The surface and subsurface conditions of components are significant for their functional properties. Every manufacturing process step changes the surface condition due to its mechanical, chemical and/or thermal impact. The depth of the affected zone varies for different machining operations, and is predetermined by the process parameters and characteristics. Furthermore, the initial state has a decisive influence on the interactions that lead to the final surface conditions. The aim of the investigation presented here is to compare the influence of the load characteristics over the depth applied to manufactured components by several different machining operations and to determine the causing mechanisms. In order to ensure better comparability between the surface modifications caused by different machining operations, the same material was used (AISI 4140; German steel grade 42CrMo4 acc. to DIN EN 10083-3) and annealed to a ferritic-pearlitic microstructure. Based on interdisciplinary cooperation within the collaborative research center CRC/Transregio 136 “Process Signatures”, seven different manufacturing processes, i.e., grinding, turning, deep rolling, laser processing, inductive heat treatment, electrical discharge machining (EDM) and electrochemical machining (ECM), were used, and the resulting surface zones were investigated by highly specialized analysis techniques. This work presents the results of X-ray measurements, hardness measurements and electron microscopic investigations. As a result, the characteristics and depths of the material modifications, as well as their underlying mechanisms and causes, were studied. Mechanisms occurring within 42CrMo4 steel due to thermal, mechanical, chemical or mixed impacts were identified as phase transformation, solidification and strengthening due to dislocation generation and accumulation, continuum dynamic recrystallization and dynamic recovery, as well as chemical reactions.

Additive manufacturing (AM) techniques enable new design concepts for performance improvements and functional integration in a wide range of industries. One promising application is in additively manufactured cutting tools for machining, improving process reliability on the one hand and increasing tool life and process productivity on the other hand. Compared to conventional manufacturing processes, AM allows for new and complex geometrical designs, enables the production of individualized parts, and offers new possibilities for alloy composition and material design. This work gives a comprehensive and systematic review of scientific as well as industrial activities, studies, and solutions regarding AM cutting tools and their fields of application. Four different areas are identified, including cooling and coolant supply, damping and vibrational behavior, lightweight design and topology optimization, and functional integration. Thus, the relevant and promising approaches for the industrialization of AM cutting tools are highlighted, and a perspective is given on where further scientific knowledge is needed.

Thermo-mechanical loads during hard turning lead to the formation of so-called White Layers on the machined surface. Characterized by a very fine microstructure and high hardness, White Layers have a negative effect on the fatigue life of a component. The fundamental mechanism for the White Layer formation is the dynamic recrystallization (DRX). Therefore, in the current work, two different DRX models, Helmholtz free energy and Zener-Hollomon, are implemented into Abaqus/Explicit to predict the thickness of the White Layer when hard turning quenched/tempered AISI 4140 and the results are compared with each other. For the simulation of the machining process a Finite Element Method (FEM) model based on the Coupled-Eulerian-Lagrangian (CEL) method is built up. Although both DRX models achieved a very good match between predicted and measured White Layer thickness and grain size evolution on the workpiece rim zone, the Zener-Hollomon model produced more closer agreement.

With the development of advanced image correlation and high-speed filming techniques, the kinematic field during the cutting process can be experimentally determined including the velocity and strain rate fields. As known, the setting parameters for the digital image correlation (DIC) as well as the optical parameters of the given camera and lighting system have a great influence on the spatial resolution and accuracy of the DIC results. In this study, the speckle pattern in terms of speckle size and intensity distribution are analyzed when using two different surface preparation methods. Moreover, the influences of the subset sizes for the image correlation on the strain rate are numerically studied. Interlaboratory measurements of the kinematic field during the orthogonal cutting of AISI 4140 were conducted with two different in-situ imaging setups. The material flow near the cutting tool edge determined from the velocity field is compared with the numerical simulation. The stagnation zone which is commonly found in the numerical simulation of the cutting process using a chamfered cubic boron nitride (CBN) tool was not observed in the experiments. Furthermore, slip-line fields were constructed from the experimentally determined strain rate components, from which the boundary conditions along the chip-free and chip-tool interface were derived.

Workpiece rim zone modifications during hard machining can be explained with the high thermo-mechanical loads induced by the cutting process. The formation of White Layers with a fine-grained microstructure by dynamic recrystallization (DRX) is one of those surface modifications that can negatively affect the functionality of a machined part by changing the residual stress state and facilitating crack initiation. As a consequence, the fatigue life of the machined parts is reduced. It is therefore of great interest to understand the thermo-mechanical conditions which induce White Layers formation in order to be able to control them by in-situ measurements if necessary. For this purpose, a cutting force based Soft-Sensor is developed in this study which enables the in-process estimation of White Layer thickness. Therefore, a cutting force based analytical model is used to estimate the resulting temperature fields and correlated with validated numerical chip formation simulations. In addition, the predictions of the White Layer thickness of the analytical model are then compared using light microscopy and the results of the numerical finite element model, in which a DRX model is additionally implemented.