Ole Schmedemann, M.Sc.

Room L2057

Telephone +49 40 42878-4102

Fax +49 40 42731-4551

Since January 2020	Research Associate at the Institute of Aircraft Production Technology
2016 - 2019	Master's degree in "Product Development, Materials and Production" at the TUHH
2017	September abroad at Luleå University of Technology
2012-2016	Bachelor's degree in "Mechanical Engineering" at the TUHH

Problem-oriented course: Applied Automation
Solving an automation technology task in teamwork using the KUKA YouBot

Fundamentals of machine tools

Use of augmented reality for iterative robot program optimisation in robot-automated series production processes
Wulff, Lukas Antonio; Schmedemann, Ole; Schüppstuhl, Thorsten
5th International Conference on Industry 4.0 and Smart Manufacturing, ISM (2023)
Open Access | Publisher DOI

Industrial segment anything - A case study in aircraft manufacturing, intralogistics, maintenance, repair, and overhaul
Moenck, Keno; Wendt, Arne; Prünte, Philipp Julian; Koch, Julian; Sahrhage, Arne; Gierecker, Johann; Schmedemann, Ole; Kähler, Falko; Holst, Dirk; Gomse, Martin; Schüppstuhl, Thorsten; Schoepflin, Daniel
arXiv: 2307.12674 (2023)
Open Access | Publisher DOI
Adapting synthetic training data in deep learning-based visual surface inspection to improve transferability of simulations to real-world environments
Schmedemann, Ole; Schlodinski, Simon; Holst, Dirk; Schüppstuhl, Thorsten
Automated Visual Inspection and Machine Vision V (2023)
Publisher DOI

Deep anomaly detection for endoscopic inspection of cast iron parts
Schmedemann, Ole; Miotke, Maximilian; Kähler, Falko; Schüppstuhl, Thorsten
31st International Conference on Flexible Automation and Intelligent Manufacturing (FAIM 2022)
Open Access | Publisher DOI
Anomaly detection for industrial surface inspection : application in maintenance of aircraft components
Kähler, Falko; Schmedemann, Ole; Schüppstuhl, Thorsten
Procedia CIRP 107: 246-251 (2022)
Open Access | Publisher DOI
Procedural synthetic training data generation for AI-based defect detection in industrial surface inspection
Schmedemann, Ole; Baaß, Melvin; Schoepflin, Daniel; Schüppstuhl, Thorsten
Procedia CIRP 107: 1101-1106 (2022)
Open Access | Publisher DOI
Configuration and enablement of vision sensor solutions through a combined simulation based process chain
Gierecker, Johann; Schoepflin, Daniel; Schmedemann, Ole; Schüppstuhl, Thorsten
Annals of Scientific Society for Assembly, Handling and Industrial Robotics 2021 (313-324)
Publisher DOI