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Investigations of gradient-dependent nitrided forging tools in hot bulk metal forming under cyclic thermomechanical loading

Subject Area Primary Shaping and Reshaping Technology, Additive Manufacturing
Term from 2018 to 2024
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 397768783
 
The nitriding of tools for forging applications is considered to be state of the art for forging applications and is being used in industrial applications. Due to the diffusion of nitrogen, there is a phase change in the areas near the surface which leads to an improvement in heat resistance, wear resistance, fatigue strength as well as corrosion resistance of the tools. Although a general improvement in tooling levels through nitriding is known, there is no modeling technique to perform accurate numerical wear calculations of nitrided forging tools.Within the framework of the project, such a modeling technique for the numerical wear calculation of nitrited forging tools is to be developed. In order to describe the change in hardness, test methods for the characterization of hardness development under cyclic-thermal and cyclic-thermomechanical stress are to be developed. In the forging process, the tools are exposed not only to thermal loading, but also to a complex mechanical stress collective. It is described in the literature that the mechanical load lowers the austenite starting temperature Ac1 of hot forging tool materials. Therefore, the time-temperature austenitization behavior based on time-austenitization (ZTA) diagrams with an overlaid mechanical load is to be investigated. The hardness, adjusted as a function of temperature and mechanical load, is determined experimentally by means of hardness measurements. Subsequently, the resulting hardness curves are implemented in a commercial FE program. Finally, the validation of the wear model is carried out on a backward cup extrusion process (NRFP process). The available result is thus a new modeling technique with which a realistic tool wear in the hot bulk metal forming can be predicted.
DFG Programme Research Grants
 
 

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