Institute for production technology and systems
Organisational unit: Institute
- Junior professorship for Measurement and Sensor Technology in Production Engineering
- Professorship for Manufacturing – Innovative Manufacturing
- Professorship for materials mechanics
- Professorship for Materials Technology, in particular of Magnesium Materials
- Professorship for Modelling and Simulation of Technical Systems and Processes
- Professorship for Product Development and Design
- Professorship for Production Management
- Professorship of Control and Drive Systems
- Professorship of Production Management
Organisation profile
The members of the Institute for Production Technology and Systems (IPTS) carry out work on a wide range of engineering-related research questions.
When it comes to subjects, the members of the Institute concentrate on the topics of supply chain management and production management, as well as on measurement, control, plasma, production and material technology. Within these fields, we aim to answer current research questions through both experimental work and the use of digital modelling. Our overarching goal here is to provide better solution strategies for complex problems within the field of engineering.
Main research areas
The members of the department investigate this field from both a production management and a technical perspective.
Cooperations with companies and external research institutes play an important role in the IPTS work. We collaborate with our industry partners to create practically-oriented solutions to problems within industrial practice. This allows us to transfer our research findings directly into industrial companies, thus helping to improve our partners' competitiveness. A particular highlight of our work is the strong partnership which exists between the IPTS and the Helmholtz-Zentrum Geesthacht Centre for Materials and Coastal Research, which is formally expressed in the form of two shared professorships at the IPTS.
- Published
Microstructure, mechanical and functional properties of refill friction stir spot welds on multilayered aluminum foils for battery application
Gera, D., Fu, B., Suhuddin, U. F. H. R., Plaine, A., Alcantara, N., dos Santos, J. F. & Klusemann, B., 01.07.2021, In: Journal of Materials Research and Technology. 13, p. 2272-2286 15 p.Research output: Journal contributions › Journal articles › Research › peer-review
- Published
Towards a decision support system for radiotherapy business continuity in a pandemic crisis
Reuter-Oppermann, M., Müller-Polyzou, R. & Georgiadis, A., 03.04.2022, In: Journal of Decision Systems. 31, 1-2, p. 40-67 28 p.Research output: Journal contributions › Journal articles › Research › peer-review
- Published
Modeling precipitation kinetics for multi-phase and multi-component systems using particle size distributions via a moving grid technique
Herrnring, J., Sundman, B., Staron, P. & Klusemann, B., 15.08.2021, In: Acta Materialia. 215, 14 p., 117053.Research output: Journal contributions › Journal articles › Research › peer-review
- Published
Dynamically adjusting the k-values of the ATCS rule in a flexible flow shop scenario with reinforcement learning
Heger, J. & Voss, T., 2023, In: International Journal of Production Research. 61, 1, p. 147-161 15 p.Research output: Journal contributions › Journal articles › Research › peer-review
- Published
Gender and Diversity aspects in Engineering Education and their impact on the design of engineering curricula
Block, B.-M. & Guerne, M. G., 18.06.2021, Proceedings of the 2021 IEEE Global Engineering Education Conference, EDUCON 2021: Women in Engineering. Klinger, T., Kollmitzer, C. & Pester, A. (eds.). Piscataway: IEEE - Institute of Electrical and Electronics Engineers Inc., p. 738-744 7 p. 9454043. (IEEE Global Engineering Education Conference, EDUCON; vol. 2021-April).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
- Published
Outperformed by a Computer? - Comparing Human Decisions to Reinforcement Learning Agents, Assigning Lot Sizes in a Learning Factory: 11th Conference on Learning Factories, CLF2021
Voß, T., Rokoss, A., Maier, J. T., Schmidt, M. & Heger, J., 06.2021, Rochester: Elsevier Inc., 6 p. (SSRN).Research output: Working paper › Working papers
- Published
Compression behaviour of wire + arc additive manufactured structures
Abbaszadeh, M., Ventzke, V., Neto, L., Riekehr, S., Martina, F., Kashaev, N., Hönnige, J., Williams, S. & Klusemann, B., 01.06.2021, In: Metals. 11, 6, 18 p., 877.Research output: Journal contributions › Journal articles › Research › peer-review
- Published
Influence of Mg content in Al alloys on processing characteristics and dynamically recrystallized microstructure of friction surfacing deposits
Ehrich, J., Roos, A., Klusemann, B. & Hanke, S., 05.07.2021, In: Materials Science and Engineering A. 819, 141407.Research output: Journal contributions › Journal articles › Research › peer-review
- Published
A Comparative Study for Fisheye Image Classification: SVM or DNN
Chen, Z. & Georgiadis, A., 01.01.2021, Proceedings of the 12th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2020. Abraham, A., Ohsawa, Y., Gandhi, N., Jabbar, M. A., Haqiq, A., McLoone, S. & Issac, B. (eds.). Springer Science and Business Media Deutschland, p. 424-433 10 p. (Advances in Intelligent Systems and Computing; vol. 1383 AISC).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
- Published
Anwendungen des maschinellen Lernens in der Produktion aus Auftrags- und Produktsicht: Ein Überblick
Denkena, B., Dittrich, M.-A., Noske, H., Kramer, K. & Schmidt, M., 19.05.2021, In: ZWF Zeitschrift für wirtschaftlichen Fabrikbetrieb. 116, 5, p. 358-362 5 p.Research output: Journal contributions › Journal articles › Research