MSE 2022
Lecture
28.09.2022
Modelling of layer development and nitrogen distribution on different microstructures during plasma nitriding
TB

Tim Bergelt

Technische Universität Chemnitz

Bergelt, T. (Speaker)¹
¹Chemnitz University of Technology
Vorschau
20 Min. Untertitel (CC)

Nitriding is a common thermochemical treatment to improve surface properties of steels with focus on corrosion, wear resistance and hardness. To meet the requirements of the specific application field, surface properties can be tailored in a wide range by adjusting the process parameters like nitriding temperature, processing time and atmosphere. Further, chemical composition and microstructure of the used material also influence evolution and layer growth of the nitriding zone. Focus of this work is the development of a FE-model to simulate the microstructural impact of plasma nitriding for different steels based on experimental investigations. A high-alloy tool steel X153CrMoV12 and nitriding steel 15CrMoV5-9 were plasma-nitrided at three different nitriding temperatures (480 °C, 520 °C, 560 °C) and processing times (2 h, 4 h, 16 h). The resulting nitrided zones were analysed by optical microscopy and glow discharge optical emission spectroscopy (GDOES) to characterize microstructure and nitrogen distribution dependent on process parameters. Based on the experimental data, a FE-analysis of the nitriding process was performed to investigate the influence of the plasma-nitriding parameters and the microstructure on the evolution of the nitrided zone using the commercial FE-program DEFORM. DEFORM enables the implementation of a real microstructure using a script-based approach. Up to now, only a few simulation concepts exist for nitriding processes with defined microstructure. The developed model is able to rebuild the microstructural effects like the transformation of primary carbides and consider them during the nitriding process. Therefore, a prediction of the resulting nitriding zone and the expected nitrogen distribution within the validated range is possible. Additionally, the developed model allows very good predictions regarding the distinction between chemical composition of the two investigated steels and the resulting microstructures. This enables a transfer of the results and the application of the developed model for similar materials.

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