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B3  Data Mining on Sensor Data of Automated Processes


Deuse.jpg
Prof. Dr. Deuse, Jochen
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Prof. Dr. Morik, Katharina
wiederkehr.jpg
Prof. Dr.-Ing. Wiederkehr, Petra

Enhancing the control of industrial processes and the quality of products can be supported by learning from sensor data. Project B3 focuses on the investigation of how decentralised data mining can be used for real-time quality predictions and how it can be integrated into production processes.

The tasks of data analytics in production systems have been ordered according to their difficulty: (1) anomaly detection, (2) diagnostic analytics, (3) predictive analytics, and (4) prescriptive analytics. In the first phase, we succeeded in developing a new decentralised anomaly detection and invented learning from label proportions. In the second phase, we investigated diagnostic and predictive analytics. Diagnostic analytics aims at explaining not ok products by process data. Based on time series data from a hot rolling process for steel-bars production, features have been extracted and aggregated that help to distinguish between ok and not ok products. Modeling the overall preprocessing in the software RapidMiner took the toolbox to its extreme, becoming a high-level programming environment. The advantage is the reproducibility of RapidMiner processes and their understandable documentation. Predictive analytics in flexible production processes has contributed to adequate process control in real-time. For distributed data mining, the training of local models from counts (TLMC) for vertically partitioned data has been developed. The anomaly detection has been enhanced for distributed settings as they are given by the Internet of Things. In the third phase, prescriptive analytics will be the focus of the project; i.e., the learned model changes the process in real-time. An example is not only to recognise a deviation of sensor measurements from the normal, but also to adapt the process parameters accordingly.

Project management:

Prof. Dr. Deuse, Jochen
Prof. Dr. Morik, Katharina
Prof. Dr.-Ing. Wiederkehr, Petra

Alumni:

Blom, Hendrik
Dr. Bohnen, Fabian
Büscher, Jan
Dr. Erohin, Olga
Finkeldey, Felix
Dr. Konrad, Benedikt
Panusch, Thorben
Saadallah, Amal
M. Sc. Schmitt, Jacqueline
Dr.-Ing. Siebrecht, Tobias
Dr. Stolpe, Marco
Dr. Tavakol, Maryam
Wiegand, Mario
Dr. Ing. Zwinkau, Ronny

Software:

LLP

Publications:

Saadallah/etal/2022a Saadallah, Amal and Büscher, Jan and Abdulaaty, Omar and Panusch,Thorben and Deuse,Jochen and Morik, Katharina. Explainable Predictive Quality Inspection using Deep Learning in Electronics Manufacturing. In 55th CIRP conference on Manufacturing Systems, Elsevier, 2022. LaTeX Symbol


Saadallah/etal/2022c Saadallah, Amal and Abdulaaty, Omar and Büscher, Jan and Panusch,Thorben and Morik, Katharina and Deuse,Jochen. Early Quality Prediction using Deep Learning on Time Series Sensor Data. In 55th CIRP conference on Manufacturing Systems, Elsevier, 2022. LaTeX Symbol


Saadallah/etal/2022d Saadallah, Amal and Finkeldey, Felix and Buß, Jens and Morik, Katharina and Wiederkehr, Petra and Rhode, Wolfgang. Simulation and Sensor Data Fusion for Machine Learning Application. In Advanced Engineering Informatics, Vol. 52, pages 101600, 2022. LaTeX Symbol


Cao/etal/2021a Cao, Ba-Tung and Saadallah, Amal and Egorov, Alexey and Freitag, Steffen and Meschke, Günther and Morik, Katharina. Online Geological Anomaly Detection Using Machine Learning in Mechanized Tunneling. In In: Barla M., Di Donna A., Sterpi D. (eds) (editors), Challenges and Innovations in Geomechanics, Vol. vol 125., pages 323--330, Springer, 2021. LaTeX Symbol Green Arrow


Saadallah/etal/2021a Saadallah, Amal and Tavakol, Maryam and Katharina, Morik. An Actor-Critic Ensemble Aggregation Model for Time-Series Forecasting. In The 37th IEEE International Conference on Data Engineering (ICDE), 2021. LaTeX Symbol


Saadallah/Morik/2021a Saadallah, Amal and Katharina, Morik. Meta-Adversarial Training of Neural Networks for Binary Classification. In IJCNN International Joint Conference on Neural Networks, 2021. LaTeX Symbol


