07 Fakultät Konstruktions-, Produktions- und Fahrzeugtechnik
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/8
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Item Open Access Numerical modeling of cutting characteristics during short hole drilling : modeling of kinetic characteristics(2023) Storchak, Michael; Stehle, Thomas; Möhring, Hans-ChristianAnalyzing the cutting process characteristics opens up significant opportunities to improve various material machining processes. Numerical modeling is a well-established, powerful technique for determining various characteristics of cutting processes. The developed spatial finite element model of short hole drilling is used to determine the kinetic characteristics of the machining process, in particular, the components of cutting force and cutting power. To determine the component model parameters for the numerical model of drilling, the constitutive equation parameters, and the parameters of the contact interaction between the drill and the machined material on the example of AISI 1045 steel machining, the orthogonal cutting process was used. These parameters are determined using the inverse method. The DOE (Design of Experiment) sensitivity analysis was applied as a procedure for determining the component models parameters, which is realized by multiple simulations using the developed spatial FEM model of orthogonal cutting and the subsequent determination of generalized values of the required parameters by finding the intersection of the individual value sets of these parameters. The target values for the DOE analysis were experimentally determined kinetic characteristics of the orthogonal cutting process. The constitutive equation and contact interaction parameters were used to simulate the short hole drilling process. The comparison of experimentally determined and simulated values of the kinetic characteristics of the drilling process for a significant range of cutting speed and drill feed changes has established their satisfactory coincidence. The simulated value deviation from the corresponding measured characteristics in the whole range of cutting speed and drill feed variation did not exceed 23%.Item Open Access Generalizable process monitoring for FFF 3D printing with machine vision(2023) Werkle, Kim Torben; Trage, Caroline; Wolf, Jan; Möhring, Hans-ChristianAdditive manufacturing has experienced a surge in popularity in both commercial and private sectors over the past decade due to the growing demand for affordable and highly customized products, which are often in direct opposition to the requirements of traditional subtractive manufacturing. Fused Filament Fabrication (FFF) has emerged as the most widely-used additive manufacturing technology, despite challenges associated with achieving contour accuracy. To address this issue, the authors have developed a novel camera-based process monitoring method that enables the detection of errors in the printing process through a layer-by-layer comparison of the actual contour and the target contour obtained via G-Code processing. This method is generalizable and can be applied to different printer models with minimal hardware adjustments using off-the-shelf components. The authors have demonstrated the effectiveness of this method in automatically detecting both coarse and small contour deviations in 3D-printed parts.Item Open Access A data-driven approach for cutting force prediction in FEM machining simulations using gradient boosted machines(2024) Reeber, Tim; Wolf, Jan; Möhring, Hans-ChristianCutting simulations via the Finite Element Method (FEM) have recently gained more significance due to ever increasing computational performance and thus better resulting accuracy. However, these simulations are still time consuming and therefore cannot be deployed for an in situ evaluation of the machining processes in an industrial environment. This is due to the high non-linear nature of FEM simulations of machining processes, which require considerable computational resources. On the other hand, machine learning methods are known to capture complex non-linear behaviors. One of the most widely applied material models in cutting simulations is the Johnson-Cook material model, which has a great influence on the output of the cutting simulations and contributes to the non-linear behavior of the models, but its influence on cutting forces is sometimes difficult to assess beforehand. Therefore, this research aims to capture the highly non-linear behavior of the material model by using a dataset of multiple short-duration cutting simulations from Abaqus to learn the relationship of the Johnson-Cook material model parameters and the resulting cutting forces for a constant set of cutting conditions. The goal is to shorten the time to simulate cutting forces by encapsulating complex cutting conditions in dependence of material parameters in a single model. A total of five different models are trained and the performance is evaluated. The results show that Gradient Boosted Machines capture the influence of varying material model parameters the best and enable good predictions of