Nonlinear friction is the limiting factor in using motor current signals to estimate the load of machine tools. The inertia of the axis and the positional dependency of the friction add another degree of complexity. The work focuses on industrial machining centers with ball-screw driven stages as they are used in metal cutting. The approach uses Internal low-frequency signals from the NC controller to keep the barriers for an industrial application at a minimum. The contribution of this study is twofold: First, it extends conventional analytic friction models so that they incorporate positional dependency of friction, as well as the contribution of the inertia of the axis. Second, it proposes how to model the both effects jointly through support vector regression. This data-driven model outperforms the extended Stribeck and the generalized Maxwell-slip friction models, which serve as a representative benchmark for static and dynamic friction models respectively. However, this comes with the need for a careful selection of the data, on which the support vector machine is trained, in order to obtain an accurate and general model.

The quantification of the heat flow distribution in the metal cutting process depending on the cut material and the process parameters is a research area with a long history. However, a quantification of the heat flow distribution between chip, tool, and workpiece is still a not fully solved problem and remains a necessary input value for the further modeling of temperature fields and subsequent tool wear and thermal induced surface alterations, which may impair the workpiece functionality. Thus, the following publication shows the results of orthogonal cutting in order to investigate the heat flow distribution between the chip and workpiece. Therefore, the heat partitions in the cutting process were calculated by a thermodynamic methodology. This methodology considers the temperature rise in the workpiece and the chip, measured by thermography and pyrometry, as the effect of the cutting work dissipated into sensible heat. Four metals, Inconel 718, AISI 1045, Ti6Al4V, and AlMgSi0.5, were cut at varying undeformed chip thicknesses and cutting velocities. By formulating a dimensionless number for the cutting process, the Péclet number, the thermal diffusivity was included as an evaluation criterion of heat partitioning between the chip and workpiece across material properties and process settings. In this way, the validity of the Péclet number as an evaluation criterion for heat partitions in cutting and as a valuable heuristic for process design was confirmed. Another goal was to extend the state of the art approach of empirical process analysis by orthogonal cuts with regard to specific cutting forces into the thermal domain in order to provide the basis for further temperature modeling in cutting processes. The usage of the empirical data basis was finally demonstrated for the analytical modeling of temperature fields in the workpiece during milling. Therefore, the specific heat inputs into the workpiece measured in the orthogonal cuts were transferred to the milling process kinematics in order to model the heat flow into the workpiece during milling. This heat flow was used as input for an existing analytical model in order to predict stationary temperature fields in the milling process for the two-dimensional case.

The cutting process is a complex nonlinear system. Predicting such a system with conventional regression models is inefficient. In this paper, a hybrid approach using deep neural networks (DNN) is proposed to predict the specific cutting forces. With the aim of obtaining the hybrid training data, orthogonal cutting tests and 2D FEM chip formation simulations have been performed under diverse cutting parameters, tool geometries and tool wear conditions. Predictive models using a DNN and a conventional linear regression method were established. In comparison with the conventional linear regression method, the hybrid model using the machining learning is more accurate.

Fir tree slots in turbine discs are used as an attachment between the disc and the blades. To a great extend, these slots are manufactured by broaching. Currently, the used cutting tool material is High Speed Steel (HSS). Due to its low high temperature stability, the manufacturing process is limited to low cutting speeds (vc = 2–5 m/min) and presents, therefore, a bottleneck in the turbine manufacturing process. To increase the productivity, cemented carbide can be used as cutting tool material with cutting speeds up to five times higher than those used for HSS. Due to the high safety demands, the broaching process requires extensive process design to ensure a high process reliability. For the tool design, profound knowledge of the mechanical loads is mandatory due to its major effect on the manufactured part. Empirical research to investigate the actual mechanical load is time-consuming and expensive due to high tool costs, especially of cemented carbide broaches, and the high amount of possible tool geometry combinations. In this paper, an alternative approach to determine the cutting forces is presented. Grooving experiments were conducted in order to reproduce the engagement conditions from the broaching process. If the transferability of this approach can be shown, the amount of broaching tools as well as the availability of a broaching machine tool for the design of new broaching tools can be decrease dramatically. This would result in a reduction of tool design time and an increase in productivity for tool manufacturers.