Wiederkehr/etal/2021a Wiederkehr, Petra and Finkeldey, Felix and Merhofe, Torben. Augmented semantic segmentation for the digitization of grinding tools based on deep learning. In CIRP Annals, Vol. 70, No. 1, pages 297--300, Elsevier, 2021. LaTeX Symbol


Finkeldey/etal/2020a Finkeldey, Felix and Saadallah, Amal and Wiederkehr, Petra and Morik, Katharina. Real-time prediction of process forces in milling operations using synchronized data fusion of simulation and sensor data. In Engineering Applications of Artificial Intelligence, Vol. 94, 2020. LaTeX Symbol


Finkeldey/etal/2020b Finkeldey, Felix and Wirtz, Andreas and Merhofe, Torben and Wiederkehr, Petra. Learning-Based Prediction of Pose-Dependent Dynamics. In Journal of Manufacturing and Materials Processing, Vol. 4, No. 3, 2020. LaTeX Symbol


Nanni/etal/2020a Nanni, Mirco and Gennady, Andrienko and Barabasi, Albert-Laszlo and Boldrini, Chiara and Bonchi, Francesco and Cattuto, Ciro and Chiaromonte, Francesca and Commande, Giovanni and Conti, Marco and Cote, Mark and Dignum, Frank and Dignum, Virginia and Domingo-Ferrer, Josep and Ferragina, Paolo and Giannotti, Fosca and Guidotti, Riccardo and Helbng, Dirk and Kaski, Kimmo and Kertesz, Janos and Lehmann, Sune and Lepri, Bruno and Lukowicz, Paul and Matwin, Stan and Megias, Jimenez, David Megias and Monreale, Anna and Morik, Katharina and Oliver, Nuria and Passarella, Andrea and Passerini, Andrea and Pedreschi, Dino and Pentland, Alex and Pianesi, Fabio and Pratesi, Francesca and Rinzivillo, Salvatore and Ruggieri, Salvatore and Siebes, Arno and Torra, Vicenc and Trasarti, Roberto and van der Hoven, Jeroen and Vespignani, Alessandro. Give more data, awareness and control to individual citizens, and they will help COVID-19 containment. In Transactions on Data Privacy, Vol. 13, pages 61--66, 2020. LaTeX Symbol


Saadallah/Morik/2020g Saadallah, Amal and Katharina, Morik. Active Sampling for Learning Interpretable Surrogate Machine Learning Models. In IEEE International Conference on Data Science and Advanced Analytics (DSAA), 2020. LaTeX Symbol


Schmitt/etal/2020a Schmitt, Jacqueline and Boenig, Jochen and Borggraefe, Thorbjoern and Beitinger, Gunter and Deuse, Jochen. Predictive model-based quality inspection in electronics manufacturing using Machine Learning and Edge Cloud Computing. In Advanced Engineering Informatics (ADVEI), 2020. LaTeX Symbol


Schulte/etal/2020a Schulte, Lukas and Schmitt, Jacqueline and Meierhofer, Florian and Deuse, Jochen. Optimizing Inspection Process Severity by Machine Learning Under Label Uncertainty. In Nunes, Isabel L. (editors), Advances in Human Factors and Systems Interaction, pages 3--9, Cham, Springer, 2020. LaTeX Symbol


Bunse/etal/2019a Bunse, Mirko and Saadallah, Amal and Morik, Katharina. Towards Active Simulation Data Mining. In Kottke, Daniel and Lemaire, Vincent and Calma, Adrian and Krempl, Georg and Holzinger, Andreas (editors), Proc. of the 3rd Int. Tutorial and Workshop on Interactive Adaptive Learning at ECML-PKDD 2019, Vol. 2444, pages 104--107, CEUR Workshop Proceedings, 2019. LaTeX Symbol Green Arrow


Deuse/etal/2019a Deuse, Jochen and Schmitt, Jacqueline and Bönig, Jochen and Beitinger, Gunter. Dynamische Röntgenprüfung in der Elektronikproduktion. Einsatz von Data-Mining-Verfahren zur Qualitätsprognose. In Zeitschrift für wirtschaftlichen Fabrikbetrieb (ZWF), Vol. 114, No. 5, pages 264-267, 2019. LaTeX Symbol


