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  2021 (1)
Object Detection for Smart Factory Processes by Machine Learning. Malburg, L.; Rieder, M.; Seiger, R.; Klein, P.; and Bergmann, R. In The 4th International Conference on Emerging Data and Industry 4.0 (EDI40), Warsaw, Poland, March 23 - 26, 2021, of Procedia Computer Science, 2021. Elsevier Accepted for publication. Preprint available soon.
bibtex   abstract  
  2020 (3)
Using Physical Factory Simulation Models for Business Process Management Research. Malburg, L.; Seiger, R.; Bergmann, R.; and Weber, B. In del-Río-Ortega , A.; Leopold, H.; and Santoro, F. M., editor(s), Business Process Management Workshops - BPM 2020 International Workshops, Sevilla, Spain, September 13 - 18, 2020, volume 397, of Lecture Notes in Business Information Processing, pages 95–107, 2020. Springer The original publication is available at www.springerlink.com
Using Physical Factory Simulation Models for Business Process Management Research [pdf]Paper   doi   bibtex   abstract  
Enhancing Siamese Neural Networks through Expert Knowledge for Predictive Maintenance. Klein, P.; Weingarz, N.; and Bergmann, R. In IoT Streams for Data-Driven Predictive Maintenance and IoT, Edge, and Mobile for Embedded Machine Learning, volume 1325, of Communications in Computer and Information Science, 2020. Springer International Publishing. Accepted for publication.
Enhancing Siamese Neural Networks through Expert Knowledge for Predictive Maintenance [pdf]Paper   doi   bibtex   abstract  
Semantic Web Services for AI-Research with Physical Factory Simulation Models in Industry 4.0. Malburg, L.; Klein, P.; and Bergmann, R. In Panetto, H.; Madani, K.; and Smirnov, A. V., editor(s), Proceedings of the International Conference on Innovative Intelligent Industrial Production and Logistics, IN4PL 2020, Budapest, Hungary, November 2-4, 2020, pages 32-43, 2020. SCITEPRESS.
Semantic Web Services for AI-Research with Physical Factory Simulation Models in Industry 4.0 [pdf]Paper   doi   bibtex   abstract  
  2019 (2)
Generation of Complex data for AI-Based Predictive Maintenance Research With a Physical Factory Model. Klein, P.; and Bergmann, R. In 16th International Conference on Informatics in Control Automation and Robotics, ICINCO 2019, Prague, Czech Republic, Proceedings , volume 1, pages 40-50, 2019. INSTICC, SciTePress.
Generation of Complex data for AI-Based Predictive Maintenance Research With a Physical Factory Model [pdf]Paper   doi   bibtex  
FTOnto: A Domain Ontology for a Fischertechnik Simulation Production Factory by Reusing Existing Ontologies. Klein, P.; Malburg, L.; and Bergmann, R. In Jäschke, R.; and Weidlich, M., editor(s), Proceedings of the Conference on "Lernen, Wissen, Daten, Analysen", Berlin, Germany, September 30 - October 2, 2019., volume 2454, of CEUR Workshop Proceedings, pages 253–264, 2019. CEUR-WS.org
FTOnto: A Domain Ontology for a Fischertechnik Simulation Production Factory by Reusing Existing Ontologies [pdf]Paper   bibtex   abstract  
  2018 (1)
Data Generation with a Physical Model to Support Machine Learning Research for Predictive Maintenance. Klein, P.; and Bergmann, R. In Lernen. Wissen. Daten. Analysen. (LWDA 2018), 2018. CEUR Workshop Proceedings
Data Generation with a Physical Model to Support Machine Learning Research for Predictive Maintenance [pdf]Paper   bibtex