Numerical Modelling and Analysis of Orthogonal Metal Cutting

Abstract: Most components in use in our society have undergone a machining process at some stage within its manufacturing cycle. As a result, the economics of the machining process plays an important role in the manufacturing costs. There are several reasons for developing a rational approach to material removal, such as improving cutting techniques, producing products with enhanced precision, and increasing the rate of production. The economics of the cutting process has made this area one of great importance from both the technical and the engineering economics points of view. As a result analytical models have been developed in order to achieve a better understanding about the phenomena occurring in the cutting process such as Ernst and Mechant shear angle relationship. Continuous development of numerical methods, such as the finite element method together with more computing power, gives the potential to simulate the complex physical phenomena involved in the chip formation of a cutting process. The research work presented in this dissertation concerns the development of finite element models of the turning process. The finite element method has been used to gain better understanding of the cutting process. Both the updated Lagrangian- and the arbitrary Lagrangian-Eulerian formulation have been applied. For the time integration both the explicit and implicit time scheme have been used. The finite element models presented here is able to simulate a diversity of process parameters. Considering the workpiece the following process characteristics are investigated chip formation, cutting forces, temperature distribution, deformation zones, sub-surface deformation, stagnation zone and minimal chip thickness. For the cutting tool the affect micro-geometry has on the maximal principal stress, force distribution and the maximum effective stress is studied. The flow stress model used during this research is the Johnson-Cook model. An inverse analysis has been performed in order to enhance and predict new constants of this flow stress model. This is achieved by experimentally determined parameters from the turning process and then an inverse analysis is conducted by the use of a Kalman filter.