Project Overview
Principle Investigators: |
Prof. Dr.-Ing. habil. Verena Kräusel Prof. Dr. Agnes Koschmider |
Project Team: |
M.Sc. Jakub Korenek M.Sc. Dominic Langhammer |
Research Institutions: |
Fraunhofer Institute for Machine Tools and Forming Technology IWU Chemnitz Institute of Information Systems and Process Analytics, University of Bayreuth |
Semi-finished Material(s): |
S500MC |
Manufacturing Processes: |
Shear cutting (punching) and collar drawing |
Motivation
- Improvement of the process quality and robustness in the shearing-cutting-collar-drawing process by optimising the die surfaces to increase process reliability with regard to edge cracks that occur
- Integration of forming domain knowledge into a hybrid process model and the application of advanced analysis methods to create a well-founded decision-making basis for process optimisation
- Interdisciplinary collaboration between partners with different research competences for a holistic view of the process
- Creation of comprehensible correlations through Explainable Artificial Intelligence (XAI)
Aims
As part of the research project Data4Collar, which is part of the SPP 2422, the interdisciplinary interaction of forming technology and data science is being used to investigate the formation of edge cracks and the effective design of the die surface by means of a digital representation of the process chain of shear cutting and collar drawing.
Initially, a data-driven modelling of the shearing-cutting-collar drawing process is pursued. The integration of in-line sensor technology into a test tool capable of continuous operation enables comprehensive recording and analysis of process data. This forms the basis for the development of a data-based model, which is extended to a hybrid model through the integration of formalised domain knowledge in order to promote explainability and transparency in the sense of XAI. By synthesising the data-driven model with domain knowledge through the integration of white/grey box models and the development of a hybrid model, the aim is to enable the explanation of correlations between process data and product quality in addition to transparency and interpretability.
Working Program
Work Package |
Description |
WP1 |
Experimental and data analytical basics |
WP2 |
Design of the continuous shear-cutting-collar-drawing process for in-process data acquisition |
WP3 |
Analytical and numerical process analysis (domain knowledge) |
WP4 |
Development of a data generator for the systematic evaluation of developed processes |
WP5 |
Process data acquisition in continuous operation |
WP6 |
Process data-driven modelling |
WP7 |
Hybrid process model |
Expected Results
The aim of this project is to create transferable system knowledge which, taking into account the sensitivity to edge cracking, enables an effective design of the mould working surfaces in the process design and thus contributes to a robustification of shearing-collar drawing processes.
Contact
Prof. Dr. Agnes Koschmider
Fraunhofer Institute for Applied Information Technology FIT
Wittelsbacherring 10
95444 Bayreuth
E-mail: agnes.koschmider@uni-bayreuth.de
Website: https://www.wi.fit.fraunhofer.de
Prof. Dr.-Ing. habil. Verena Kräusel
Fraunhofer Institute for Machine Tools and Forming Technology IWU
Reichenhainer Street 88
09126 Chemnitz
E-mail: info@iwu.fraunhofer.de
Website: https://www.iwu.fraunhofer.de/de/forschung/leistungsangebot/kompetenzen-von-a-bis-z/umformen.html
M.Sc. Jakub Korenek
Sheet Metal Working Department
Fraunhofer Institute for Machine Tools and Forming Technology
Reichenhainer Straße 88
09126 Chemnitz
E-Mail: jakub.korenek@iwu.fraunhofer.de
Website: www.iwu.fraunhofer.de
M.Sc. Dominic Langhammer