MB » LPS » Team
Wiss. Mitarbeiter
Simon Fahle , M. Sc.
Vorträge
HUMAINE KI-Entwickler:innen-Arbeitskreis
Fahle, Simon
1. KI-Entwickler:innen-Arbeitskreis, 26.08.2021, digital
Investigation Of Suitable Methods For An Early Classification On Time Series In Radial-Axial Ring Rolling
Fahle, Simon; Glaser, Thomas; Kuhlenkötter, Bernd
CPSL 2021, 10.08.2021-11.08.2021, digital
Investigation of Machine Learning Models for a Time Series Classification Task in Radial–Axial Ring Rolling
Fahle, Simon; Glaser, Thomas; Kuhlenkötter, Bernd
ICTP 2021, 26.07.2021, digital
Research on Preprocessing Methods for Time Series Classification Using Machine Learning Models in the Domain of Radial-Axial Ring Rolling
Fahle, Simon; Kneißler, Andreas; Glaser, Thomas; Kuhlenkötter, Bernd
WGP-Jahreskongress 2020, 23.09.2020, digital
Systematic review on machine learning (ML) methods for manufacturing – Identifying artificial intelligence (AI) methods for field
Fahle, Simon; Prinz, Christopher; Kuhlenkötter, Bernd
Procedia CIRP, 02.07.2020, digital
Data-Survey RAW 2019
Fahle, Kuhlenkötter
Aachener Ringwalzforum, 11.11.2019, Aachen
Maschinelles Lernen - Was ist es und wofür kann es eingesetzt werden?
Fahle
Nemas-Innovationstreff, 27.11.2019, Kreuztal
Veröffentlichungen
Improving quality prediction in radial-axial ring rolling using a semi-supervised approach and generative adversarial networks for synthetic data generation
Fahle, Simon; Glaser, Thomas; Kneißler, Andreas; Kuhlenkötter, Bernd
Production Engineering , 2021 , DOI: https://doi.org/10.1007/s11740-021-01075-x .
Investigation Of Suitable Methods For An Early Classification On Time Series In Radial-Axial Ring Rolling
Fahle, Simon; Glaser, Thomas; Kuhlenkötter, Bernd
2nd Conference on Production Systems and Logistics , 2021 , DOI: https://doi.org/10.15488/11234 .
Investigation of Machine Learning Models for a Time Series Classification Task in Radial–Axial Ring Rolling
Fahle S., Glaser T., Kuhlenkötter B.
Forming the Future. The Minerals, Metals & Materials Series , 2021 , Springer , DOI: https://doi.org/10.1007/978-3-030-75381-8_48 .
Feature Engineering For A Cross-process Quality Prediction Of An End-of-line Hydraulic Leakage Test Using An Experiment Sample
Neunzig, Christian; Fahle, Simon; Kuhlenkötter, Bernd; Möller, Matthias
Proceedings of the 2nd Conference on Production Systems and Logistics (CPSL 2021) , 2021 , 156-166 , Hannover : Institutionelles Repositorium der Leibniz Universität Hannover , DOI: 10.15488/11269 .
Comparison on the Processing of Height Deviations of Disks from FEM and Real Rollings in Radial-Axial Ring Rolling
Glaser T., Schwarz P., Fahle S., Paffrath K.U., Kuhlenkötter B.
Forming the Future. The Minerals, Metals & Materials Series , 2021 , Springer , DOI: https://doi.org/10.1007/978-3-030-75381-8_245 .
Human-Centered Artificial Intelligence Application: Recognition of Manual Assembly Movements for Skill-Based Enhancements
Prinz C., Fahle S., Kuhlenkötter B., Losacker N., Zhang W., Cai W.
Proceedings of the Conference on Learning Factories (CLF) , 2021 , DOI: http://dx.doi.org/10.2139/ssrn.3861613 .
Research on Preprocessing Methods for Time Series Classification Using Machine Learning Models in the Domain of Radial-Axial Ring Rolling
Fahle, Simon; Kneißler, Andreas; Glaser, Thomas; Kuhlenkötter, Bernd
Proceedings of the 10th Congress of the German Academic Association for Production Technology (WGP), Dresden, 23-24 September 2020 , 2020 , Springer , ISBN: 978-3-662-62138-7 , DOI: https://doi.org/10.1007/978-3-662-62138-7_49 .
Systematic review on machine learning (ML) methods for manufacturing processes – Identifying artificial intelligence (AI) methods for field application
Fahle, Simon; Prinz, Christopher; Kuhlenkötter, Bernd
Procedia CIRP Vol 93 , 2020 , Pages 413-418 , Elsevier B.V. , DOI: https://doi.org/10.1016/j.procir.2020.04.109 .
Investigation of compaction by ring rolling on thermal sprayed coatings
Glaser, T.; Kuhlenkötter, B.; Fahle, S.; Husmann, S.; Abdulgader, M.; Tillmann, W.
Procedia Manufacturing 50 , 2020 , 192-198 , DOI: 10.1016/j.promfg.2020.08.036 .
Resistance-Based Temperature Monitoring Using Machine Learning and Adapted Activation for an SMA Locking System in Aircraft Interiors
Theren, Benedict; Fahle, Simon; Weirich, Antonia; Kuhlenkötter, Bernd
ASME 2020 Conference on Smart Materials, Adaptive Structures and Intelligent Systems Proceedings , 2020 , DOI: https://doi.org/10.1115/SMASIS2020-2249 .
A Practical Training Approach in Learning Factories to Make Artificial Intelligence Tangible
Oberc, Henning; Fahle, Simon; Prinz, Christopher; Kuhlenkötter, Bernd
Procedia CIRP Vol 93 , 2020 , Pages 467-472 , Elsevier B.V. , DOI: https://doi.org/10.1016/j.procir.2020.04.074 .
A Framework for Data Integration and Analysis in Radial-Axial Ring Rolling
Fahle, Simon; Kuhlenkötter, Bernd
Proceedings of the 1st Conference on Production Systems and Logistics (CPSL 2020) , 2020 , 127-136 , DOI: https://doi.org/10.15488/9654 .
Wirtschaftlichkeitsbewertung auf dem Weg zum CPPS - Entwicklung eines ganzheitlichen Ansatzes zur Wirtschaftlichkeitsbewertung mitttels Betrachtung von Interdependenzen
T. Wienbruch, S. Leineweber, S. Fahle, B. Kuhlenkötter
Industrie Management , 2019 , GITO .
Projekte
humAIne
Human Centered AI Network, 01.04.2021 - 31.03.2026
Kompetenzzentrum HUMAINE Transfer-Hub der Metropole Ruhr für die humanzentrierte Arbeit mit KI
Fehlervermeidung in Radial-Axial Ringwalzprozessen durch Online-Analyse der Zustandsdaten
01.02.2019 - 01.02.2021