Knowledge about the angular tool position is important for many modern process monitoring or control systems in machining. However, the availability of a high-resolution encoder is not always given, and its access creates further expenditure. Hence, a new method was developed to generate the tool position out of the measurement signal of the effective power. Thus, the signal used for process monitoring also provides further information about the tool position. The method is based on a statistical analysis of the signal in order to find recurring patterns and is validated in a hobbing process.

The quantification of the heat flow distribution in the cutting zone is still a not solved problem in particular if cooling lubrication is involved. The publication introduces a model extended measuring approach in order to monitor heat and coolant flows in the milling process under CO2 – MQL cooling lubrication. The system featured a telemetry system in order to transmit the temperature measured by a tool-embedded thermocouple. By further data post processing of the temperature, the heat flow into the tool was inversely determined by comparison of the measured temperature a distinct point with analytically modeled, transient temperatures.

The knowledge of the tool wear condition is essential for the dimensional accuracy of the workpiece. Commonly used systems for wear monitoring are usually based on the piezoelectric force measurement. However, in industry these systems are difficult to integrate. A suitable to integrate sensor type is the acoustic emission (AE) sensor. In this paper the main focus will be on the flank wear of drilling tools. For the investigation of the emitted frequency of the flank wear different analogy experiments needs to be realized. With the help of machine learning algorithms the recorded data will be classified.

Since the 1960s, the Inconel Alloy 718 has been a standard nickel-based superalloy due to its high strength, balanced mechanical properties, and strong corrosion resistance at relatively low costs and has been widely used in critical aircraft engine components. With the aim of improving productivity and product quality by implementing advanced tools and new process designs, models such as the FE model are utilized to predict the machining performance such as the cutting forces, the tool life, and the surface integrity. In the research area of FEM chip formation simulation, the influence of flank wear on predictions has not been investigated, especially not on the underestimation of the cutting normal force. In this paper, a 2D FEM chip formation model with the coupled Eulerian-Lagrangian (CEL) method has been built to predict cutting forces as well as other material loadings (Brinksmeier et al. Procedia CIRP 13:429–434, 2014; Buchkremer and Klocke Wear 376-377:1156–1163, 2017) in the machining of Direct Aged 718. In order to validate the performance of the FE model, fundamental investigations have been performed in orthogonal cutting with different cutting parameters. Two kinds of cemented carbide cutting tools with different cobalt contents have been applied to achieve different tool wear behaviors. Moreover, the underestimation of the cutting normal force by FEM chip formation simulation has been investigated and solved in consideration of the flank wear. The introduced FE-modeling approach shows precise predictions in terms of the cutting forces and the chip formation.

Cutting super alloy is a highly sensitive manufacturing process regarding the complex thermo-mechanical interactions in the cutting zone, which finally determine the capability of the process in order to reach economic requirements. The connection between the intensity of heat sources as well as heat partitions into the tool, work piece and chip is yet not fully understood. Thus heat flows and other thermal conditions in the cutting zone cannot be predicted satisfactory, though they influence the chip formation mechanics, the surface integrity, respectively functionality of the machined work piece as well as the tool wear and lifetime. Because of this deficit the ecological and economical design of the manufacturing process is still limited and often not knowledge based. The proposed paper presents a methodology in order to measure and predict heat flows respectively affiliated temperatures during cutting nickel-base super alloy (Inconel 718). The heat flows in the cutting zone are determined by infrared thermography and a further energy balance by post processing the thermal images. A FE-model for chip formation simulation, which is based on CEL (Coupled-Eulerian-Lagrange) formulation, was used to calculate the heat flows. Finally, the results of the simulation and the experiments were compared.

