B1 - Self-learning Engineering Assistance System (funding period 2)
Simultaneous development of a self-learning engineering assistance system
Project Status: finished
Last Update: 23.01.2017
Members
The objective of this subproject B1 is the development of the self-learning engineering assistance system referred to as SLASSY that supports the design engineer during the design process of sheet-bulk metal formed parts. The synthesis step is supported by offering feature elements both for the primary design elements (PDE) and the secondary form elements (SDE) to the designer. It furthermore enables him to analyze a part, consisting of a primary form element (e.g. cup, plate, ring) and at least one secondary form element (tooth, strap, rib), that is to be manufactured with a sheet-bulk metal forming process. The knowledge needed for this analysis is acquired through a process of knowledge discovery in data bases whereas the data is derived from SBMF simulations or experiments with input-parameter variation studies. The explicit form of the design-relevant knowledge is represented by metamodels, a result of the KDD process. The overall architecture of SLASSY is suitable to support the described aspects including the management of the simulation data and the design-relevant knowledge derived from this data. It is depictured in the following figure.

The objective of this subproject B1 is the development of the self-learning engineering assistance system referred to as SLASSY that supports the design engineer during the design process of sheet-bulk metal formed parts. The synthesis step is supported by offering feature elements both for the primary design elements (PDE) and the secondary form elements (SDE) to the designer. It furthermore enables him to analyze a part, consisting of a primary form element (e.g. cup, plate, ring) and at least one secondary form element (tooth, strap, rib), that is to be manufactured with a sheet-bulk metal forming process. The knowledge needed for this analysis is acquired through a process of knowledge discovery in data bases whereas the data is derived from SBMF simulations or experiments with input-parameter variation studies. The explicit form of the design-relevant knowledge is represented by metamodels, a result of the KDD process. The overall architecture of SLASSY is suitable to support the described aspects including the management of the simulation data and the design-relevant knowledge derived from this data. It is depictured in the following figure.
Working Groups
Publications
2016
- Breitsprecher, T.; Küstner, C.; Wartzack, S.: Development of a self-learning assistance system for the use within sheet-bulk metal forming. In: Knowledge-Based Systems, (2016), Elsevier, submitted
- Küstner, C.; Beyer, F.; Kumor, D.; Loderer, A.; Wartzack, S.; Willner, K.; Blum, H.; Rademacher, A.; Hausotte, T.: Simulation-based development of Pareto-optimized tailored blanks for the use within sheet-bulk metal forming. In: Marjanovic, D.; Storga, M.; Pavkovic, N.; Bojcetic, N.; Skec, S. (Edt.): DS 84: Proceedings of the DESIGN 2016 14th International Design Conference, (2016), Design Society, pp. 291-300
- Küstner, C.; Mitsch, J.; Hegwein, M.; Meintker, N.; Mönks, K.; Fröhlich, M.; Wartzack, S.: Zustandsdiagnose von Maschinen im Kontext von Industrie 4.0 unter Einsatz von Data-Mining Methoden. In: Krause, D.; Paetzold, K.; Wartzack, S. (Edt.): Design for X - Beiträge zum 27. DFX-Symposium 2016, (2016), Hamburg: TuTech, pp. 169-180
2015
- Breitsprecher, T.; Sauer, C.; Sperber, C.; Wartzack, S.: Design-for-manufacture of sheet-bulk metal formed parts. In: Weber, C.; et al. (Edt.): DS80-4 Proceedings of the 20th International Conference on Engineering Design (ICED15), (2015), Mailand: Design Society, pp. 183-192
- Breitsprecher, T.; Kestel, P.; Küstner, C.; Sprügel, T.; Wartzack, S.: Einsatz von Data-Mining in modernen Produktentstehungsprozessen. In: ZWF - Zeitschrift für wirtschaftlichen Fabrikbetrieb, 110(2015)11, München: Carl Hanser, pp. 744-750
2014
- Ashhab, M.S.; Breitsprecher, T.; Wartzack, S.: Neural network based modeling and optimization of deep drawing – extrusion combined process . In: Journal of Intelligent Manufacturing, 25(2014)1, Springer, pp. 77-84
- Breitsprecher, T.; Kestel, P.; Dingfelder, C.; Wartzack, S.: Gaussian process based approach for automatic knowledge acquisition. In: Marjanovic, D. (Edt.): DS 77: Proceedings of the DESIGN 2014 13th International Design Conference, (2014), Dubrovnik: Design Society, pp. 1733-1740
- Breitsprecher, T.; Meinel, A.; Thummet, M.; Wartzack, S.: Produkt- und Prozessdatenmodellierung im Kontext der Blechmassivumformung. In: Stelzer, R. (Edt.): Entwerfen Entwickeln Erleben 2014 (EEE2014). Beiträge zur virtuellen Produktentwicklung und Konstruktionstechnik, (2014), Dresden: TUDpress Verlag der Wissenschaften, pp. 551-564
- Breitsprecher, T.; Wartzack, S.: Der Einsatz von Gaußprozessen zur Beschleunigung der automatischen Wissensakquisition. In: Krause, D.; Paetzold, K.; Wartzack, S. (Edt.): Design for X - Beiträge zum 25. DFX-Symposium 2014, (2014), Hamburg: TuTech Verlag, pp. 227-236
- Breitsprecher, T.; Dingfelder, C.; Wartzack, S.: Ein Ansatz zur adaptiven Simulationsdatenerhebung. In: Brökel, K.; Feldhusen, J.; Grote, K.-H.; Rieg, F.; Stelzer, R. (Edt.): 12. Gemeinsames Kolloquium Konstruktionstechnik, (2014), Bayreuth, pp. 461-470
2013
- Breitsprecher, T.; Wartzack, S.: A classification system for secondary design features for the use within sheet-bulk metal forming. In: Lindemann, U.; Srinivasan, V.; Kim, Y.S.; et al. (Edt.): DS 75-5: Proceedings of the 19th International Conference on Engineering Design (ICED13), (2013), Seoul: Design Society, pp. 039–048
- Breitsprecher, T.; Hense, R.; Beyer, F.; Biermann, D.; Wartzack, S.; Willner, K.: Sensitivitätsanalyse der tribologischen Eigenschaften gefräster Oberflächenstrukturen bei der Blechmassivumformung. In: Merklein, M.; Behrens, B. A., Tekkaya, A. E. (Edt.): 2. Workshop Blechmassivumformung, (2013), Bamberg: Meisenbach, pp. 121-136
Presentations
2016
- 18.05.2016: Küstner, C.: Simulation-based development of Pareto-optimized tailored blanks for the use within sheet-bulk metal forming, Cavtat
- 06.10.2016: Küstner, C.: Zustandsdiagnose von Maschinen im Kontext von Industrie 4.0 unter Einsatz von Data-Mining Methoden, Jesteburg
2015
- 29.07.2015: Breitsprecher, T.: Design-for-manufacture of sheet-bulk metal formed parts, ICED15, Mailand
2014
- 21.05.2014: Kestel, P.: Gaussian process based approach for automatic knowledge acquisition, DESIGN2014, Dubrovnik
- 17.10.2014: Breitsprecher, T.: Ein Ansatz zur adaptiven Simulationsdatenerhebung, KT2014, Bayreuth
2013
- 19.08.2013: Breitsprecher, T.: A classification system for secondary design features for the use within sheet-bulk metal forming, ICED13, Seoul
- 13.11.2013: Breitsprecher, T.: Vortrag bearbeiten: Sensitivitätsanalyse der tribologischen Eigenschaften gefräster Oberflächenstrukturen bei der Blechmassivumformung, Erlangen