This image shows Benjamin Maschler

Benjamin Maschler

M.Sc.

Academic staff
Institute of Industrial Automation and Software Engineering

Contact

+49 711 685 67295
+4971168567302

Pfaffenwaldring 47
70550 Stuttgart
Germany
Room: 1.115

Journals and Conferences:
  1. 2021

    1. B. Maschler, D. Braun, N. Jazdi, and M. Weyrich, “Transfer Learning as an Enabler of the Intelligent Digital Twin,” in 31st CIRP Design Conference, Enschede, The Netherlands, May 2021, 2021.
    2. M. Weiß, P. Marks, B. Maschler, D. White, P. Kesseli, and M. Weyrich, “Towards establishing formal verification and inductive code synthesis in the PLC domain,” in 19th IEEE International Conference on Industrial Informatics (INDIN), Palma de Mallorca, Spain, July 2021, 2021.
    3. B. Maschler, S. Kamm, and M. Weyrich, “Deep industrial transfer learning at runtime for image recognition,” at - Automatisierungstechnik, vol. 69, no. 3, pp. 211-220, 03.2021, 2021.
    4. B. Maschler, T. Müller, A. Löcklin, and M. Weyrich, “Transfer Learning as an Enhancement for Reconfiguration Management of Cyber-Physical Production Systems,” in 15th CIRP Conference on Intelligent Computation and Manufacturing Engineering, July 2021, Gulf of Naples, Italy, 2021.
    5. B. Maschler, S. Tatiyosyan, and M. Weyrich, “Regularization-based Continual Learning for Fault Prediction in Lithium-Ion Batteries,” in 15th CIRP Conference on Intelligent Computation and Manufacturing Engineering, July 2021, Gulf of Naples, Italy, 2021.
    6. B. Maschler and M. Weyrich, “Deep Transfer Learning for Industrial Automation,” IEEE Industrial Electronics Magazine, vol. 15, no. 2, pp. 65-75, June 2021, 2021.
    7. B. Maschler, T. T. H. Pham, and M. Weyrich, “Regularization-based Continual Learning for Anomaly Detection in Discrete Manufacturing,” in 54th CIRP Conference on Manufacturing Systems, Athens, Greece, Vol. 104, pp. 452-457, November 2021, 2021.
    8. B. Lindemann, B. Maschler, N. Sahlab, and M. Weyrich, “A survey on anomaly detection for technical systems using LSTM networks,” Computers in Industry, vol. 131, pp. 103498, June 2021, 2021.
    9. B. Maschler, T. Knodel, and M. Weyrich, “Towards Deep Industrial Transfer Learning for Anomaly Detection on Time Series Data,” in 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), 07-10 Sept. 2021, Västerås, Sweden, 2021.
  2. 2020

    1. B. Maschler and M. Weyrich, “Deep Transfer Learning at Runtime for Image Recognition in Industrial Automation Systems,” in 16th Technical Conference EKA – Design of Complex Automation Systems (Virtual Conference), Mai 2020, Magdeburg, pp. 15-21, 2020.
    2. B. Maschler, S. Kamm, N. Jazdi, and M. Weyrich, “Distributed Cooperative Deep Transfer Learning for Industrial Image Recognition,” in 53rd CIRP Conference on Manufacturing Systems (Virtual Conference), 1-3 July 2020, Chicago, pp. 437-442, 2020.
    3. B. Maschler, D. White, and M. Weyrich, “Anwendungsfälle und Methoden der künstlichen Intelligenz in der anwendungsorientierten Forschung im Kontext von Industrie 4.0,” in ten Hompel M., Vogel-Heuser B., Bauernhansl T. (Eds.) Handbuch Industrie 4.0. Springer Reference Technik. Springer Vieweg, Berlin, Heidelberg, published online: 24.11.2020, p. 1-15, 2020.
    4. B. Maschler, H. Vietz, N. Jazdi, and M. Weyrich, “Continual Learning of Fault Prediction for Turbofan Engines using Deep Learning with Elastic Weight Consolidation,” in 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), 8-11 Sept. 2020, Vienna, Austria, pp. 959-966, 2020.
    5. B. Maschler, S. Ganssloser, A. Hablizel, and M. Weyrich, “Deep learning based soft sensors for industrial machinery,” in 14th CIRP Conference on Intelligent Computation in Manufacturing Engineering, CIRP ICME ’20 (Virtual Conference), 15-17 July 2020, Gulf of Naples, Italy, 2020.
    6. N. Jazdi, B. Ashtari Talkhestani, B. Maschler, and M. Weyrich, “Realization of AI-enhanced industrial automation systems using intelligent Digital Twins,” in 8th CIRP Conference of Assembly Technology and Systems (Virtual Conference), 30.09.-01.10.2020, Athens, Greece, pp. 396-400, 2020.
  3. 2019

    1. M. Klein, B. Maschler, A. Zeller, B. Ashtari Talkhestani, N. Jazdi, R. Rosen, and M. Weyrich, “Architektur und Technologiekomponenten eines digitalen Zwillings,” in 20. Leitkonferenz der Mess- und Automatisierungstechnik Automation 2019, 02.-03.Juli 2019, Baden-Baden, 2019.
    2. B. Maschler, N. Jazdi, and M. Weyrich, “Maschinelles Lernen für intelligente Automatisierungssysteme mit dezentraler Datenhaltung am Anwendungsfall Predictive Maintenance,” in 20. Leitkonferenz der Mess- und Automatisierungstechnik Automation 2019, 02.-03.Juli 2019, Baden-Baden, 2019.
  4. 2018

    1. M. Weyrich, A. Zeller, B. Maschler, T. Jung, and others, VDI-Statusreport Testen vernetzter Systeme für Industrie 4.0. VDI/VDE-Gesellschaft Mess- und Automatisierungstechnik, 2018.

Research focus: Development of methods for decentralized machine learning without an exchange of raw data for applications in automation.

Description: In many cases, machine learning holds the danger of a loss of confidential data. The use of continual learning approaches as an alternative to cloud-based techniques allows for a preservation of control over such data.

At the IAS, methods are developed using continual learning to allow for both, protecting data and using artificial intelligence techniques in the field of automation.

Research portal: ResearchGate Benjamin Maschler

  • Chair of the Board of the Doctoral Candidates’ Convention of the University of Stuttgart (DoKUS)
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