Intelligent machining simulation: Process Modelling and Functional Performance Prediction of Superalloys

Machining is one of the fundamental manufacturing operations wherein the material experiences a very complex deformation condition during the interaction with a cutting tool, Figure 1. To meet quality standards and achieve efficient productivity, a number of time-consuming and costly experimental trials are typically used to optimise cutting parameters and show part
conformity, particularly for safety critical aerospace components. Although there already exists some knowledge about the effect of cutting operation on the produced surface qualities and subsurface deformation, there is not a reliable non-destructive technique available to detect their presence nor the extent of which these features affect the parts performance is known. Additionally, many modelling strategies have already been developed to reduce the need for experimental observations, however these are either very time consuming or not comprehensive enough to link the process parameters and simulations to the parts quality with respect to their service life.
The project aims to develop a digital platform for simulation of machining process, produced surface integrity and functional performance of the superalloys in order to create an intelligent framework for process control and optimisation with respect to the applied cutting parameters and cutting tool conditions. A multi-scale physics based Finite Element model of the cutting process will be realised to simulate the chip formation and predict the machining induced deformation and stress state on the workpiece materials. The results are used to model microstructural morphology and surface integrity at the machined surface that will be fed into a functional performance analysis under various service loads.