Partner presentation:
The Institute for Production Systems (IPS) was founded as a scientific institution of the Faculty of Mechanical Engineering at the Technical University of Dortmund and is headed by Prof. Dr.-Ing. Jochen Deuse and Dr.-Ing. Ralph Richter. Scientists from the disciplines of mechanical engineering, industrial engineering, logistics, computer science and mathematics work at the institute.
The institute’s work focuses on the research and design of technical and socio-technical work systems. The research areas Work System Design, Production System Dynamics, Digital Manufacturing and Smart Quality are derived from this. In addition, the IPS has comprehensive expertise in the areas of data analysis, data management and competence development. Data collection, networking and analysis are used for data-driven problem solving within the four research areas of the institute. Here, experience has already been gained in numerous industrial and research projects. The transfer of competence in industrial data analysis is an essential part of the teaching activities of the IPS. Experience in the development of competences of industrial employees has also been gained through industrial and research projects.
Role in the project:
The research goal of the Institute for Production Systems of the TU Dortmund within the project AKKORD is the conception of the Reference Construction Kit and the associated structure for networked information provision and dynamic collaboration through industrial data analysis. Partial goals of the IPS are the development of methods and tools for comprehensive, application-oriented data analysis in value creation networks as well as the development of implementation systems for the digital design of business processes through industrial data analysis. The creation of accompanying integration, training and consulting concepts as well as the development of competencies for data analysis is a further goal of the IPS.
Published work reports:
- First work report from the research area “Analysis Modules and Configuration” – Configuration of Analysis Modules
- Second Work Report from the research area “Analysis Modules and Configuration” – Integration and Visualization
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Presentation of the AKKORD research project at the automatica trade fair 2022 in Munich
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Third work report from the research area “Analysis modules for networked and integrated data”
Publications:
- J. Mazarov, P. Wolf, J. Schallow, F. Nöhring, J. Deuse, R. Richter (2019): Industrial Data Science in Wertschöpfungsnetzwerken. Konzept einer Service-Plattform zur Datenintegration und -analyse, Kompetenzentwicklung und Initiierung neuer Geschäftsmodelle. In: Zeitschrift für wirtschaftlichen Fabrikbetrieb 109 (2019) 12, S. 874-877.
- J. Mazarov, J. Schmitt, J. Deuse, R. Richter (2020): Visualisierung in Industrial-Data-Science-Projekten. Nutzen grafischer Darstellungen von Informationen und Daten in Industrial-Data-Science-Projekten. In: Industrie 4.0 Management 36 (2020) 12, S. 63-66.
- V. Nolte, T. Sindram, J. Mazarov, J. Deuse (2020): Industrial Data Science erfolgreich implementieren. Interviewstudie zu Erfolgsfaktoren und Hemmnissen. In: Zeitschrift für wirtschaftlichen Fabrikbetrieb 115 (2020) 10, S. 734-737.
- J. Deuse, N. West, M. Syberg (2021): The Evolution of Scientific Managemet. From Industrial Engineering to Industrial Data Science. In: International Conference on Industrial Engineering and Industrial Management (ICIEIM), S. 99-101.
- N. West, J. Gries, C. Brockmeier, J. Göbel, J. Deuse (2021): Towards integrated Data Analysis Quality: Criteria for the application of Industrial Data Science. In: International Conference on Information Reuse an Integration for Data Science (IEEE-IRI), S. 131-138.
- J. Deuse, N. West, M. Syberg (2022): Rediscovering Scientific Management. The Evolution from Industrial Engineering to Industrial Data Science. In: International Journal of Production Management and Engineering (IJPME), S. 1-12.
- C. Rese, N. West, M. Gebler, S. Krzoska, P. Schlunder, J. Deuse (2023): Pipeline for the Automatic Extraction of Procedural Knowledge from Assembly Instructions into Controlled Natural Language. In: Journal of Software 18 (2023) 1, S. 1-14.
- M. Syberg, N. West, J. Schwenken, R. Adams, J. Deuse (2023): Requirements for the Development of a Collaboration Platform for Competency-Based Collaboration in Industrial Data Science Projects. In: International Conference on Information Management and Management Science (IMMS 2022), S. 64-69.
- J. Schwenken, C. Klupak, M. Syberg, N. West, F. Walker, J. Deuse (2023): Development of a Transdisciplinary Role Concept for the Process Chain of Industrial Data Science. In: International Conference on Data Analytics & Management (ICDAM 2022), S. 81-88.
Contact person:
- Nikolai West: nikolai.west@ips.tu-dortmund.de
- Marius Syberg: marius.syberg@ips.tu-dortmund.de
- Jörn Schwenken: joern.schwenken@ips.tu-dortmund.de