O. Niggemann

发表

Machine Learning for Cyber-Physical Systems

Henrik S. Steude, J. Beyerer, C. Kühnert, 2022, Digital Transformation.

Network Configuration : Approaches for Solving the Cable Management Problem ⋆

M. Suermann, O. Niggemann, B. Stein, 2012 .

A Research Agenda for AI Planning in the Field of Flexible Production Systems

O. Niggemann, Aljosha Köcher, Aljosha Kocher, 2021, 2022 IEEE 5th International Conference on Industrial Cyber-Physical Systems (ICPS).

Diagnosis in Automotive Applications A Case Study with the Model Compilation Approach

Benno Stein, O. Niggemann, H. Balzer, 2006 .

Combining Automotive System and Function Models to Support Code Generation and Early System Verification

Oliver Niggemann, Dirk Stichling, Dirk Fleischer, 2008 .

A Sampling-Based Method for Robust and Efficient Fault Detection in Industrial Automation Processes

O. Niggemann, Stefan Windmann, 2018 .

Anomaly Detection with Autoencoders as a Tool for Detecting Sensor Malfunctions

O. Niggemann, W. Weber, Artur Liebert, 2022, 2022 IEEE 5th International Conference on Industrial Cyber-Physical Systems (ICPS).

Learning Physical Concepts in CPS: A Case Study with a Three-Tank System

Henrik S. Steude, O. Niggemann, Alexander Windmann, 2022, IFAC-PapersOnLine.

Anomaly detection based on time series data from industrial automatic sewing machines

O. Niggemann, Daniel Vranjes, 2022, 2022 IEEE 5th International Conference on Industrial Cyber-Physical Systems (ICPS).

Neural Network Modeling of Nonlinear Filters for EMC Simulation in Discrete Time Domain

J. Friebe, O. Niggemann, Jan-Philipp Roche, 2021, IECON 2021 – 47th Annual Conference of the IEEE Industrial Electronics Society.

On a Uniform Causality Model for Industrial Automation

O. Niggemann, René Heesch, Alexander Windmann, 2022, ArXiv.

Learning Physically Meaningful Representations of Energy Systems with Variational Autoencoders

P. Bretschneider, O. Niggemann, S. Multaheb, 2022, 2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA).

An AI benchmark for Diagnosis, Reconfiguration & Planning

O. Niggemann, Alexander Diedrich, René Heesch, 2022, 2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA).

Knowledge Based Grey Box Modeling of Inaccessible Circuits for System EMC-Simulation in Time Domain

J. Friebe, O. Niggemann, Jan-Philipp Roche, 2022, 2022 24th European Conference on Power Electronics and Applications (EPE'22 ECCE Europe).

AutoConf: New Algorithm for Reconfiguration of Cyber-Physical Production Systems

O. Niggemann, Kaja Balzereit, 2023, IEEE Transactions on Industrial Informatics.

Field-Theoretic Thermodynamic Uncertainty Relation

U. Seifert, O. Niggemann, 2020, Journal of Statistical Physics.

LSTM for Model-based Anomaly Detection in Cyber-Physical Systems pdf

Oliver Niggemann, Benedikt Eiteneuer, O. Niggemann, 2020, DX.

On Residual-based Diagnosis of Physical Systems

O. Niggemann, Alexander Diedrich, 2022, Eng. Appl. Artif. Intell..

Diagnosing Systems through Approximated Information

O. Niggemann, Alexander Diedrich, 2021, Annual Conference of the PHM Society.

A Data Provenance based Architecture to Enhance the Reliability of Data Analysis for Industry 4.0

Peng Li, Oliver Niggemann, Peng Li, 2018, 2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA).

Non-convex hull based anomaly detection in CPPS

Oliver Niggemann, Peng Li, Peng Li, 2020, Eng. Appl. Artif. Intell..

Visual data mining of graph based data

Oliver Niggemann, O. Niggemann, 2001 .

A stochastic method for the detection of anomalous energy consumption in hybrid industrial systems

Oliver Niggemann, Shuo Jiao, Stefan Windmann, 2013, 2013 11th IEEE International Conference on Industrial Informatics (INDIN).

The Two Scaling Regimes of the Thermodynamic Uncertainty Relation for the KPZ-Equation

U. Seifert, O. Niggemann, 2021, Journal of Statistical Physics.

Problem examination for AI methods in product design pdf

Oliver Niggemann, Philipp Rosenthal, O. Niggemann, 2022, ArXiv.

A self-configurable fault detection system for Industrial Ethernet networks

Oliver Niggemann, Stefan Windmann, O. Niggemann, 2017, Autom..

Visualization of traffic structures

Benno Stein, Oliver Niggemann, Jens Tölle, 2001, ICC 2001. IEEE International Conference on Communications. Conference Record (Cat. No.01CH37240).

