Methodology for holistic process chain analysis and modeling using the example of bipolar plate production

• Applicants: Dr.-Ing. Verena Psyk; Professor Dr.-Ing. Frank Walther
• Subject Area: Primary Shaping and Reshaping Technology, Additive Manufacturing ; Mechanical Properties of Metallic Materials and their Microstructural Origins
• Term: since 2025
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 558559056

To advance the development of the hydrogen economy and establish hydrogen as a secondary energy carrier within the setting of the energy transition, the production of high-performance fuel cells is of central importance. The quality of these fuel cells is crucially determined by the properties of the bipolar plates (BPP) used, which are combined in large numbers into a stack and perform essential functions such as media flow and cooling. Therefore, to make fuel cell technology accessible to the mass market, cost-effective and high-volume production of defect-free BPPs is essential. Currently, in the production process chain for BPPs, individual process steps are analyzed, modeled, and optimized in isolation. This results in a purely sequential design of the process chain, where interactions between manufacturing processes and uncertainties along the process chain are not sufficiently considered. As a result, it is largely unclear how deviations in individual process stages affect the final quality of the BPPs and to what extent deviations, such as those of a geometric nature, can be tolerated. This lack of linkage between individual process stages leads to uncertainties in determining tolerances and process parameters, which negatively impacts costs and resource efficiency. An inverse process chain analysis of BPP manufacturing can unlock previously untapped innovation potential. The project aims to create an overall model of the process chain by coupling individual models, providing a basis for conducting an inverse analysis of the process chain. This allows for multi-criteria optimization of the BPP manufacturing process, considering stochastic uncertainties from the process, modeling, and measurement techniques. To achieve this goal, the project involves interdisciplinary collaboration in the fields of production technology, measurement engineering, materials science, and modeling. To verify key quality-relevant criteria of the BPPs, such as gas tightness, dimensional errors in the channel cross-sectional geometry, and form errors, both offline and inline-capable, non-destructive measurement systems will be employed to monitor the semi-finished products along the process chain. The combination of numerous measurement systems enables a comprehensive mapping of the process chain. The impact of key process parameters on the quality-relevant criteria will be investigated in sensitivity studies and validated with experimentally generated data. The resulting data will be used to validate both the individual process models and the overall process chain. The goal is to achieve a highly compact virtual process chain that enables efficient modeling and optimization.

• DFG Programme: Priority Programmes
• Subproject of: SPP 2476: Cross-process modelling in production engineering