Deuse/Schmitt/2019a Deuse, Jochen and Schmitt, Jacqueline. Industrial Data Science - Nutzen Künstlicher Intelligenz für die Produktion. In KANBrief, Vol. 4, 2019. LaTeX Symbol Green Arrow


Saadallah/Piatkowski/2019a Saadallah, Amal and Piatkowski, Nico and Finkeldey, Felix and Wiederkehr, Petra and Morik, Katharina. Learning Ensembles in the Presence of Imbalanced Classes. In ICPRAM: 8th international conference on pattern recognition applications and methods - icpram 2019, 2019. LaTeX Symbol Green Arrow


Saadallah/Priebe/2019c Saadallah, Amal and Priebe, Florian and Katharina, Morik. A Drift-based Dynamic Ensemble Members Selection using Clustering for Time Series Forecasting. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases ECML PKDD 2019, Würzburg, Germany, 2019. LaTeX Symbol


Schmitt/Deuse/2019a Schmitt, Jacqueline and Deuse, Jochen. Modellbasierte Prüfprozesse. Einsatz von Data-Mining-Verfahren zur industriellen Qualitätssicherung. In Zeitschrift für wirtschaftlichen Fabrikbetrieb (ZWF), Vol. 114, No. 4, pages 191-193, 2019. LaTeX Symbol


Schmitt/etal/2019a Schmitt, Jacqueline and Hahn, Florian and Deuse, Jochen. Practical Framework for Advanced Quality-based Process Control in Interlinked Manufacturing Processes. In IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), pages 511-515, 2019. LaTeX Symbol


Mertens/etal/2018a Katharina Mertens and André Barthelmey and René Wöstmann and Jacqueline Schmitt and Christian Harms-Zumbrägel and Tanja Gosch and Jochen Deuse. Retrofit - Von der Brownfield-Anlage zum cyber-physischen System mit dem Ziel der OEE-Verbesserung. In Hubert Biedermann (editors), Predictive Maintenance, pages 173, TÜV Media, 2018. LaTeX Symbol


Saadallah/etal/2018a Saadallah, Amal and Finkeldey, Felix and Morik, Katharina and Wiederkehr, Petra. Stability prediction in milling processes using a simulation-based machine learning approach. In 51st CIRP conference on Manufacturing Systems, Elsevier, 2018. LaTeX Symbol


Schmitt/Deuse/2018a Schmitt, Jacqueline and Deuse, Jochen. Similarity-search and Prediction Based Process Parameter Adaptation for Quality Improvement in Interlinked Manufacturing Processes. In IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), pages 700-704, 2018. LaTeX Symbol


Schmitt/etal/2018a Schmitt, Jacqueline and Wiegand, Mario and Deuse, Jochen. Qualitätsbasierte Auftragszuordnung - Zuordnung von Zwischenprodukten zu Kundenaufträgen auf Basis von Qualitätsprognosen. In ZWF online, 2018. LaTeX Symbol


Schmitt/etal/2018b Schmitt, Jacqueline and Hahn, Florian and Deuse, Jochen. Mathematical modelling of the quality-based order assignment problem. No. 2, Institute of Production Systems, TU Dortmund University, 2018. PDF-Symbol LaTeX Symbol


Deuse/etal/2017a Deuse, J. and Schmitt, J. and Stolpe, M. and Wiegand, M. and Morik, K.. Qualitätsprognosen zur Engpassentlastung in der Injektorfertigung unter Einsatz von Data Mining. In Schriftenreihe der Wissenschaftlichen Gesellschaft für Arbeits- und Betriebsorganisation (WGAB) e.V., 2017. PDF-Symbol LaTeX Symbol


Krzoska/etal/2017a Krzoska, Sven and Eickelmann, Michel and Schmitt, Jacqueline and Deuse, Jochen. Data Mining zur Nacharbeitsdauerprognose - Prädiktive Nacharbeitssteuerung und Arbeitsprozessoptimierung für die Montage in der Automobilindustrie. In Werkstatttechnik online, No. 10, pages 773--778, 2017. LaTeX Symbol


Blom/Morik/2016a Blom, Hendrik and Morik, Katharina. Resource-Aware Steel Production Through Data Mining. In Berendt, Bettina and Bringmann, Björn and Fromont, Elisa and Garriga, Gemma and Miettinen, Pauli and Tatti, Nikolaj and Tresp, Volker (editors), Machine Learning and Knowledge Discovery in Databases, pages 263--266, Springer, 2016. LaTeX Symbol Green Arrow


