The modelling of metal cutting has proved to be particularly complex due to the diversity of physical phenomena involved, including thermo-mechanical coupling, contact/friction and material failure. The present work outlines the wide range of complex physical phenomena involved in the chip formation in a descriptive manner. In order to improve and understand the process different numerical strategies have been used for simulation. Several of these numerical strategies are reviewed and a short discussion of their relative merits and drawbacks is presented. By means of several examples, where a combined experimental/numerical effort was undertaken, we try to illustrate what numerical techniques, models and pertinent parameters are needed for successful simulations.

A dislocation density material model based on model-based-phenomenology has been used to predict orthogonal cutting of stainless steel Sanmac 316L. The chip morphology and the cutting forces are used to validate the model. The simulated cutting forces and the chip morphology showed good conformity with practical measurements. Furthermore, simulation of cutting process utilizing the dislocation density based material model improved understanding regarding material behaviour such as strain hardening and shear localization at the process zone.

No abstract

No abstract

With an increasing number of and also more complex demands on today’s automobiles the need for fast and accurate simulations to support the Engineering Design (ED) process is getting more important. The demands that are put on the automotive designs are often contradictory i.e. weight against stiffness, and no one optimal set of solutions can be found, rather a trade-off situation. At Volvo Cars Corporation, known all over the world for their safety policy, the advancement to more high strength materials is causing new problems for the engineers. As widely known, a steel material that has been exposed to plastic deformation will suffer hardening in those areas. The work in this paper, exemplified in a deployed demonstrator, show that it is possible to combine forming and crashworthiness simulations in an automated way to make advanced simulation accessible to more people in the product development process. The Knowledge Enabled Engineering (KEE) demonstrator combines forming and crashworthiness simulations for dealing with the constant trade-off in ED.