Learning Complex Similarity Measures

Benno Stein, Oliver Niggemann, Benno Stein, 2000 .

Automated Reconfiguration of Cyber-Physical Production Systems using Satisfiability Modulo Theories

Oliver Niggemann, Kaja Balzereit, O. Niggemann, 2020, 2020 IEEE Conference on Industrial Cyberphysical Systems (ICPS).

Anomaly Detection and Localization for Cyber-Physical Production Systems with Self-Organizing Maps

Oliver Niggemann, Alexander von Birgelen, O. Niggemann, 2018 .

Improving remote material classification ability with thermal imagery

O. Niggemann, Willi Großmann, Helena Horn, 2022, Scientific Reports.

On Visual Analytics in Plant Monitoring

Oliver Niggemann, Alexander Maier, Tim Tack, 2014 .

Visual Anomaly Detection in Production Plants

Oliver Niggemann, Alexander Maier, Tim Tack, 2012, ICINCO.

Integrating semantics for diagnosis of manufacturing systems

Oliver Niggemann, Andreas Bunte, Alexander Diedrich, 2016, 2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA).

The importance of model-learning for the analysis of the energy consumption of production plants

Oliver Niggemann, Bjorn Kroll, Florian Pethig, 2013, 2013 IEEE 18th Conference on Emerging Technologies & Factory Automation (ETFA).

Automated generation of timing models in distributed production plants

O. Niggemann, A. Maier, M. Koester, 2013, 2013 IEEE International Conference on Industrial Technology (ICIT).

Learning Behavior Models for Hybrid Timed Systems

Benno Stein, Hans Kleine Büning, Oliver Niggemann, 2012, AAAI.

Solving Modeling Problems with Machine Learning -- A Classification Scheme of Model Learning Approaches for Technical Systems

Benno Stein, Oliver Niggemann, Alexander Maier, 2012, MBEES.

Automatic Parameter Estimation for Reusable Software Components of Modular and Reconfigurable Cyber-Physical Production Systems in the Domain of Discrete Manufacturing

Oliver Niggemann, Birgit Vogel-Heuser, Jens Otto, 2018, IEEE Transactions on Industrial Informatics.

Why Cyber-physical Production Systems Need a Descriptive Engineering Approach – A Case Study in Plug & Produce

Oliver Niggemann, Jens Otto, Steffen Henning, 2014 .

Inference Methods for Detecting the Root Cause of Alarm Floods in Causal Models

Oliver Niggemann, Paul Wunderlich, O. Niggemann, 2018, 2018 23rd International Conference on Methods & Models in Automation & Robotics (MMAR).

High Accuracy Uncertainty-Aware Interatomic Force Modeling with Equivariant Bayesian Neural Networks

D. Kramer, O. Niggemann, Tim Rensmeyer, 2023, ArXiv.

Dimensionality Reduction and Anomaly Detection for CPPS Data using Autoencoder

Oliver Niggemann, Benedikt Eiteneuer, Nemanja Hranisavljevic, 2019, 2019 IEEE International Conference on Industrial Technology (ICIT).

A HMM-based fault detection method for piecewise stationary industrial processes

Oliver Niggemann, Stefan Windmann, Florian Jungbluth, 2015, 2015 IEEE 20th Conference on Emerging Technologies & Factory Automation (ETFA).

Symptomes Classifier Hypotheses Phenomenological Approach to Diagnosis Causality Analysis Causality Model Hypotheses Model-Based Approach to Diagnosis Symptomes Similarity Search Case Database Hypotheses

Oliver Niggemann, Volker Lohweg, V. Lohweg, 2014 .

Using behavior models for anomaly detection in hybrid systems

Hans Kleine Büning, Oliver Niggemann, Alexander Maier, 2011, 2011 XXIII International Symposium on Information, Communication and Automation Technologies.

Anomaly Detection in Production Plants using Timed Automata - Automated Learning of Models from Observations

Oliver Niggemann, Alexander Maier, Michael Jäger, 2011, ICINCO.

Sinc noise for the Kardar-Parisi-Zhang equation.

H. Hinrichsen, O. Niggemann, 2018, Physical review. E.

Field-Theoretic Thermodynamic Uncertainty Relation

U. Seifert, O. Niggemann, 2019, Journal of Statistical Physics.

Managing Complexity: Towards Intelligent Error-Handling Assistance Trough Interactive Alarm Flood Reduction

Oliver Niggemann, Sebastian Büttner, Carsten Röcker, 2017, CD-MAKE.

AutomationML: From data exchange to system planning and simulation

S. Faltinski, O. Niggemann, N. Moriz, 2012, 2012 IEEE International Conference on Industrial Technology.

Data-Driven Assistance Functions for Industrial Automation Systems

Oliver Niggemann, Stefan Windmann, O. Niggemann, 2015 .