Stolpe/2016a Marco Stolpe. The Internet of Things: Opportunities and Challenges for Distributed Data Analysis. In SIGKDD Explorations, Vol. 18, No. 1, pages 15-34, 2016. LaTeX Symbol


Stolpe/etal/2016a Stolpe, Marco and Blom, Hendrik and Morik, Katharina. Sustainable Industrial Processes by Embedded Real-Time Quality Prediction. In Kersting, Kristian and Lässig, Jörg and Morik, Katharina (editors), Computational Sustainability, pages 201--243, Springer, 2016. LaTeX Symbol Green Arrow


Stolpe/etal/2016b Marco Stolpe and Kanishka Bhaduri and Kamalika Das. Distributed Support Vector Machines: An Overview. In Michaelis, S. and Piatkowski, N. and Stolpe, M. (editors), Solving Large Scale Learning Tasks: Challenges and Algorithms, Vol. 9580, pages 109--138, Springer, 2016. LaTeX Symbol


Wiegand/etal/2016a Wiegand, Mario and Stolpe, Marco and Deuse, Jochen and Morik, Katharina. Prädiktive Prozessüberwachung auf Basis verteilt erfasster Sensordaten. In at-Automatisierungstechnik, Vol. 64, No. 7, pages 521--533, 2016. LaTeX Symbol


Eickelmann/etal/2015a Eickelmann, Michel and Wiegand, Mario and Konrad, Benedikt and Deuse, Jochen. Die Bedeutung von Data Mining im Kontext von Industrie 4.0. In Zeitschrift für wirtschaftlichen Fabrikbetrieb (ZWF), Vol. 110, No. 11, pages 738-743, 2015. LaTeX Symbol


Liebig/etal/2015a Liebig, Thomas and Stolpe, Marco and Morik, Katharina. Distributed Traffic Flow Prediction with Label Proportions: From in-Network towards High Performance Computation with MPI. In Proceedings of the 2nd International Workshop on Mining Urban Data (MUD2), Vol. 1392, pages 36--43, CEUR-WS, 2015. PDF-Symbol LaTeX Symbol Green Arrow


Stolpe/etal/2015a Marco Stolpe and Thomas Liebig and Katharina Morik. Communication-efficient learning of traffic flow in a network of wireless presence sensors. In Proceedings of the Workshop on Parallel and Distributed Computing for Knowledge Discovery in Data Bases (PDCKDD 2015), pages (to appear), CEUR-WS, 2015. LaTeX Symbol


Deuse/etal/2014a Deuse, Jochen and Wiegand, Mario and Erohin, Olga and Lieber, Daniel and Klinkenberg, Ralf. Big Data Analytics in Produktion und Instandhaltung. In Biedermann, Hubert (editors), Instandhaltung im Wandel. Herausforderungen und Lösungen im Zeitalter von Industrie 4.0, pages 33-48, 2014. LaTeX Symbol


Deuse/etal/2014b Deuse, Jochen and Erohin, Olga and Lieber, Daniel. Wissensentdeckung in vernetzten, industriellen Datenbeständen. In Lödding, Hermann (editors), Industrie 4.0. Wie intelligente Vernetzung und kognitive Systeme unsere Arbeit verändern, pages 373-395, Gito, 2014. LaTeX Symbol Green Arrow


Bhaduri/Stolpe/2013a Bhaduri, Kanishka and Stolpe, Marco. Distributed Data Mining in Sensor Networks. In Aggarwal, Charu C. (editors), Managing and Mining Sensor Data, Berlin, Heidelberg, Springer, 2013. LaTeX Symbol Green Arrow


Bohnen/etal/2013a Bohnen, Fabian and Stolpe, Marco and Deuse, Jochen and Morik, Katharina. Using a Clustering Approach with Evolutionary Optimized Attribute Weights to Form Product Families for Production Leveling. In Windt, Katja (editors), Robust Manufacturing Control, pages 189--202, Berlin, Heidelberg, Springer, 2013. LaTeX Symbol Green Arrow


