From Orthogonal Cutting Experiments towards Easy-to-Implement and Accurate Flow Stress Data

Abstract

Despite recent advances in numerical modeling of machining processes showing a significant potential for shortening product and process design activities, the broader application of the Finite Element Method (FEM)–based modeling approaches in the manufacturing industry is still limited by the expensive and time-consuming techniques involved in obtaining accurate material flow stress data. This study proposes a new efficient approach consisting of a combined numerical-empirical methodology for inversely identifying the thermomechanical material behavior of AISI 316L stainless steel from machining experiments. In order to establish the work material's flow stress properties under the extreme conditions of machining, the Johnson–Cook (JC) constitutive equation is chosen to consider the impacts of strain, strain-rate, and temperature. Due to the unstable material behavior of AISI 316L stainless steel under certain thermomechanical conditions in the primary shear zone, the calibration of a damage model is integrated into the process for evaluating the flow stress data.

The methodology approximates the material constants of the JC relationship by systematically comparing experimentally measured machining results with those predicted equivalents of a 2D implicit FEM process model. The methodology is experimentally verified on AISI 316L stainless steel with respect to cutting forces, chip geometries and temperatures in the tool-chip interface.

Keywords:

• AISI 306L
• Inverse identification
• Johnson-Cook
• Material model
• Orthogonal cutting