Thermomechanically treated (TMT) materials are characterized by a fine-grained microstructure, which leads to extraordinary mechanical properties. In this study, the alloyed tempering steel 42CrMo4 (AISI 4137) is used to set up a two-step TMT upsetting process with intermediate cooling. A water-air based cooling system was used to adjust different phase configurations between the two steps by varying the target temperature and cooling rate. Standardized test specimens for Charpy impact tests and tensile tests as well as for metallographic analyses are cut out of the formed parts. Tensile tests showed that the yield strength can be enhanced up to 1188 MPa while the elongation at break is about 12% without any additional heat treatment by forming the material after rapid cooling. This fulfills the demands of the standard in quenched and tempered state. This process route allows for local-load tailored part design and manufacturing by adjusting the forming conditions conveniently.

The current trend of mass customization pushes conventional production techniques to their limits. In the case of forming technology, limitations in terms of adaptability and flexibility emerge, while additive manufacturing lacks in the manufacturing of large, geometrically simple components. Combining both processes has potential to use the strengths of each process and thus realize time and cost efficient mass customization. As the interactions between the processes have not been fully investigated yet, in this work a distinct modelling approach in LS-DYNA is used to examine the influence of the additively manufactured elements on the formability. Namely, varying geometric properties and number of pins created with additive manufacturing are in the focus of this research. The used material is the alloy Ti-6Al-4V, which requires processing at elevated temperatures due to its low formability at room temperature. The results show a clear influence of the additively manufactured elements on the formability.

Temperature measurement close to the point of its origin is of great importance during chip removal. Therefore, two different temperature measurement methods are used and compared with each other for turning of the aluminum alloy EN AW-2017. On the one hand, cutting temperatures are measured by three thermocouples embedded in the indexable insert. On the other hand, the temperature in the contact area of the tool and the workpiece is detected by a tool-workpiece thermocouple measuring the thermoelectric voltage resulting from the Seebeck effect. For the experiments the cutting speed remains constant while the depth of cut and the feed are varied. The results show a rise of the cutting temperature with increasing cross-section of the undeformed chip. In comparison, the tool-workpiece thermocouple offers a higher sensitivity while the embedded thermocouples measure higher temperatures for large depths of cut. Hence, the suitability of the methods is affected by the cross-section of the undeformed chip.

Hot stamping of boron manganese steel is a state of the art process for manufacturing safety-relevant automotive components with regard to lightweight design. In terms of the mechanical properties, the microstructural evolution is of particular interest. Besides conventional hot stamping processes, this is especially apparent for the manufacture of hot stamped parts with tailored properties. To reduce costs and scrap parts, numerical process design requires appropriate material models considering transformation kinetics during in-die quenching. The phase transformation behavior can be characterized through experiments on various testing facilities, which can lead to discrepancies in the results and therefore in the predicted mechanical properties. In this paper, the results from two testing facilities are compared to each other through dilatometry experiments on the boron-manganese steel 22MnB5. For further characterization of the differences, secondary samples are taken to analyze the hardness as well as the microstructure by optical microscopy.

One central aspect of future high speed machining is the knowledge of the thermal behaviour of the machine tool and its motor spindle. A new temperature control for motor spindles with energy efficient synchronous reluctance drive is developed. In the first instance a finite element method model (FEM) is set up. This FEM aims to analyse the use case of nearly constant bearing temperatures within a defined range throughout the machining operation. By means of design of experiments (DOE), selected operating points of the speed-torque-characteristics are simulated with FEM considering different cooling parameters such as volume flow and inlet temperature. Machine learning algorithms are used to model the input-output-relationship in order to reduce the complex thermal motor spindle FEM. The applied algorithms are multiple linear regression and artificial neural network. The concept of temperature strategy, the FEM simulation results and the thermal models using machine learning algorithms are presented.

Vibrations have a significant influence on quality and costs in metal cutting processes. Existing methods for predicting vibrations in machine tools enable an informed choice of process settings, however they rely on costly equipment and specialised staff. Therefore, this contribution proposes to reduce the modelling effort required by using machine learning based on data gathered during production. The approach relies on two sub-models, representing the machine structure and machining process respectively. A method is proposed for initialising and updating the models in production.

The results of spatter measurements within laser-based powder bed fusion of metals are presented. A stereoscopic imaging setup and corresponding reconstruction algorithm are used to determine three-dimensional measures of the spatter characteristics from experiments with 1.4404 stainless steel. The spatter characteristics are correlated to the process zone morphology and evaporation behavior. The evolution of the spatter count over consecutive tracks is investigated and shows a decrease and convergence towards a constant value. Experiments with the process gases argon, helium and nitrogen reveal that the spatter count decreases with the gas density, whereas the spatter speed stays unaffected. This confirms the key role of the process gas in the entrainment of powder particles and the associated spatter generation. The results indicate that macroscopic spatter characteristics contain relevant information about microscopic process behavior. This makes spatter characteristics a designated process feature for new sensing approaches for the observation of industrial applications.

Ti-6Al-4V was machined by varying the nozzle position during external cryogenic CO2 cooling. The thermomechanical load was measured and the resulting surface morphology was characterized. The results show a significant influence of the nozzle position on the temperatures in the surface layer. Furthermore, a correlation between the temperatures and the microhardness inside the surface layer of the workpiece was found. This relationship was used to specify an optimal positioning of the nozzle in order to minimize the occurring temperatures.

The near-surface layer of forging tools is repeatedly exposed to high thermal and mechanical loading during industrial use. For the assessment of wear resistance of tool steels, in previous work thermal cyclic loading tests were carried out to investigate changes in hardness. However, actual results of time-temperature-austenitisation (TTA) tests with mechanical stress superposition demonstrated a distinct reduction of the austenitisation start temperature indicating a change in the occurence of tempering and martensitc re-hardening effects during forging. Therefore, the superposition of a mechanical compression stress to the thermal cyclic loading experiments is of high interest. Tests are carried out in this study to analyse hardness evolution of the tool steel H11 (1.2343) under consideration of forging process conditions. The results show that the application of compression stresses on the specimen during the temperature cycles is able to restrict tempering effects while increasing the amount of martensitic re-hardening.

Grinding is an established process for gear manufacturing, as good geometric and surface quality can be achieved. For bevel gears, grinding is used in case of high demands on accuracy and reproducibility. In industry, design of bevel gear grinding processes is usually based on experience. An efficient design of grinding processes can be performed based on the cutting force. Knowledge of the cutting force is necessary to predict the process influence on the workpiece and the wear of the grinding tools. For bevel gear grinding, no cutting force models exist. To model the cutting force in grinding processes, the contact conditions must be known. In this report, a model of the geometric contact conditions in bevel gear grinding is presented. The model is validated by comparing the simulated bevel gear flank with the ideal flank. Finally, the relation between simulation and measured process loads is analyzed.