Bohnen/etal/2013b Bohnen, Fabian and Buhl, Matthias and Deuse, Jochen. Systematic Procedure for leveling of low volume and high mix production. In CIRP Journal od Manufacturing Science and Technology, Vol. 6, No. 1, pages 53-58, 2013. LaTeX Symbol


Deuse/etal/2013a Deuse, Jochen and Konrad, Benedikt and Bohnen, Fabian. Renaissance of Group Technology: Reducing Variability to Match Lean Production Prerequisites. In Bakhtadze, Natalia and Chernyshov, Kirill and Dolgui, Alexandre and Lototsky, Vladimir (editors), Manufacturing Modelling, Management, and Control, Vol. 7, pages 998-1003, 2013. LaTeX Symbol


Konrad/etal/2013a Konrad, Benedikt and Lieber, Daniel and Deuse, Jochen. Striving for Zero Defect Production: Intelligent Manufacturing Control through Data Mining in Continuous Rolling Mill Processes. In Windt, Katja (editors), Robust Manufacturing Control, pages 215--229, CIRP, Berlin, Heidelberg, Springer, 2013. LaTeX Symbol Green Arrow


Lieber/etal/2013a Lieber, Daniel and Stolpe, Marco and Konrad, Benedikt and Deuse, Jochen and Morik, Katharina. Quality Prediction in Interlinked Manufacturing Processes based on Supervised & Unsupervised Machine Learning. In Procedia CIRP - 46th CIRP Conf. on Manufacturing Systems, Vol. 7, pages 193-198, Elsevier, 2013. LaTeX Symbol Green Arrow


Lieber/etal/2013b Lieber, Daniel and Erohin, Olga and Deuse, Jochen. Wissensentdeckung im industriellen Kontext - Herausforderungen und Anwendungsbeispiele. In Zeitschrift für wirtschaftlichen Fabrikbetrieb (ZWF), Vol. 108, No. 6, pages 388-393, 2013. LaTeX Symbol


Stolpe/etal/2013a Stolpe, M. and Bhaduri, K. and Das, K. and Morik, K.. Anomaly Detection in Vertically Partitioned Data by Distributed Core Vector Machines. In Blockeel, Hendrik and Kersting, Kristian and Nijssen, Siegfried and \vZelezný, Filip (editors), Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Part III, pages 321--336, Springer, 2013. LaTeX Symbol


Lee/etal/2012a Lee, S. and Stolpe, M. and Morik, K.. Separable Approximate Optimization of Support Vector Machines for Distributed Sensing. In Flach, Peter A. and De Bie, Tijland and Cristianini, Nello (editors), Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2012, Bristol, UK, September 24-28, 2012. Proceedings, Part II, Vol. 7524, pages 387--402, Springer, 2012. LaTeX Symbol


Lieber/etal/2012a Lieber, Daniel and Konrad, Benedikt and Deuse, Jochen and Stolpe, Marco and Morik, Katharina. Sustainable Interlinked Manufacturing Processes through Real-Time Quality Prediction. In Dornfeld, David A. and Linke, Barbara S. (editors), Leveraging Technology for a Sustainable World, pages 393-398, CIRP, Berlin, Heidelberg, Springer, 2012. LaTeX Symbol Green Arrow


Maschek/etal/2011a Maschek,Thomas and Konrad, Benedikt and Deuse, Jochen and Hermanns, Gerhard and Weber, Daniel and Schreckenberg, Michael. Verkehrsforschung in der Produktionsflussanalyse - Übertragung von Modellen der statistischen Physik auf die Analyse von Produktionssystemen. In ZWF - Zeitung für wirtschaftlichen Fabrikbetrieb, Vol. 106, No. 11, pages 833--837, 2011. LaTeX Symbol


Stolpe/etal/2011a Stolpe, Marco and Morik, Katharina and Konrad, Benedikt and Lieber, Daniel and Deuse, Jochen. Challenges for Data Mining on Sensor Data of Interlinked Processes. In Proceedings of the Next Generation Data Mining Summit (NGDM) 2011, 2011. PDF-Symbol LaTeX Symbol Green Arrow


Stolpe/Morik/2011a Stolpe, M. and Morik, K.. Learning from Label Proportions by Optimizing Cluster Model Selection. In Gunopulos, Dimitrios and Hofmann, Thomas and Malerba, Donato and Vazirgiannis, Michalis (editors), Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2011, Athens, Greece, September 5-9, 2011, Proceedings, Part III, pages 349--364, Springer, 2011. PDF-Symbol LaTeX Symbol


