Studying at the University of Verona
Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.
Study Plan
The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University.
Please select your Study Plan based on your enrollment year.
1° Year
Modules | Credits | TAF | SSD |
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Compulsory courses for Embedded & IoT Systems
Compulsory courses for Smart systems &data analytics
2° Year activated in the A.Y. 2021/2022
Modules | Credits | TAF | SSD |
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Compulsory courses for Embedded & IoT Systems
Compulsory courses for Robotics systems
Compulsory courses for Smart systems &data analytics
Modules | Credits | TAF | SSD |
---|
Compulsory courses for Embedded & IoT Systems
Compulsory courses for Smart systems &data analytics
Modules | Credits | TAF | SSD |
---|
Compulsory courses for Embedded & IoT Systems
Compulsory courses for Robotics systems
Compulsory courses for Smart systems &data analytics
Modules | Credits | TAF | SSD |
---|
3 courses to be chosen among the following
Legend | Type of training activity (TTA)
TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.
Process monitoring (2020/2021)
Teaching code
4S009011
Credits
6
Language
English
Scientific Disciplinary Sector (SSD)
ING-INF/05 - INFORMATION PROCESSING SYSTEMS
The teaching is organized as follows:
Teoria
Laboratorio
Learning outcomes
The course aims to provide students with skills in: i) analyzing data using univariate, multivariate and high-dimensional statistics methods; ii) identification of anomalous situations; iii) analysis of heterogeneous data; iv) analysis of dynamic and non-stationary processes; v) time series prediction.
At the end of the course the student will have to demonstrate that he is able to manage the monitoring of an industrial process. In particular, he will have to demonstrate that he is able to: i) identify potential failure modes; ii) design a data acquisition system on the production line; iii) identify anomalies in the process; iv) optimize the process parameters according to predefined objectives (rejection rate, time reduction, etc.); v) analyze the causes of unexpected failures (root cause analysis); vi) manage the maintenance of the system with predictive techniques.
Examination Methods
The exam involves the discussion of a project proposing a solution to an industrial problem.
The student will present his/her work in about 15 minutes (with or without the use of support material such as slides, written report, demo, etc.), followed by a questions & answers session.
For the generation of the grade it will be taken into account:
- performance of the developed system (with different metrics depending on the problem);
- theoretical motivation behind the student's design choices;
- ability to clearly and concisely present the key points of the project;
- ability to support a discussion on possible alternative solutions and potential causes of failure of the solution developed.
The student must also demonstrate mastery of all the topics in the program (even those not addressed during the project).