for the research, design and development of digitisation
Data Collection, Embedded Systems and Internet of Things, Cloud Systems, Machine Learning, Big Data, Analysis, design and review of industrial and logistic processes for the provision of services.

Digital automation engineer for research, design and development of data-driven automation systems
Machine Learning, Robotics, Automation, Internet of Things, Dynamic Modelling, Predictive Maintenance, Optimization, Smart-Grids and Digital Energy Systems, Digital Industrial Machines and Plants.

Digital automation engineer for process and product analysis and simulation
Machine Learning, Robotics, Dynamic and Multiphysics Modelling, Automation, Logistics and digital production systems, Business intelligence, high-throughput automated calculations

Function in a work context

Digital automation engineer for the research, design and development of digitisation
- s/he designs the digital infrastructure of processes and services, in order to allow automatic collection of data in the field and the exchange of data between the various physical or virtual components involved.
- s/he designs digital services that can be integrated into the communication and data exchange infrastructure of production systems, for the supply of products and/or services, and that can integrate data collection with existing technologies.
- s/he develops solutions based on the collection and analysis of large amounts of data and their analysis using machine learning techniques in order to transform data into decisions.


Digital automation engineer for research, design and development of data-driven automation systems
- s/he designs data-driven automated solutions for products and/or processes;
- s/he uses data to model, design and implement the automation of physical, virtual or mixed nature processes by exploiting the information that can be extracted from data;
- s/he designs digital services to support process automation based on data analysis and processing;
- s/he optimises the reliability of processes by analysing and processing data.


Digital automation engineer for process and product analysis and simulation
- s/he uses data to build digital twins and simulation models to reproduce, predict and analyse the behaviour of a product or process, physical, virtual or mixed in nature, to obtain dynamic information on production or business processes guiding organisational decisions.
- s/he designs digital solutions to support the development, reliability and analysis of data-driven simulation models and computer design for the optimisation of industrial applications, product development processes and the design of new materials.

Educational goals

The Master's degree programme in Digital Automation Engineering enables students to enhance and develop the learning skills already acquired in previous university programmes. The training of graduates, which involves and links scientific fields characterising information and industrial engineering, instils autonomy for future continuous updates and insights, which are necessary to always generate innovation.
The project and laboratory activities, conducted and verified during the course of studies and the preparation of the thesis, require appropriate in-depth literature searches that stimulate the learning ability that will be required to meet future complex engineering challenges, both in the world of work and research.
The ability to learn is expressed in the tests provided at the end of each programme, and in the realisation of the thesis project.

Communication skills

The Master's degree programme in Digital Automation Engineering trains graduates to be able to communicate effectively in the description of engineering tasks; the multidisciplinary nature of the degree programme provides students with the ability to collaborate directly with technical stakeholders of various natures, facilitating teamwork. Training that encompasses all phases of modelling, simulation and analysis of systems, for control, monitoring and diagnostics, enables graduates to competently communicate the information obtained, stimulating its correct interpretation.
Communication skills are developed in students in the preparation and presentation of individual or group projects, in participation in internship activities and in the writing and presentation of the dissertation.
Communication skills, the clarity of exposition of engineering problems and solutions, and the correct use of technical language are tested by intensifying discussions with students during lectures and laboratory experiences and in the performance of internship activities, as well as in the preparation and exposition of dissertations.

Making Judgements

Master's graduates in Digital Automation Engineering will have attained, at the end of their training, a technical maturity and a critical spirit that will enable them to understand the most appropriate methodologies for probabilistic modelling, optimisation, control, monitoring and diagnostics of mechanical and electrical systems and the application of artificial intelligence for automation. The defining characteristic of graduates will be a strong propensity to correctly interpret information gathered through field data acquisition, which stems from a profound physical-mechanical knowledge of systems.
Graduates will be able to carry out autonomous bibliographic research, selecting the appropriate databases and scientific communities with which to interact in order to learn about the state of the art and disseminate the innovative results of their work, and will be able to design and conduct laboratory and field experimental activities (learning by doing) to gather information under operational conditions.
Autonomy of judgement is verified by lecturers during examinations and in the course of collaborative project presentations, by company or academic referees in the course of internships, by the thesis project supervisor and by the Degree Board.

Learning skills

The Master's degree programme in Digital Automation Engineering enables students to enhance and develop the learning skills already acquired in previous university programmes. The training of graduates, which involves and links scientific fields characterising information and industrial engineering, instils autonomy for future continuous updates and insights, which are necessary to always generate innovation.
The project and laboratory activities, conducted and verified during the course of studies and the preparation of the thesis, require appropriate in-depth literature searches that stimulate the learning ability that will be required to meet future complex engineering challenges, both in the world of work and research.
The ability to learn is expressed in the tests provided at the end of each programme, and in the realisation of the thesis project.