  • Saadallah/etal/2022a - Explainable Predictive Quality Inspection using Deep Learning in Electronics Manufacturing
  • Saadallah/etal/2022c - Early Quality Prediction using Deep Learning on Time Series Sensor Data
  • Saadallah/etal/2022d - Simulation and Sensor Data Fusion for Machine Learning Application
  • Cao/etal/2021a - Online Geological Anomaly Detection Using Machine Learning in Mechanized Tunneling
  • Saadallah/etal/2021a - An Actor-Critic Ensemble Aggregation Model for Time-Series Forecasting
  • Saadallah/Morik/2021a - Meta-Adversarial Training of Neural Networks for Binary Classification
  • Wiederkehr/etal/2021a - Augmented semantic segmentation for the digitization of grinding tools based on deep learning
  • Finkeldey/etal/2020a - Real-time prediction of process forces in milling operations using synchronized data fusion of simulation and sensor data
  • Finkeldey/etal/2020b - Learning-Based Prediction of Pose-Dependent Dynamics
  • Nanni/etal/2020a - Give more data, awareness and control to individual citizens, and they will help COVID-19 containment
  • Saadallah/Morik/2020g - Active Sampling for Learning Interpretable Surrogate Machine Learning Models
  • Schmitt/etal/2020a - Predictive model-based quality inspection in electronics manufacturing using Machine Learning and Edge Cloud Computing
  • Schulte/etal/2020a - Optimizing Inspection Process Severity by Machine Learning Under Label Uncertainty
  • Bunse/etal/2019a - Towards Active Simulation Data Mining
  • Deuse/etal/2019a - Dynamische Röntgenprüfung in der Elektronikproduktion. Einsatz von Data-Mining-Verfahren zur Qualitätsprognose
  • Deuse/Schmitt/2019a - Industrial Data Science - Nutzen Künstlicher Intelligenz für die Produktion
  • Saadallah/Piatkowski/2019a - Learning Ensembles in the Presence of Imbalanced Classes
  • Saadallah/Priebe/2019c - A Drift-based Dynamic Ensemble Members Selection using Clustering for Time Series Forecasting
  • Schmitt/Deuse/2019a - Modellbasierte Prüfprozesse. Einsatz von Data-Mining-Verfahren zur industriellen Qualitätssicherung
  • Schmitt/etal/2019a - Practical Framework for Advanced Quality-based Process Control in Interlinked Manufacturing Processes
  • Mertens/etal/2018a - Retrofit - Von der Brownfield-Anlage zum cyber-physischen System mit dem Ziel der OEE-Verbesserung
  • Saadallah/etal/2018a - Stability prediction in milling processes using a simulation-based machine learning approach
  • Schmitt/Deuse/2018a - Similarity-search and Prediction Based Process Parameter Adaptation for Quality Improvement in Interlinked Manufacturing Processes
  • Schmitt/etal/2018a - Qualitätsbasierte Auftragszuordnung - Zuordnung von Zwischenprodukten zu Kundenaufträgen auf Basis von Qualitätsprognosen
  • Schmitt/etal/2018b - Mathematical modelling of the quality-based order assignment problem
  • Deuse/etal/2017a - Qualitätsprognosen zur Engpassentlastung in der Injektorfertigung unter Einsatz von Data Mining
  • Krzoska/etal/2017a - Data Mining zur Nacharbeitsdauerprognose - Prädiktive Nacharbeitssteuerung und Arbeitsprozessoptimierung für die Montage in der Automobilindustrie
  • Blom/Morik/2016a - Resource-Aware Steel Production Through Data Mining
  • Stolpe/2016a - The Internet of Things: Opportunities and Challenges for Distributed Data Analysis
  • Stolpe/etal/2016a - Sustainable Industrial Processes by Embedded Real-Time Quality Prediction
  • Stolpe/etal/2016b - Distributed Support Vector Machines: An Overview
  • Wiegand/etal/2016a - Prädiktive Prozessüberwachung auf Basis verteilt erfasster Sensordaten
  • Eickelmann/etal/2015a - Die Bedeutung von Data Mining im Kontext von Industrie 4.0
  • Liebig/etal/2015a - Distributed Traffic Flow Prediction with Label Proportions: From in-Network towards High Performance Computation with MPI
  • Stolpe/etal/2015a - Communication-efficient learning of traffic flow in a network of wireless presence sensors
  • Deuse/etal/2014a - Big Data Analytics in Produktion und Instandhaltung
  • Deuse/etal/2014b - Wissensentdeckung in vernetzten, industriellen Datenbeständen
  • Bhaduri/Stolpe/2013a - Distributed Data Mining in Sensor Networks
  • Bohnen/etal/2013a - Using a Clustering Approach with Evolutionary Optimized Attribute Weights to Form Product Families for Production Leveling
  • Bohnen/etal/2013b - Systematic Procedure for leveling of low volume and high mix production
  • Deuse/etal/2013a - Renaissance of Group Technology: Reducing Variability to Match Lean Production Prerequisites
  • Konrad/etal/2013a - Striving for Zero Defect Production: Intelligent Manufacturing Control through Data Mining in Continuous Rolling Mill Processes
  • Lieber/etal/2013a - Quality Prediction in Interlinked Manufacturing Processes based on Supervised & Unsupervised Machine Learning
  • Lieber/etal/2013b - Wissensentdeckung im industriellen Kontext - Herausforderungen und Anwendungsbeispiele
  • Stolpe/etal/2013a - Anomaly Detection in Vertically Partitioned Data by Distributed Core Vector Machines
  • Lee/etal/2012a - Separable Approximate Optimization of Support Vector Machines for Distributed Sensing
  • Lieber/etal/2012a - Sustainable Interlinked Manufacturing Processes through Real-Time Quality Prediction
  • Maschek/etal/2011a - Verkehrsforschung in der Produktionsflussanalyse - Übertragung von Modellen der statistischen Physik auf die Analyse von Produktionssystemen
  • Stolpe/etal/2011a - Challenges for Data Mining on Sensor Data of Interlinked Processes
  • Stolpe/Morik/2011a - Learning from Label Proportions by Optimizing Cluster Model Selection