Speeding Up Model-based Diagnosis by a Heuristic Approach to Solving SAT

Benno Stein, Oliver Niggemann, Theodor Lettmann, 2006, Artificial Intelligence and Applications.

Data Driven Condition Monitoring of Wind Power Plants Using Cluster Analysis

Peng Li, Oliver Niggemann, Jens Eickmeyer, 2015, 2015 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery.

System modeling based on machine learning for anomaly detection and predictive maintenance in industrial plants

Oliver Niggemann, Bjorn Kroll, Sebastian Schriegel, 2014, Proceedings of the 2014 IEEE Emerging Technology and Factory Automation (ETFA).

Data Driven Modeling for System-Level Condition Monitoring on Wind Power Plants

Peng Li, Oliver Niggemann, Florian Pethig, 2015, DX.

On the Nature of Structure and Its Identification

Benno Stein, Oliver Niggemann, Benno Stein, 1999, WG.

Supporting Intrusion Detection by Graph Clustering and Graph Drawing

Oliver Niggemann, Jens Tölle, O. Niggemann, 2000 .

Information Retrieval in Industrial Production Environments

Oliver Niggemann, Stefan Windmann, O. Niggemann, 2018, 2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA).

Self-Organizing Maps for Anomaly Localization and Predictive Maintenance in Cyber-Physical Production Systems

Oliver Niggemann, Alexander von Birgelen, Davide Buratti, 2018 .

Discretization of hybrid CPPS data into timed automaton using restricted Boltzmann machines

Oliver Niggemann, Nemanja Hranisavljevic, Alexander Maier, 2020, Eng. Appl. Artif. Intell..

Data-Driven Monitoring of Cyber-Physical Systems Leveraging on Big Data and the Internet-of-Things for Diagnosis and Control

Oliver Niggemann, Gautam Biswas, John S. Kinnebrew, 2015, DX.

A Cross-Frequency Protective Emblem: Protective Options for Medical Units and Wounded Soldiers in the Context of (fully) Autonomous Warfare

Jonas J. Schöttler, K. Isleif, O. Niggemann, 2023, ArXiv.

Incorporating Uncertainty into Unsupervised Machine Learning for Cyber-Physical Systems

Oliver Niggemann, Benedikt Eiteneuer, Carlo Voß, 2020, 2020 IEEE Conference on Industrial Cyberphysical Systems (ICPS).

Robustness and Generalization Performance of Deep Learning Models on Cyber-Physical Systems: A Comparative Study

Henrik S. Steude, O. Niggemann, Alexander Windmann, 2023, ArXiv.

Data-driven Identification of Causal Dependencies in Cyber-Physical Production Systems

Oliver Niggemann, Alexander Maier, Tino Hutschenreuther, 2019, ICAART.

A Bayesian predictive assistance system for resource optimization — A case study in industrial cleaning process

Oliver Niggemann, Ganesh Man Shrestha, O. Niggemann, 2014, Proceedings of the 2014 IEEE Emerging Technology and Factory Automation (ETFA).

Generating Artificial Sensor Data for the Comparison of Unsupervised Machine Learning Methods

Oliver Niggemann, Erik Pfannstiel, Bernd Zimmering, 2021, Sensors.

A Novel Anomaly Detection Algorithm for Hybrid Production Systems based on Deep Learning and Timed Automata

O. Niggemann, Nemanja Hranisavljevic, A. Maier, 2020, ArXiv.

On the Identification of Decision Boundaries for Anomaly Detection in CPPS

Oliver Niggemann, Barbara Hammer, Peng Li, 2019, 2019 IEEE International Conference on Industrial Technology (ICIT).

Generation of Adversarial Examples to Prevent Misclassification of Deep Neural Network based Condition Monitoring Systems for Cyber-Physical Production Systems

Oliver Niggemann, Barbara Hammer, Jens Otto, 2018, 2018 IEEE 16th International Conference on Industrial Informatics (INDIN).

Data-driven anomaly detection in cyber-physical production systems

Oliver Niggemann, Christian W. Frey, C. Frey, 2015, Autom..

On the Learning of Timing Behavior for Anomaly Detection in Cyber-Physical Production Systems

Oliver Niggemann, Alexander Maier, Jens Eickmeyer, 2015, DX.

Semantic interoperability for asset communication within smart factories

Oliver Niggemann, Heiko Koziolek, Thomas Usländer, 2017, 2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA).

On the applicability of model based software development to cyber physical production systems

Oliver Niggemann, Bjorn Kroll, O. Niggemann, 2014, Proceedings of the 2014 IEEE Emerging Technology and Factory Automation (ETFA).

A generic synchronized data acquisition solution for distributed automation systems

Oliver Niggemann, Bjorn Kroll, Alexander Maier, 2012, Proceedings of 2012 IEEE 17th International Conference on Emerging Technologies & Factory Automation (ETFA 2012).