cutting forces as well as deliver insights into the relevance of the material parameters for the cutting and thrust forces in orthogonal cutting.Item Open Access Determination of the tool-chip contact length for the cutting processes(2022) Storchak, Michael; Drewle, Konstantin; Menze, Christian; Stehle, Thomas; Möhring, Hans-ChristianThe thermomechanical interaction of the tool with the chip in the most loaded secondary cutting zone depends on the contact length of the tool rake face with the chip. Experimental studies of the dependency of the contact length on the cutting speed, the undeformed chip thickness, and the tool rake angle, performed by the optical method, are used for comparison with the contact length obtained by the FE modeling of the orthogonal cutting process. To determine the parameters of the constitutive Johnson-Cook equation, which serves as a material model of the FE cutting model that has a predominant influence on the contact length, a software-implemented algorithm was developed. This algorithm is based on determining the generalized parameters of the constitutive equation through finding the intersection of these parameter sets. The plurality intersection of the parameter sets of the constitutive equation is determined by means of the design of experiments and refined by subsequent multiple iterations. The comparison of the contact length values, obtained by simulating the cutting process using the generalized parameters of the constitutive equation as a material model with their experimental values, does not exceed 12% for a wide range of cutting speeds and depths of cut, as well as for the tool rake angle.Item Open Access Validation of the manufacturing Methodology of prestressed fiber-reinforced polymer concrete by the variation of process parameters(2023) Engert, Michelle; Werkle, Kim Torben; Wegner, Robert; Born, Larissa; Gresser, Götz T.; Möhring, Hans-ChristianPolymer concrete has proved to be advantageous in machine building for many years thanks to its excellent damping properties. Until now, its use was limited to machine beds due to its comparatively low tensile strength. Its use in moving structural components has not been possible until now. Recent research results have shown that this challenge can be met by integrating prestressed carbon fibers. Until now, the production of samples out of prestressed fiber-reinforced polymer concrete has been carried out according to fixed specifications. It is not yet clear whether these specifications are suitable to fully exploit the potential of the material. Samples manufactured to these specifications show at least a large scatter in bending stiffness. Within the scope of this paper, the existing manufacturing process is validated by the variation of process steps. Specifically, this involved the use of a shaker, variation of the dwell time in the mold, variation of the resin content, and the procedure for impregnating the fibers. The characterization of the samples showed that the scatter could only be reduced by increasing the dwell time. However, this leads to a decrease in bending stiffness and, thus, is not suitable for further improvement of the novel material.Item Open Access Determination of the shear angle in the orthogonal cutting process(2022) Storchak, Michael; Stehle, Thomas; Möhring, Hans-ChristianDetermination of the shear angle by experimental and analytical methods, as well as by numerical simulation, is presented. Experimental determination of the shear angle was performed by analyzing the chip roots obtained by the method of cutting process quick stop through purposeful fracture of the workpiece in the area surrounding the primary cutting zone. The analytical determination of the shear angle was carried out using the chip compression ratio and was based on the principle of a potential energy minimum. Measurement of the shear angle in the numerical simulation of orthogonal cutting was performed using the strain rate pattern of the machined material at the selected simulation moment. It was analyzed how the parameters of the Johnson-Cook constitutive equation and the friction model affect the shear angle value. The parameters with a predominant effect on the shear angle were determined. Then the generalized values of these parameters were established with a software algorithm based on identifying the intersection of the constitutive equation parameter sets. The use of generalized parameters provided the largest deviation between experimental and simulated shear angle values from 9% to 18% and between simulated and analytically calculated shear angle values from 7% to 12%.Item Open Access Numerical modeling of cutting characteristics during short hole drilling : part 2 - modeling of thermal characteristics(2024) Storchak, Michael; Stehle, Thomas; Möhring, Hans-ChristianThe modeling of machining process characteristics and, in particular, of various cutting processes occupies a significant part of modern research. Determining the thermal characteristics in short hole drilling processes by numerical simulation is the object of the present study. For different contact conditions of the