Investigation of the mechanical workpiece loading during orthogonal cutting AISI 4140 by means of digital image correlation

Against the background of advancing climate change, the manufacturing industry is also facing enormous challenges. In this context, the downsizing of components plays a special role, driven not only by the increasing electrification of powertrain systems, but also with the aim of increasing component power density. This places high demands on component geometry and dimensional accuracy as well as on the required material and subsurface workpiece properties. The latter have a decisive influence on the application behavior and service life of the components and must be individually adapted to the corresponding application, not only in the case of safety-critical components. Changes in the workpiece surface integrity state, such as a changed residual stress profile or the formation of a White Layer caused by dynamic recrystallization, are induced by the thermo-mechanical load spectrum of the machining process on the workpiece side. In order to avoid subsurface damage, numerous, mostly destructive test methods are therefore used to characterize the subsurface workpiece condition. This time-consuming and cost-intensive quality processes may be drastically shortened by using numerical or analytical models to estimate the surface integrity state, thus increasing the cost efficiency of manufacturing processes. In addition, innovative measurement techniques offer the possibility to calibrate and validate models with spatially and temporally highly resolved process state variables and thus to increase their prediction quality. For this reason, a method for analyzing the process-induced strain rate fields during orthogonal machining of hardened AISI 4140 based on Digital Image Correlation (DIC) will be presented in this paper. Furthermore it was used to investigate the penetration depth of the strain rate field as a function of the process parameters. In the future, a physics-based in-process determination of process-induced workpiece surface integrity change can be built on this approach.