The strategy in manufacturing hardened parts used in car bodies is to tailor the mechanical properties. This is done by combining together a high-strength region and a hightoughness region to ensure the crash performa...
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Technical systems change their states and relations between elements during the transformation of energy, matter and information. Paper develops a new systematic approach to the description of processes and their clas...
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Recent advancements in implant technology include increasing application of electronic systems in the human body. Hermetic encapsulation of electronic components is necessary, specific implant functions and body envir...
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One of the most important mechanical joining technologies for mixed-material car body constructions is self-pierce riveting with semi-tubular rivet (SPR-ST). In order to achieve appropriate joint quality for SPR-ST, i...
One of the most important mechanical joining technologies for mixed-material car body constructions is self-pierce riveting with semi-tubular rivet (SPR-ST). In order to achieve appropriate joint quality for SPR-ST, it is often necessary to use individual process parameters like die geometry or rivet length for each material and thickness combination. In this paper a method is presented, that allows to increase the flexibility of the SPR-ST process by an optimization of process parameters in regard to join several material combinations with one die geometry. Thereby FEM simulation is combined with statistical approaches to develop an optimized SPR-ST process.
Press hardening of steels for the production of car body components is very common. The reason for this is that the process allows the use of blanks with low wall thickness and the production of ultra-high strength co...
Press hardening of steels for the production of car body components is very common. The reason for this is that the process allows the use of blanks with low wall thickness and the production of ultra-high strength components with complex geometries. The Hot Metal Gas forming (HMGF) process for closed profiles combines the advantages of hydroforming, such as increased rigidity, functional integration or elimination of joining operations, with those of press hardening. In this paper results of continuous tests with actively cooled tools are presented in combination with temperature and displacement measurement. Furthermore, test results for HMGF with tool integrated conductive heating are demonstrated. Tests were done with tube material PHS1800 by SSAB, part temperatures over the Point of austenitisation and maximum internal pressure of 70 MPa. Thermocouples recorded the heat distribution in the tools. Other measured and recorded variables were the displacement of the component wall while forming under increasing internal pressure by a tactile displacement sensor and simultaneous temperature of its surface with a thermal sensor head. For the first time, information on pressure, the corresponding deformation stage and temperature profile could be documented during an entire forming step. A close to series production geometry DP4 was used to investigate the tool-integrated conductive heating of components.
This paper shows a comparison of existing self-pierce riveting technologies with the newly developed self-pierce riveting with solid formable rivet (SPR-SF) for the joining of Aluminum die casts. The challenges during...
This paper shows a comparison of existing self-pierce riveting technologies with the newly developed self-pierce riveting with solid formable rivet (SPR-SF) for the joining of Aluminum die casts. The challenges during the mechanical joining of the Aluminum die cast AlSi9Mn by different joining technologies like self-pierce riveting with semi-tubular rivet (SPR-ST), self-pierce riveting with moveable die element and semi-tubular rivet (S-SPR-ST), self-pierce riveting with solid rivet (SPR-S) and self-pierce riveting with solid formable rivet (SPR-SF) will be discussed and the joining technologies in regard to process force, interlock, shear tensile strength and top tensile strength will be analyzed.
machine learning, big data and deep learning are today's catchphrases for how to improve reliability and productivity of your manufacturing equipment. Production companies implement a large number of sensors to re...
machine learning, big data and deep learning are today's catchphrases for how to improve reliability and productivity of your manufacturing equipment. Production companies implement a large number of sensors to record every activity within their production lines and learn as much as possible about their running processes in order to predict shifting product properties and to prevent stoppage due to failure. The successful application of machine learning algorithms to predict machine and process behavior depends on a reliable and balanced database. Since the foremost goal of every manufacturing business is to make sound parts and to avoid defects, there is a large amount of data available for smoothly running processes but only very little for failure production. One approach to solve this imbalance would be to link the production line data with simulation data. Simulation models allow for computing failure parts with no additional costs and therefore enable the exploration of the entire parameter space. We conducted press-hardening experiments with a variation of process parameters for a structural car body part on the press hardening line at fraunhofer IWU. As an evaluation criterion, we measured the hardness of the final part at critical spots. In order to expand the experimental data, we applied FE simulations to the entire press hardening process chain. The paper explains limitations of the model and elaborates on its parameterization. As a final task, we applied a basic machine-learning algorithm to both experimental and numerical data as well as to their combination in order to evaluate the data space expansion through simulations. The results obtained through machine learning indicate significant differences in the prediction of part quality for solely experimental data and its combination with simulation data. This is especially true for press hardening because of non-linear system behavior and a large amount of uncertain and hard-to-identify parameters. We
Due to its biocompatibility titanium is the metal of choice for most medical implants. The surface in contact with the human body may be equipped with a functional microstructure for various purposes such as bone ingr...
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ISBN:
(纸本)9780995775107
Due to its biocompatibility titanium is the metal of choice for most medical implants. The surface in contact with the human body may be equipped with a functional microstructure for various purposes such as bone ingrowth. All implants must be sterilized before operation. Among other processes, the sterilization by low energy electron beam (e-beam-sterilization) offers a lot of advantages. The non-thermal sterilization works with short process times (milliseconds) and without microbicide gases. The radiation sterilization is a regulated process according to DIN EN ISO 11137, which describes a killing effect of microorganism after the validation of a dose of 25 kGy. In principal it is possible to sterilize all material classes, electronic devices and different geometries, so that the low energy e-beam-sterilization is a suitable method for multifunctional implants. The sterilization of surface microstructures with low energy e-beam-sterilization is challenging because of the limited penetration depth. The influence of high aspect ratio microstructures on low energy e-beam-sterilization was investigated experimentally. A microhole array with 230 μm hole diameter served as a model structure and was manufactured in the titanium surface by electrical discharge machining. Other surface microstructures were generated by laser machining and blasting. All samples were contaminated with 107 CFU/sample Escherichia coli (E. coli) K12, sterilized by e-beam and incubated in a culture medium in order to prove that the sterilization was successful. The microhole depth was varied to determine the critical depth for low energy e-beam-sterilization.
Hammer-peening can replace extensive hand-polishing during the processing of freeform surfaces, but it is rarely applied in practice due to the interplay of numerous parameters, including the process and tool paramete...
Hammer-peening can replace extensive hand-polishing during the processing of freeform surfaces, but it is rarely applied in practice due to the interplay of numerous parameters, including the process and tool parameters as well as the geometry and the material of the workpiece. In the present study we systematically investigate the effect of tool radii, tool angles, pressure, path and impact distance and the path definition (with respect to the direction of previous surface milling) on the resulting surface roughness and strain hardening of a cast iron, a low- and a high-alloyed steel using a pneumatic tool setup and complementary Finite Element (FE) simulations. Our experimental results show that an impact and path distance of 0.18 mm, a pressure of 7.3 bar and a tool radius of 8 mm reduce the surface roughness of a face-milled surface with an average roughness of Ra = 0.8 μm to an average roughness of Ra = 0.5 μm for all materials under consideration. The FE simulations indicate that, for a ball-milled surface, the surface roughness Ra decreases (and the arithmetical mean height Sa increases) the most for a tool angle of 45° and for a hammer-peening path perpendicular to the previous ball-milling path. These results contribute to the development of a mathematical model that allows to identify suitable parameter combinations prior to hammer-peening processing for a given workpiece surface.
Energy-labels draw users’ attention to energy efficiency and thus they force the manufacturers to reduce the energy consumption of their products. This paper focuses on the large variety of metal-cutting machine tool...
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