workpiece with the drill cutting inserts, the thermal properties of the machined material were determined. The above-mentioned properties and parameters of the model components were established using a three-dimensional finite element model of orthogonal cutting. Determination of the generalized values of the machined material thermal properties was performed by finding the set intersection of individual properties values using a previously developed software algorithm. A comparison of experimental and simulated values of cutting temperature in the workpiece points located at different distances from the drilled hole surface and on the lateral clearance face of the drill outer cutting insert shows the validity of the developed numerical model for drilling short holes. The difference between simulated and measured temperature values did not exceed 22.4% in the whole range of the studied cutting modes.Item Open Access Optimization of a clamping concept based on machine learning(2021) Feng, Qi; Maier, Walther; Stehle, Thomas; Möhring, Hans-ChristianFixtures are an important element of the manufacturing system, as they ensure productive and accurate machining of differently shaped workpieces. Regarding the fixture design or the layout of fixture elements, a high static and dynamic stiffness of fixtures is therefore required to ensure the defined position and orientation of workpieces under process loads, e.g. cutting forces. Nowadays, with the increase in computing performance and the development of new algorithms, machine learning (ML) offers an appropriate possibility to use regression methods for creating realistic, rapid and reliable equivalent ML models instead of simulations based on the finite element method (FEM). This research work introduces a novel method that allows an optimization of clamping concepts and fixture design by means of ML, in order to reduce manufacturing errors and to obtain an increased stiffness of fixtures and machining accuracy. This paper describes the preparation of a dataset for training ML models, the systematic selection of the most promising regression algorithm based on relevant criteria, the implementation of the chosen algorithm Extreme Gradient Boosting (XGBoost) and other comparable algorithms, the analysis of their regression results, and the validation of the optimization for a selected clamping concept.Item Open Access Influence of the manufacturing parameters of an AlMg5 wire-based hybrid production process on quality and mechanical properties(2021) Möhring, Hans-Christian; Becker, Dina; Eisseler, Rocco; Stehle, Thomas; Reeber, TimHybrid manufacturing processes are known for combining the advantages of additive manufacturing and more traditional manufacturing processes such as machining to create components of complex geometry while minimising material waste. The trend towards lightweight design, especially in view of e-mobility, gives aluminium materials an important role to play. This study examines the use of aluminium alloys in laser metal wire deposition (LMWD) processes with subsequent subtractive machining, which is considerably more difficult due to the different process-related influences. The investigations are focussed on the influence of the differently controlled laser power on the shape accuracy, the microstructure, and the hardness of the AlMg5 test components after the LMWD process with subsequent subtractive machining by turning. The long-term goal of the investigations is to increase the stability of the hybrid production process of AlMg5 components with defined dimensional accuracy and mechanical properties.Item Open Access Improving machinability of additively manufactured components with selectively weakened material(2021) Maucher, Clemens; Teich, Heiko; Möhring, Hans-ChristianPart design and the possibilities of production are disrupted by the increased usage of additive manufacturing (AM). Featuring excellent creative freedom due to the layer-by-layer buildup of components, AM leads to profound changes in future part design and enables previously impossible geometries. Laser powder bed fusion (LPBF) technology already allows to manufacture small quantities of parts with high productivity and material efficiency. Due to the specific process characteristics, the resulting surface finish of these parts is insufficient for a wide range of applications, and post-processing is usually unavoidable. Specifically for functional surfaces, this post-processing is often done by machining processes, which can pose challenges for intricate and complex AM parts due to excessive machining forces. In the present paper, the influence and the possibilities of the LPBF process parameters on the subtractive post-processing are shown. A novel weakened structure is developed to selectively reduce the strength of the material and improve the cutting conditions. Chip formation, cutting forces and vibrations during drilling as well as cutting forces during an orthogonal cut are examined. To quantify the differences, a comparison of the machinability between bulk material, standard support structures and the weakened structure is carried out.