MSE Master of Science in Engineering

The Swiss engineering master's degree

Chaque module vaut 3 ECTS. Vous sélectionnez 10 modules/30 ECTS parmi les catégories suivantes:

  • 12-15 crédits ECTS en Modules technico-scientifiques (TSM)
    Les modules TSM vous transmettent une compétence technique spécifique à votre orientation et complètent les modules de spécialisation décentralisés.
  • 9-12 crédits ECTS en Bases théoriques élargies (FTP)
    Les modules FTP traitent de bases théoriques telles que les mathématiques élevées, la physique, la théorie de l’information, la chimie, etc., vous permettant d’étendre votre profondeur scientifique abstraite et de contribuer à créer le lien important entre l’abstraction et l’application dans le domaine de l’innovation.
  • 6-9 crédits ECTS en Modules contextuels (CM)
    Les modules CM vous transmettent des compétences supplémentaires dans des domaines tels que la gestion des technologies, la gestion d’entreprise, la communication, la gestion de projets, le droit des brevets et des contrats, etc.

Le descriptif de module (download pdf) contient le détail des langues pour chaque module selon les catégories suivantes:

  • leçons
  • documentation
  • examen 
Intelligent and Hyperconnected Machine (FTP_SmartMach)

Students learn and experience an advanced approach for designing an autonomous real-time process monitoring system (cyber-physical system)

Compétences préalables

 

  • General mechanics
  • IT basics 

 

Objectifs d'apprentissage

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.


Contenu des modules

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.

Méthodes d'enseignement et d'apprentissage

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.

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