Projektgruppen


Jarvis4MBSE

Projektbeschreibung

Jarvis4MBSE ist ein Tool für Model-based Systems Engineering (MBSE) das in einer kontinuierlichen Projektgruppe von Studenten der Universität Paderborn entwickelt wird. Es vereint moderne Visualisierungstechnik und aktuelle Methoden auf dem Bereich der künstlichen Intelligenz um die Ingenieure durch intuitive Benutzerinterkationen und einen eingebauten MBSE Assistenten zu unterstützen. Die aktuelle Version von Jarvis4MBSE setzt sich aus den folgenden Komponenten zusammen:

Backend
Speichert formalisierte Systemmodelle & führt Modelltransformationen durch

Multi-Platform-Frontend

  • Interaktive 3d Systemoberfläche für das Systemdesign
  • Interactive GUI for 2D representation & design of system models

Augmented Reality
Intuitive 3D Visualisierung der Modelle

MBSE Assistant
Eingebauter Assistent zur Wissensextraktion und Automatisierung von Entwicklungsaktivitäten

Gewünschte Vorkenntnisse

  • Gute Programmierkenntnisse
  • Vorkenntnisse in den Bereichen Modellierung und Modellierungssprachen (z.B. UML, SysML)
  • Interesse an Systems Engineering und Model-based Systems Engineering
  • Interdisziplinäres und Analytisches Denken

Lernziele

  • Praktische Erfahrung in Softwarespezifikation und Softwareentwicklung
  • Praktische Erfahrung in Systems Engineering und Model-based Systems Engineering
  • Expertise in modernen Konzepten zur Benutzerinteraktion und künstlichen Intelligenz
  • Projektmanagement, Präsentationsskills und Teamwork

Referenzen

Weitere Informationen finden Sie auf unserer Seite: https://jarvisformbse.github.io/jarvisformbse/

Ankündigungen

29. März 2019: Die Projektgruppe Jarvis4MBSE I wurde erfolgreich beendet. Das Ergebnis ist ein erster Prototyp und eine Reihe von User Stories für die nächsten Projektgruppen.

8. April 2019: Jarvis4MBSE II ist mit 17 Teilnehmern gestartet.


Digital tools for strategic planning (doorstep)

Contents

Within strategic product planning, there are several main tasks, such as determination of potentials, product discovering or business planning. Behind these tasks, in turn, are various subtasks, such as foresight and generation planning. The project DizRuPt can be located there. Here an instrument for the data-driven product planning is developed, which e.g. includes methods for hypothesis, data inventory and data analysis. But further-reaching topics such as the identification of trends and technologies or business forecasts in the context of foresight and business planning are conceivable. The aim of the project group is to identify and specify potential tools that support these tasks. Subsequently, a promising concept should be implemented. Assistants, documentation tools, games etc. are conceivable. In addition to an appealing UI, e. g. AI, Data Mining techniques and mobile technologies could be used.

Learning Outcome

  • Methods of (data-driven) Product Planning
  • Project Management
  • Software Specification and Programming
  • Presentation and Team Work

Course Details

See introduction slides (PDF)

Instructors

  • Maximilan Frank
  • Melina Massmann
  • Maurice Meyer

Appointments

We meet every Wednesday from 2 p.m. till 4 p.m. (Room: F0.225).

7 Oct 2019, 10 a.m.: Kick off (Room: F0.225)


Artificial Intelligence for Systems Engineering

Content

In the scope of this project group, we will develop AI-based assistance systems to support engineers during the design and development of technical systems. To this end, we will analyze the product creation process with a focus on (Model-based) Systems Engineering, identify potentials for the utilization of Artificial Intelligence and develop prototypes for the most promising ideas. This project group will be based on the results of the prior project group Jarvis4MBSE [1] and be conducted in close collaboration with the research project KI-Marktplatz (engl.: AI marketplace) [2]. Examples for AI-based assistant systems are:

The touch-based editor is able to understand hand-drawn system models and translate them into formal models, which, for example, are used for as input for system analyses.

 

The MBSE (Model-based Systems Engineering) Knowledge Graph builds up a knowledge graph from given MBSE models and uses this graph to provide suggestions for the creation of
new system models.

The virtual Systems Engineering expert is a chat-bot tailored towards Systems Engineering. It provides expert knowledge to the engineers and can handle engineering-specific requests.

Details

See introduction slides (PDF[RB1] )

[1] www.hni.uni-paderborn.de/ase/lehre/projektgruppen/

[2] https://ki-marktplatz.com/