Mechanistic force models allow an estimation of the force components in cutting technology. This is essential for an accurate simulation of the force, an analysis of the tool load, or a model-based predictive force control. The model coefficients do not only depend on the material and the tool but also on the engagement condition. This requires an online identification of those coefficients. To determine those coefficients, this paper uses curve fitting based on the instantaneous uncut chip thickness, a method that has only recently gained momentum in milling. This work applies this technique to the well-established, nonlinear Kienzle force model. The paper reviews a broad range of nonlinear, derivative-free optimization algorithms for this least-squares curve-fitting problem evaluating accuracy and runtime. The evaluation is conducted on 121experiments with distinct process conditions resulting in a statistically verified conclusion. The results indicate that in spite of a heterogeneous optimization space, local constrained algorithms are most suited for model identification.

In many examinations, high-pressure coolant supply showed its' great potential to improve the productivity when machining difficult to cut materials. However, most examinations regarding the supply of metalworking fluid at elevated pressure were performed in turning. Accordingly, a profound knowledge of the fundamental mechanisms of the focused high-pressure coolant supply in milling is vital for an optimal process and tool design and mostly still missing. However, especially the sensor-based examination of the cooling effect on the tool temperature in milling under coolant supply is highly challenging, because the rotation of the tool prevents the direct application of temperature sensors in the tool. Therefore, an analogy test bench for lathes was developed to generate an interrupted cut and chips with a non-constant undeformed chip thickness h. With this test bench, different coolant supply strategies with different coolant nozzle orientation, coolant supply pressure and volumetric flow rate were examined. The results show, that the coolant supply pressure, volumetric flow rate and coolant nozzle orientation have a major influence on the tool temperature. As opposed to this, no major influence was found on the cutting force.

Many different process chains are possible to manufacture profiled grooves in turbine discs. Broaching with high speed steel tools is still state of the art today but as a consequence of the rising demand for aero engines, the disc manufacturers are striving for alternative high performance processes to increase both flexibility and productivity in the manufacturing of these safety critical features. Broaching machines are oftentimes at a bottleneck in the production of rotating turbine discs. Several other machining processes have been discussed in the context of slotting, such as broaching with carbide tools, milling, water jet machining, W-EDM and grinding. Within this paper a multi-criteria assessment approach is presented dealing with slotting processes. The assessment comprehends economical, ecological, flexibility and productivity criteria, and is based on data gathered with an aero engine OEM. The technological aspects such as tool life and productivities are based on real machining tests that have been carried out within the project HoFePro. The assessment is conducted for multiple profile shapes that represent different sizes and geometrical complexities of profiled grooves. The manufacturing processes within the assessment include broaching with HSS and carbide, milling with ceramics and carbide (side and end) as well as profile milling with carbide tools. The underlying workpiece material is a nickel-based alloy.

Recent studies have shown that machining under specific cooling and cutting conditions can be used to induce a nanocrystalline surface layer in the workspiece. This layer has beneficial properties, such as improved fatigue strength, wear resistance and tribological behavior. In machining, a promising approach for achieving grain refinement in the surface layer is the application of cryogenic cooling. The aim is to use the last step of the machining operation to induce the desired surface quality to save time-consuming and expensive post machining surface treatments. The material used in this study was AISI 304 stainless steel. This austenitic steel suffers from low yield strength that limits its technological applications. In this paper, liquid nitrogen (LN2) as cryogenic coolant, as well as minimum quantity lubrication (MQL), was applied and investigated. As a reference, conventional flood cooling was examined. Besides the cooling conditions, the feed rate was varied in four steps. A large rounded cutting edge radius and finishing cutting parameters were chosen to increase the mechanical load on the machined surface. The surface integrity was evaluated at both, the microstructural and the topographical levels. After turning experiments, a detailed analysis of the microstructure was carried out including the imaging of the surface layer and hardness measurements at varying depths within the machined layer. Along with microstructural investigations, different topological aspects, e.g., the surface roughness, were analyzed. It was shown that the resulting microstructure strongly depends on the cooling condition. This study also shows that it was possible to increase the micro hardness in the top surface layer significantly.

This study proposes a method to monitor cutting power using external voltage and current sensors installed on the feed-drive motor of a machining center. The tool load is crucial in the machining process, in particular, in metal cutting. Force/torque sensors enable for high-quality cutting force monitoring, but suffer from high investment costs. Therefore, this study uses voltage and current sensors, which are easy to implement and do not interfere with the process. This method calculates the cutting power by estimating the back-electromotive force, which is the induced voltage generated by the flux change in the motor, and filtering the cutting current which contributes only the process. The method is experimentally validated in straight slot-milling tests and compared to a dynamometer.

