Daniel Knüttel

Dr. Daniel Knüttel

Postal addressinspire AG
c/o SUPSI
Dr. Daniel Knüttel
Via Serafino Balestra 16
6900 Lugano
Phone+41 44 556 58 74
Email
Websitehttps://inspire.ch/de/forschung-fuer-die-industrie/robotik/industrie-4.0-digitalisierung-iot/imp-d
CategoryHead Intelligent Production Systems
GroupIntelligent Production Systems
Language SkillsGerman, English, French, Italian
Competences

 

  • AI in automation
  • Automation in quality control
  • AI-based workflow automation
  • Predictive quality forecasting
Reference Projects
  • EIT manufacturing OSCAR: Optical Scan and Repair solution to automate the preparation process of repairing with Direct Metal Deposition
  • EIT manufacturing VSPOOL: Virtual Stock Pooling Platform. LLM based Automated Technical Document Processing
  • Development of a predictive quality control framework for the watch industry. 117.970 IP-ICT Oris Predictive Analysis and Learning
  • EIT manufacturing Doremi: Digital Twin based set-up time estimation
Publications
  • Knüttel, Daniel, et al. "Machine learning based track height prediction for complex tool paths in direct metal deposition." CIRP Annals 71.1 (2022): 193-196.
  • Knüttel, Daniel, et al. "Automated repairing process of metal components in manufacturing with directed energy deposition." International Journal of Mechatronics and Manufacturing Systems 17.2 (2024): 150-179.
  • Carpanzano, Emanuele, and Daniel Knüttel. "Advances in artificial intelligence methods applications in industrial control systems: Towards cognitive self-optimizing manufacturing systems." Applied sciences 12.21 (2022): 10962.
  • Knüttel, Daniel, et al. "Transfer learning of neural network based process models in direct metal deposition." Procedia CIRP 107 (2022): 863-868.