Each module contains 3 ECTS. You choose a total of 10 modules/30 ECTS in the following module categories:
- 12-15 ECTS in technical scientific modules (TSM)
TSM modules teach profile-specific specialist skills and supplement the decentralised specialisation modules.
- 9-12 ECTS in fundamental theoretical principles modules (FTP)
FTP modules deal with theoretical fundamentals such as higher mathematics, physics, information theory, chemistry, etc. They will teach more detailed, abstract scientific knowledge and help you to bridge the gap between abstraction and application that is so important for innovation.
- 6-9 ECTS in context modules (CM)
CM modules will impart additional skills in areas such as technology management, business administration, communication, project management, patent law, contract law, etc.
In the module description (download pdf) you find the entire language information per module divided into the following categories:
Students learn and experience an advanced approach for designing an autonomous real-time process monitoring system (cyber-physical system)
- General mechanics
- IT basics
Students learn and experience an advanced approach for designing an autonomous real-time process monitoring system.
This will allow them to experience a development project by directly integrating an expert reflection on the digital autonomy expected of automated mechanisms in the Industry 4.0 world.
They will also be introduced to the multidisciplinary roles that the engineer of tomorrow ill have to play in the face of the challenges of digitization and the advent of intelligent and autonomous machines.
This course uses as a common thread the Micro5 eco-demonstrator developed in the framework of the HES-SO thematic programs (2013-2016) and recently equipped with an original and very advanced cognitive system.
Contents of Module
The learning objectives are to allow the student to develop a critical sense and to experience the steps and difficulties related to defining and developing an artificial intelligence system on a production tool.
The following steps will be covered:
- Positioning and role of the engineer in the digitalization of production means.
- Definition of a cognitive mechatronic system: from machining to control program.
- Definition of the objectives and methods of the system to be developed on the basis of a specific case (e.g., micro milling machine, wear detection, etc.).
- Definition of the tools needed to automate a machine sensors, database, AI, and feedback).
- Development of a cyber-physical production and management system (data selection, signal processing, feedback, real-time processing, data storage, SPC).
- Data analysis and processing.
- Introduction of prior knowledge into the cyber-physical system.
- Development of a digital twin.
Teaching and Learning Methods
Presentation by the professors of the main concepts and themes. Illustration via concrete, applied examples. Week by week, the students will conceive a simulated smart machine.
Students organized in teams will apply the concepts and themes to practical use cases. The application can vary from a case study to the realization of a mini-project in team.