Search

Die wear is always an important issue in hot forming processes, such as in forging and extrusion. Die life affects the economics of process to product and in order to optimise die life, the mechanism of wear should be approached scientifically. The aim of this work is to provide a systematic method for predicting and quantifying wear occurring in the extrusion of INCONEL 718 (IN718), nickel superalloy. To characterise wear, the process prediction which contributes to it must be identified and quantified. First, material characterisation was carried out using the Gleeble physical materials simulator. Then a set of unified viscoplastic constitutive equations was developed suitable for modelling microstructural evolution of IN718, i.e. evolution of average grain size, dislocation density and recrystallisation under hot forming conditions, which enabled resulting flow stress to be calculated and the microstructure of formed parts to be predicted. Second, heat transfer and friction during the forming process were investigated, by upsetting cylinders and performing ring tests on IN718. The heat transfer experimental work centres rounded the development of a reliable method for the measurement of the sub-surface temperatures in the bottom die during upsetting. The experimental values of sub-surface temperatures under various lubrication and forging conditions were analysed. A theoretical approach was proposed for the determination of the values of effective heat transfer coefficient and effective friction factor, and comparisons of experimental results and those from FE simulations were made and satisfactory matchings were obtained. Finally, integration of the material model and derived boundary conditions using subroutines for FEA are presented. Qualitative studies of abrasive die wear carrying out in a FE package, DEFORM, on the effect of various hot forming cases are shown. The numerical results are compared with the observations from mechanical measurements and metallurgical examinations for the studied die. Good correlations are found for most cases, which prove the presented methods can be used effectively in the prediction of die wear. Also, further work is suggested to enhance the modelling capabilities.