Broaching is still state of the art for manufacturing profiled slots in turbine discs. The broaching processes can be divided into roughing, semi-finishing, and finishing. The functionality of the manufactured slot is mainly determined by the finishing process with regard to the groove geometry and the surface integrity. Since the broaching tool is in contact with the entire fir tree slot in the finishing process, the highest process forces are expected in finishing and semi-finishing. In case of dedicate geometries, the high process forces can lead to the deformation of work piece material, and thus to geometrical inaccuracies. The process and tool design in turbine discs broaching processes are based mainly on experiences. Therefore, the new process and tool design are time- and cost-consuming by means of experiences-based design, for example, by implementation of new cutting material, such as carbide broaching tool. To predict the process forces in dependence on the slot geometry in broaching process, an analytical force model and a FEM model with coupled Eulerian-Lagrangian(CEL) formulation are introduced in this work. The investigated parameter range is based on the typical range for broaching with high speed steel for v c = 2.5 to 5 m/min, rise per tooth h = 0.02 mm. By means of the new model based approach, the broaching process and tools can be designed and optimized on the model level.

In the field of machining difficult-to-cut materials like titanium or nickel-based alloys, the application of high-pressure coolant supply may result in a significant increase in productivity and process stability. Due to enhanced cooling and lubrication of the cutting zone and thus reduced thermal tool load, tool wear can be decreased which allows higher applicable cutting speeds. Furthermore, the process stability can be increased as a result of effective chip breaking and chip evacuation. Since energy efficiency is very crucial, pressure and flow rate have to be adjusted carefully and in accordance with the cutting parameters to guarantee best results with less energy. For this purpose, experimental investigations were carried out with variation of the coolant flow rate for a given coolant pressure in order to find the minimum required value for a certain machining task with the overall aim to prevent waste of the media used. To maximise the positive effect of high-pressure coolant supply strategy on productivity and process stability, specially designed coolant jet guidance geometry on the rake face was also investigated and compared to conventional tools in turning aerospace materials TiAl6V4 and Inconel 718.

In aero engines sector, the connection between turbine discs and blades is realized by profiled grooves. The standard process to manufacture these fir tree or dove tail slots is broaching with tools out of High Speed Steel (HSS). On the one hand HSS has a high toughness, on the other hand though only a low hot hardness compared to other cutting materials like cemented carbide. However, for the introduction of cemented carbide broaching tools a redesign of the tool micro and macro geometry is necessary. For this development of broaching tools made out of alternative cutting materials as cemented carbide, especially in the finishing sector, the chips are from major interest due to the multi-flank chip formation and the resulting mechanical tool load. In this work, the multi-flank chip formation in manufacturing internal radii with cemented carbide tools was investigated. High speed recordings and cutting force measurements were implemented to analyze the chip formation with regard to the typical chip formation phenomena like wrinkling and folding, which are already examined in gear manufacturing sector for gear hopping. (C) 2018 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the 46th SME North American Manufacturing Research Conference.

Multiple technology chains are able to manufacture fir tree slots for the mounting of turbine blades including broaching, milling, non-conventional machining strategies and combinations of the named technologies. The advantageousness of the possible technology chains depends on many boundary conditions such as the capacity, the floor space, scheduled delivery, material, shape of the fir tree slots and many more. Within this paper different technology chains are assessed considering productivity and costs under the assumptions of different scenarios. The manufacturing technologies as well as their interdependencies have been investigated within a project providing technological boundary conditions for the assessment like tool lifes and required manufacturing times. The data was combined with organizational and financial data from a manufacturing OEM to enable a proper and holistic assessment. The technologies include broaching with HSS and cemented carbide as well as milling with ceramic and cemented carbide. The scenarios include different assumptions regarding the slot shape and size, the capacity and the demand for discs as well as a comparison of a brown field and green field approach. Based on the results, key parameters are deducted affecting the advantage of the considered technologies. For reasons of confidentiality, the results are obtained in a relative manner.