Disserations:

  • Lieber/2018a - Data Mining in der Qualitätslenkung am Beispiel der Stabstahlproduktion
  • Stolpe/2017a - Distributed Analysis of Vertically Partitioned Sensor Measurements under Communication Constraints
  • Erohin/2016a - Wissensgewinnung durch Datenanalyse zur prospektiven Zeitermittlung
  • Bohnen/2013a - Eine Methodik zur Produktionsnivellierung auf der Basis von Fertigungsfamilien

Final Theses:

  • Haritz/2017a - Parameterschätzung mit Gütegarantie durch Bandit Models für die Regelung im Industrie 4.0 Kontext
  • Honysz/2017a - Anomalie-Erkennung in Spritzgieß-Prozessdaten
  • Rickhoff/2016a - Zyklische Concept Drifts
  • Gaertner/2014a - Klassifikation von Zeitreihen über die Bestimmung häufger symbolisierter Subsequenzen
  • Roetner/2014a - Behandlung von Concept Drift in zyklischen Prozessen
  • Koscharnyj/2013a - Beitrag zur Optimierung von Qualitätssicherungsmethoden in der Stahlindustrie auf Basis einer Untersuchung und Bewertung gängiger Qualitätssicherungsstrategien in der Automobil- und Prozessindustrie
  • Matuschek/2013a - Symbolisierung und Clustering von Zeitreihen als neue Operatoren im ValueSeries Plugin von Rapidminer
  • Spain/2013a - A Survey on Subspace Clustering
  • Stumpf/2013a - Untersuchung der Eignung ausgewählter Mustererkennungsverfahren zur Identifizierung qualitätsrelevanter Einflussfaktoren in der Stahlindustrie
  • Blom/2011a - Entwicklung von Optimierungsverfahren für das Lösen verschiedener Lernaufgaben mit der Stützvektormethode

Preliminary Work:

Bohnen/Deuse/2010a Bohnen, F. and Deuse, J.. Leveling of Low Volume and High Mix Production based on a Group Technology Approach. In Proceedings of the 43rd CIRP International Conference on Manufacturing Systems, pages 949--956, 2010. PDF-Symbol LaTeX Symbol