AutomationML as a Shared Model for Offline- and Realtime-Simulation of Production Plants and for Anomaly Detection

Oliver Niggemann, Barath Kumar, Alexander Maier, 2013 .

AutomationML as a Basis for Offline - And Realtime-simulation - Planning, Simulation and Diagnosis of Automation Systems

Oliver Niggemann, Barath Kumar, Alexander Maier, 2011, ICINCO.

FliPSi: Generating Data for the Training of Machine Learning Algorithms for CPPS

O. Niggemann, Niklas Widulle, Anna Nordhausen, 2022, Annual Conference of the PHM Society.

Improving clustering based anomaly detection with concave hull: An application in fault diagnosis of wind turbines

Peng Li, Oliver Niggemann, O. Niggemann, 2016, 2016 IEEE 14th International Conference on Industrial Informatics (INDIN).

Big Data and Machine Learning for the Smart Factory—Solutions for Condition Monitoring, Diagnosis and Optimization

Oliver Niggemann, Alexander Maier, Sebastian Schriegel, 2017 .

Machine Learning for Cyber Physical Systems, Selected papers from the International Conference ML4CPS 2015, Lemgo, Germany, October 1-2, 2015

Oliver Niggemann, Jürgen Beyerer, Christian Kühnert, 2016, ML4CPS.

Plan-Based Derivation of General Functional Structures in Product Design

O. Niggemann, F. Mantwill, Philipp Rosenthal, 2023, arXiv.org.

A meta heuristic for graph drawing: learning the optimal graph-drawing method for clustered graphs

Benno Stein, Oliver Niggemann, Benno Stein, 2000, AVI '00.

Models for model's sake

Oliver Niggemann, Joachim Stroop, O. Niggemann, 2008, 2008 ACM/IEEE 30th International Conference on Software Engineering.

Behavior Modeling Tools in an Architecture-Driven Development Process - From Function Models to AUTOSAR

Oliver Niggemann, Ulrich Eisemann, Michael Beine, 2007 .

Using Models for Dynamic System Diagnosis: A Case Study in Automotive Engineering.

Benno Stein, Thomas Spanuth, O. Niggemann, 2009 .

Dagstuhl-Workshop MBEES: Modellbasierte Entwicklung eingebetteter Systeme VIII, Schloss Dagstuhl, Germany, 2012, Tagungsband Modellbasierte Entwicklung eingebetteter Systeme

Benno Stein, O. Niggemann, A. Maier, 2012, MBEES.

Statistical Models of Network Traffic

Oliver Niggemann, Barath Kumar, Juergen Jasperneite, 2010 .

L EARNING P HYSICAL C ONCEPTS IN CPS: A C ASE S TUDY WITH A T HREE -T ANK S YSTEM pdf

Oliver Niggemann, Henrik S. Steude, Alexander Windmann, 2022 .

Automated process planning for cyber-physical production systems

Oliver Niggemann, Antje Rogalla, O. Niggemann, 2017, 2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA).

Using Learned Models for the Root Cause Analysis of Cyber-Physical Production Systems

Benno Stein, Oliver Niggemann, Andreas Bunte, 2014 .

On the Diagnosis of Cyber-Physical Production Systems

V. Lohweg, O. Niggemann, 2015, AAAI.

Machine Learning for Cyber Physical Systems

O. Niggemann, Jürgen Beyerer, Christian Kühnert, 2021, Technologien für die intelligente Automation.

Towards Industrie 4.0 compliant configuration of condition monitoring services

Oliver Niggemann, Armin Walter, Florian Pethig, 2017, 2017 IEEE 15th International Conference on Industrial Informatics (INDIN).

A Generic DigitalTwin Model for Artificial Intelligence Applications

Oliver Niggemann, Christian Kühnert, Alexander Diedrich, 2021, 2021 4th IEEE International Conference on Industrial Cyber-Physical Systems (ICPS).

The DigitalTwin from an Artificial Intelligence Perspective pdf

Oliver Niggemann, Alexander Diedrich, Christian Kuehnert, 2020, ArXiv.

A software architecture for the analysis of energy- and process-data

Oliver Niggemann, Bjorn Kroll, Stefan Schramm, 2013, 2013 IEEE 18th Conference on Emerging Technologies & Factory Automation (ETFA).

Gradient-based Reconfiguration of Cyber-Physical Production Systems

Oliver Niggemann, Kaja Balzereit, O. Niggemann, 2021, 2021 4th IEEE International Conference on Industrial Cyber-Physical Systems (ICPS).

Expressing uncertainty in neural networks for production systems

Oliver Niggemann, Bernd Zimmering, Samim Ahmad Multaheb, 2021, Autom..