@article{4589,
  author       = {{Schriegel, Sebastian and Pethig, Florian and Windmann, Stefan and Jasperneite, Jürgen}},
  journal      = {{ Automation 2017, Baden-Baden}},
  title        = {{{PROFIanalytics - die Brücke zwischen PROFINET und Cloud-basierter Prozessdatenanalyse}}},
  year         = {{2017}},
}

@book{4595,
  author       = {{Pethig, Florian and Schriegel, Sebastian and Maier, Alexander and Otto, Jens and Windmann, Stefan and Böttcher, Björn and Niggemann, Oliver and Jasperneite, Jürgen}},
  isbn         = {{ 978-3-8163-0709-9}},
  publisher    = {{VDMA Guideline, Publisher: VDMA Verlag GmbH, Editor: Verband Deutscher Maschinen- und Anlagenbau e.V.}},
  title        = {{{Industrie 4.0 Communication Guideline Based on OPC UA}}},
  year         = {{2017}},
}

@misc{4906,
  author       = {{Borcherding, Holger and Austermann, Johann and Otte, Raphael and Windmann, Stefan and Köster, Markus and Stichweh, Heiko and Grabs, Volker and Ehlich, Martin and Hohnsbein, Thorsten}},
  publisher    = {{TIB Hannover}},
  title        = {{{Intelligente Antriebs- und Steuerungstechnik für die energieeffiziente Intralogistik}}},
  year         = {{2017}},
}

@inproceedings{4620,
  author       = {{Windmann, Stefan and Jasperneite, Jürgen}},
  booktitle    = {{IEEE International Conference on Emerging Technologies and Factory Automation (ETFA 2015)}},
  title        = {{{An FPGA Based FIFO with Efficient Memory Management}}},
  year         = {{2015}},
}

@inproceedings{4795,
  author       = {{Niggemann, Oliver and Windmann, Stefan and Volgmann, Sören and Bunte, Andreas and Stein, Benno}},
  booktitle    = {{International Workshop on the Principles of Diagnosis (DX)}},
  publisher    = {{Graz, Austria}},
  title        = {{{Using Learned Models for the Root Cause Analysis of Cyber-Physical Production Systems}}},
  year         = {{2014}},
}

@article{4199,
  author       = {{Niggemann, Oliver and Borcherding, Holger and Köster, Markus and Windmann, Stefan and Ehlich, Martin}},
  issn         = {{1436-4980}},
  journal      = {{Werkstattstechnik : wt}},
  number       = {{5}},
  pages        = {{416 -- 422}},
  publisher    = {{Springer}},
  title        = {{{Energieeffizienz in der Intralogistik : Elektrische Antriebstechnik - intelligent und nachhaltig}}},
  year         = {{2013}},
}

@inproceedings{4276,
  abstract     = {{In the presented work, the detection of anomalous energy consumption in hybrid industrial production systems is investigated. A model-based approach with a timed hybrid automaton as overall system model is employed for anomaly detection. The approach is based on the assumption of several system modes, i.e. phases with continuous system behavior. Transitions between the modes are attributed to discrete control events such as on/off signals. The underlying discrete event system which comprises both system modes and transitions is modeled as finite state machine. The focus of this paper is set on the modeling of the energy consumption in the particular system modes. Sequences of stochastic state space models are employed for this purpose. Model learning and anomaly detection for this approach are considered. The proposed approach is further evaluated in a small model factory. The experimental results show significant improvements compared to existing approaches to anomaly detection in hybrid industrial systems.}},
  author       = {{Windmann, Stefan and Jiao, Shuo and Niggemann, Oliver and Borcherding, Holger}},
  booktitle    = {{11th International IEEE Conference on Industrial Informatics}},
  location     = {{Bochum}},
  pages        = {{194 -- 199}},
  publisher    = {{IEEE}},
  title        = {{{A Stochastic Method for the Detection of Anomalous Energy Consumption in Hybrid Industrial Systems}}},
  year         = {{2013}},
}