• Skip navigation
  • Skip to navigation
  • Skip to the bottom
Simulate organization breadcrumb open Simulate organization breadcrumb close
FAPS – Institute for Factory Automation and Production Systems
  • FAUTo the central FAU website
  • Contact

FAPS – Institute for Factory Automation and Production Systems

Navigation Navigation close
  • Current
    • News
    • FAPS in Press
    • FAPS Information Sheet
    • Events
    • Annual Reports
    • Books
    Portal Current
  • Career
    • Scientific Positions
    • Non-scientific Positions
    • HiWi Positions
    • Job offers from our partners
    • International PhD Candidates
    • FAPS-X
    Portal Career
  • The Chair
    • Principles
    • History
    • Organization
    • Staff
    • Site Locations
    • Equipment
    • Doctorates
    • FAPS Alumni Network
    Portal The Chair
  • Research
    • Research Sectors
      • Electronics Production
      • Electric Motor Production
      • Signal and power networks
      • Biomechatronics
      • Engineering Systems
    • Technology Fields
    • FAPS Information Sheet
    • Research Projects
    • Completed Research Projects
    • Publications
    Portal Research
  • Studies
    • Courses
    • Thesis Topics
      • Electronics Production
      • Electric motor production
      • Home Automation
    • HiWi Positions
    • Project on Applied AI
    • FAPS Fellowship
    • Letter of Recommendation
    • FAPS Research Master
    Portal Studies
  • Cooperation
    • Types of Cooperation
    • Technology Transfer
    • Services
      • Electronics Production
      • Electric motor production
      • Biomechatronics
      • Engineering Systems
    • MID Application Center
    • Associations
    • FAPS ProNet e. V.
    Portal Cooperation
  1. Home
  2. Research
  3. Technology Fields
  4. Artificial Intelligence and Machine Learning

Artificial Intelligence and Machine Learning

In page navigation: Research
  • Research Sectors
    • Robotics
    • Engineering Systems
    • Automation Technology
    • Medical Technology
    • Electronics Production
    • Electric Motor Production
    • Electric Road Systems
    • Signal and power networks
    • Home Automation
  • Technology Fields
    • Construction and connection technology
    • Additive Mechatronics
    • Automated Production Systems
    • Artificial Intelligence and Machine Learning
    • Communication and cooperation
    • Planning and Simulation
    • Energy and Ecology
    • Innovative Quality Management
    • Energy Storage
    • Process and Material Analytics
    • Software Engineering and Deployment
    • Autonomous Mobile Systems
  • FAPS Information Sheet
  • Research Projects
  • Completed Research Projects
  • Publications

Artificial Intelligence and Machine Learning

Definition

In the course of digitalization, interconnected plants and intelligent products are generating ever-increasing amounts of data. Artificial intelligence methods, especially machine learning, make it possible to analyze this data profitably and generate knowledge from it. This knowledge, in turn, must be represented and linked in such a way that existing data silos can be broken down, end-to-end data integration can be established, and user-friendly applications can be realized.

Vision

The technology field supports industry in identifying and exploiting the various potentials of AI, especially machine learning. Furthermore, it serves the knowledge transfer within the institute.

Focus areas

  • Data management and databases (e.g., SQL, NoSQL)
  • Edge cloud architectures and machine learning operations (MLOps)
  • Data pre-processing (e.g., feature engineering) and explorative data analysis using statistical methods
  • Machine learning, deep learning (e.g., convolutional neural networks, transformers), and reinforcement learning
  • Generative AI (e.g., large language models such as ChatGPT, generative adversarial networks)
  • Knowledge graphs based on semantic web technologies

Application Fields

  • AI applications in the Industry 4.0 environment (e.g., automatic visual inspection, predictive maintenance, process monitoring, process control, process optimization)
  • Knowledge-based assistance systems in engineering (e.g., constraint-based configurators, knowledge graphs)
  • AI systems in medical technology applications (e.g., environment segmentation for visually impaired people)

Head of Technology Field

  • Andreas Mayr, M.Sc., M.Sc.

Members

  • Marcel Baader, M.Sc.
  • Helmut Engelhardt, M.Sc.
  • Jan Fröhlich, M.Sc.
  • Simon Fröhlig, M.Sc.
  • Gabriela García, M.Sc.
  • Andreas Gründer, M.Sc.
  • Benjamin Gutwald, M.Sc.
  • Annalena Hartmann, M.Sc.
  • Bernd Hofmann, M.Sc.
  • Lucas Janisch, M.Sc.
  • Oguz Kedilioglu, M.Sc.
  • Christoph Konrad, M.Sc.
  • Felix Mahr, M.Sc.
  • Sven Meier, M.Sc., M.Sc.
  • Andreas Morello, M.Sc.
  • Alexander Müller, M.Sc.
  • Huong Giang Nguyen, M.Sc.
  • Daniela Pisanu, M.Sc.
  • Anja Preitschaft, M.Sc.
  • Ben Rachinger, M.Sc.
  • Tim Raffin, M.Sc.
  • Tobias Reichenstein, M.Sc.
  • Albert Scheck, M.Sc.
  • Benedikt Scheffler, M.Sc.
  • Simon Schlichte, M.Sc.
  • Elisabeth Schmidl, M.Eng.
  • Alexander Schneider, M.Sc.
  • Dr. Reinhardt Seidel, M.Sc.
  • Till Sindel, M.Sc.
  • Oliver Stelter, M.Sc.
  • Dipl.-Ing. Ludwig Streloke
  • Nils Thielen, M.Sc.
  • Jann Warnecke, M.Sc.
  • Patrick Ziegler, M.Sc.
Friedrich-Alexander-Universität
Erlangen-Nürnberg

Schlossplatz 4
91054 Erlangen
  • Sitemap
  • Imprint
  • Privacy
  • Accessibility
  • Facebook
  • RSS Feed
  • Twitter
  • Xing
  • YouTube
Up