Modeling of uncertainties in the process chain from the raw material to crimp connector for reverse material and process optimization

• Applicant: Professor Dr.-Ing. Thomas Bergs
• Subject Area: Metal-Cutting and Abrasive Manufacturing Engineering ; Primary Shaping and Reshaping Technology, Additive Manufacturing
• Term: since 2025
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 558602624

The research project aims to improve the performance of crimp connectors of electrical circular connectors made of copper-zinc alloys. The basis for this is the hypothesis that an increase in performance is possible through multi-criteria optimization of the entire process chain, taking into account uncertainties inherent in the material and process. The performance of the crimp connectors is defined by three central criteria: geometric parameters, the mechanical connectors strength and the electrical contact resistance. The aim of the project is to develop a new type of simulation methodology across processes along the entire process chain that makes it possible for the first time to predict these key performance indicators backwards as a function of the relevant process and material parameters. This methodology takes into account uncertainties that arise both in the material and in the process steps. A consistent methodology across processes for reverse multi-criteria optimization will be developed, which is based on various target parameters and is intended to significantly increase process efficiency. In the first phase, research is focused on the development of a consistent simulation methodology across processes along the entire process chain. This should be able to formulate the target variables - i.e. the performance parameters of the crimp connectors - as a function of the various process and material parameters. Uncertainties that may occur in the material or during the production process are taken into account. In order to avoid discrepancies between different discretization methods, material and friction models and to speed up the simulation, a universal replacement model is being developed. This model serves as a bridge to harmonize inconsistent models and calculation methods. In addition, a process chain for the production of crimp connectors is being created that includes the use of soft sensors to record uncertainties. Soft sensors combine experimental data from laboratory tests with measurement data in order to record and model uncertainties in material and process parameters, thereby minimizing the experimental effort. In the second phase, the focus is on the multi-criteria optimization of the performance of the crimp connectors. This optimization is carried out by directly inverting the sub-process models, creating a reverse simulation methodology across processes. The method is applied to at least three central target parameters in order to optimize the crimp connectors. Furthermore, the transferability of the developed methodology to other materials and geometrically different crimp connectors will be demonstrated. This will allow the applicability of the methodology to be extended to other industrial applications.

• DFG Programme: Priority Programmes
• Subproject of: SPP 2476: Cross-process modelling in production engineering
• International Connection: Switzerland
• Partner Organisation: Schweizerischer Nationalfonds (SNF)
• Cooperation Partner: Professor Dr.-Ing. Markus Bambach