A dynamic model for simulation of hot radial forging process

Huang, Jianglin and Slater, Carl D. and Mandral, Anup and Blackwell, Paul (2017) A dynamic model for simulation of hot radial forging process. Procedia Engineering, 207. pp. 478-483. ISSN 1877-7058 (https://doi.org/10.1016/j.proeng.2017.10.808)

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A comprehensive dynamic process model has been developed to investigate features of the inherently transient hot radial forging process, taking account of complex process kinematics, thermo-elastoplastic material behaviour and microstructural evolution. As an input to this model, a fully systematic thermomechanical testing matrix was carried out on a Gleeble 3800 including temperature (20-1100°C), strain (up to a true strain of 1) and strain rates (from 0.1 to >50 s-1). The proposed model can accurately capture vibration characteristics due to the high frequency short strokes during radial forging, which have been found to have a strong effect on material flow, forging load. Numerical analyses were performed to investigate the effect of different axial spring stiffnesses on forging load, strain distribution in the workpiece, and maximum axial feeding rate. It has been found that forging load increases significantly with increasing stiffness of the axial spring. The axial spring stiffness was also found to have a strong effect on determination of axial feeding rate and reduction ratio of workpiece by limiting the axial vibration amplitude of workpiece under the maximum compression of spring coil to avoid hard stop of workpiece in the axial direction during forging. It has been found that the spring stiffness does not have a strong effect on the strain distribution in the work piece. For practical application, the proposed model is applied to simulate the manufacturing process of a hollow transmission shaft using a GFM SKK10/R machine. Simulation results based on a 3 dimensional framework provide a detailed insight of material flow, residual stress and grain size evolution during the multiple pass radial forging process and the results are compared with available experimental measurements. The results provide valuable insights for process design.