MSE Master of Science in Engineering

The Swiss engineering master's degree

Jedes Modul umfasst 3 ECTS. Sie wählen insgesamt 10 Module/30 ECTS in den folgenden Modulkategorien:

  • ​​​​12-15 ECTS in Technisch-wissenschaftlichen Modulen (TSM)
    TSM-Module vermitteln Ihnen profilspezifische Fachkompetenz und ergänzen die dezentralen Vertiefungsmodule.
  • 9-12 ECTS in Erweiterten theoretischen Grundlagen (FTP)
    FTP-Module behandeln theoretische Grundlagen wie die höhere Mathematik, Physik, Informationstheorie, Chemie usw. Sie erweitern Ihre abstrakte, wissenschaftliche Tiefe und tragen dazu bei, den für die Innovation wichtigen Bogen zwischen Abstraktion und Anwendung spannen zu können.
  • 6-9 ECTS in Kontextmodulen (CM)
    CM-Module vermitteln Ihnen Zusatzkompetenzen aus Bereichen wie Technologiemanagement, Betriebswirtschaft, Kommunikation, Projektmanagement, Patentrecht, Vertragsrecht usw.

In der Modulbeschreibung (siehe: Herunterladen der vollständigen Modulbeschreibung) finden Sie die kompletten Sprachangaben je Modul, unterteilt in die folgenden Kategorien:

  • Unterricht
  • Dokumentation
  • Prüfung
Intelligent and Hyperconnected Machine (FTP_SmartMach)

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

Eintrittskompetenzen

 

  • General mechanics
  • IT basics 

 

Lernziele

Students learn and experience an advanced approach to 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-designer of tomorrow will have to play in the face of the challenges of digitization and the advent of intelligent and autonomous machines.

This course uses as a red 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.


Modulkategorie

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-designer in the face of digitalization issues
  • Definition of a digital cognitive system (prospective and decision-making capacities)
  • Goals to be achieved by the system being developed (issues and methods)
  • Definition of the tools to be developed
  • Development of a relevant cyber-physical system in production (choice of relevant data, signal processing, documentation and data feedback, real-time management, data storage)
  • Data processing and analysis
  • Experimentation through monitored and precursor machining (visualization, experience report)
  • Digitalisation of know-how (empowerment tools)
  • Development of a digital behavioral twin

 

Lehr- und Lernmethoden

Theory:

  • Cognitive system (what and how)
  • Prospective capabilities
  • Cyber-physical system
  • Data feedback and analysis

Practical:

  • Application to machines
  • Case studies

Experimentation:

  • Machining with data feedback
  • Labeling
  • Analyses
  • AI restitution

 

Vollständige Modulbeschreibung herunterladen

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