Morik/etal/2010a Morik, Katharina and Stolpe, Marco and Deuse, Jochen and Bohnen, Fabian and Reichel, Ulrich. Prognosemodelle zur Ermittlung der Produkteigenschaften -- Einsatz von Data-Mining-Verfahren im Walzwerk. In stahl und eisen, No. 10, pages 80--82, 2010. LaTeX Symbol


Morik/etal/2010b Morik, Katharina and Deuse, Jochen and Faber, Vanessa and Bohnen, Fabian. Data Mining in Sensordaten verketteter Prozesse. In Zeitschrift für Wirtschaftlichen Fabrikbetrieb (ZWF), Vol. 105, No. 1-2, pages 106--110, Carl Hanser, 2010. LaTeX Symbol


Mierswa/2008a Mierswa, Ingo. Non-Convex and Multi-Objective Optimization in Data Mining. Fachbereich Informatik, Technische Universität Dortmund, 2008. PDF-Symbol LaTeX Symbol


Mierswa/etal/2008b Mierswa, Ingo and Morik, Katharina and Wurst, Michael. Collaborative Use of Features in a Distributed System for the Organization of Music Collections. In Shen and Shephard and Cui and Liu (editors), Intelligent Music Information Systems: Tools and Methodologies, pages 147--176, Igi Global Publishing, 2008. LaTeX Symbol


Birkmann/Deuse/2007a Birkmann, Stephan and Deuse, Jochen. Using a Group Technology Approach to Level a Low Volume and High Mix Production. In Proceedings of 12th Annual International Conference on Industrial Engineering - Theory, Applications and Practice, pages 265--270, Cancun, Mexico, 2007. PDF-Symbol LaTeX Symbol


Deuse/etal/2007a Deuse, Jochen and Stausberg, Jan Robert and Wischniewski, Sascha. Leitsätze zur Gestaltung einer verschwendungsarmen Produktion. In ZWF -- Zeitschrift für wirtschaftlichen Fabrikbetrieb, Vol. 102, No. 5, pages 291--294, 2007. PDF-Symbol LaTeX Symbol


Mierswa/Wurst/2006a Mierswa, Ingo and Wurst, Michael. Information Preserving Multi-Objective Feature Selection for Unsupervised Learning. In Maarten Keijzer and Mike Cattolico and Dirk Arnold and Vladan Babovic and Christian Blum and Peter Bosman and Martin V. Butz and Carlos Coello Coello and Dipankar Dasgupta and Sevan G. Ficici and James Foster and Arturo Hernandez-Aguirre and Greg Hornby and Hod Lipson and Phil McMinn and Jason Moore and Guenther Raidl and Franz Rothlauf and Conor Ryan and Dirk Thierens (editors), GECCO '06: Proceedings of the 8th annual conference on Genetic and evolutionary computation, pages 1545--1552, New York, NY, USA, ACM Press, 2006. LaTeX Symbol


Mierswa/Morik/2005a Mierswa, Ingo and Morik, Katharina. Automatic Feature Extraction for Classifying Audio Data. In Machine Learning Journal, Vol. 58, pages 127--149, 2005. PDF-Symbol PDF-Symbol LaTeX Symbol


Morik/Koepcke/2004a Morik, Katharina and Köpcke, Hanna. Analysing Customer Churn in Insurance Data - A Case Study. In Jean-Francois Boulicaut and Floriana Esposito and Fosca Giannotti and Dino Pedreschi (editors), PKDD '04: Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases, Vol. 3202, pages 325--336, New York, NY, USA, Springer, 2004. PDF-Symbol LaTeX Symbol


Morik/etal/99a Morik, Katharina and Brockhausen, Peter and Joachims, Thorsten. Combining statistical learning with a knowledge-based approach -- A case study in intensive care monitoring. In ICML '99: Proceedings of the Sixteenth International Conference on Machine Learning, pages 268--277, San Francisco, CA, USA, Morgan Kaufmann Publishers Inc., 1999. PDF-Symbol PDF-Symbol LaTeX Symbol


Eversheim/Deuse/98a Deuse, Jochen and Eversheim, W.. Teilefamilienbildung auf der Grundlage von Produktmodelldaten. In Krause, Frank-Lothar and Uhlmann, Eckhardt (editors), Innovative Produktionstechnik, pages 141--156, München, Wien, Carl Hanser Verlag, 1998. PDF-Symbol LaTeX Symbol


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