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ASME 2019 International Mechanical Engineering Congress and Exposition, IMECE 2019

作者： Schieck, Frank Mauermann, Reinhard Weise, Dieter Demmler, Matthias Fraunhofer Institute for Machine Tools and Forming Technology IWU Chemnitz Saxony Germany

ISBN: (纸本)9780791859377

The production of complex, large-scale cladding parts made of metal in small quantities for a wide range of applications in architecture, power generation, shipbuilding, but also rail vehicle construction, mobile work machines and, last but not least, automotive sector is a major challenge in terms of principled manufacturability, but also in terms of manufacturing costs. Appropriate components are often produced in small quantities by hand, whereby the reproducibility and achievable quality depend largely on the experience and craftsmanship of the employer. The incremental forming using CNC-controlled machine tools or robots offers a good alternative for an efficient and reproducible production of sheet metal components with batch size one. There are already a large number of research work, studies and examples of applications worldwide regarding principled incremental forming strategies, process layout, FE simulation and optimization strategies. The fraunhofer IWU works with the claim of applied research, that is, to transfer results from basic research into an industrial application. This also applies to the field of incremental sheet metal forming. Especially in the area of large-scale, 3-dimensional components, there is a very great need on the part of the industry. The paper provides an overview of current research results in the field of incremental forming of industrially relevant large-scale structures up to dimensions of approximately 4 x 2 meters, which are carried out in the single point process on a modified large milling machine. The topic of shape storage (molds), flexible clamping frames and heating equipment for temperature-supporting incremental forming of light metals is also addressed. The outlook identifies application and development potential aimed at both the further development of the technology and the associated equipment technology. Copyright © 2019 ASME.

关键词： machine tools

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Automated design of product-flexible car body fixtures with software-supported part alignment using particle swarm optimization

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Procedia CIRP 2020年 88卷 157-162页

作者： Rayk Fritzsche Eric Voigt Robert Schaffrath Marcel Todtermuschke Marcel Röber Head of group Assembly systems at Fraunhofer Institute for Machine Tools and Forming Technology IWU Reichenhainer Straße 88 Chemnitz 09126 Germany Scientific employee at Fraunhofer Institute for Machine Tools and Forming Technology IWU Reichenhainer Straße 88 Chemnitz 09126 Germany Head of dep. Assembly systems at Fraunhofer Institute for Machine Tools and Forming Technology IWU Reichenhainer Straße 88 Chemnitz 09126 Germany

The fraunhofer IWU has been developed specialized clamping robots for production of different car-models on one fixture. As a base for the fixture design, a method for optimal part alignment has been developed. For handling multitude of possibilities regarding the alignment of parts from different car-models, a specific software tool using particle swarm optimization has been created. The objective was to achieve similar travels for all clamping robots in this fixture. To facilitate the integration of the automated part alignment into fixture design, a further software tool for automatically designing a flexible fixture was modelled.

关键词： Body in white Automated device design Particle swarm optimization Product flexibility

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Discomfort Detection During Automated Driving Using Temporal Transformers

SSRN

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SSRN 2025年

作者： Assarzadeh, Maha Hartwich, Franziska Vitay, Julien Bocklisch, Franziska Hamker, Fred H. Artificial Intelligence Computer Science Chemnitz University of Technology Chemnitz Germany Fraunhofer Institute for Machine Tools and Forming Technology Chemnitz Germany Materials and Surface Engineering Group Chemnitz University of Technology Chemnitz Germany

With the recent breakthroughs in driving automation and the development of smart vehicles, human-technology interaction issues, such as detecting comfort levels in automated driving, have been gaining increasing attention. We assessed a passenger’s discomfort level in a smart, automated vehicle using physiological, environmental, and vehicle automation features from different sensors. Given the evidence of discomfort levels being an evolving psychological state in time, the tracking of discomfort levels for passengers of an automated vehicle can be considered a time-varying phenomenon. Our approach is to dynamically predict discomfort levels using time-dependent models, particularly the Temporal Fusion Transformer (TFT), an advanced attention-based deep learning architecture providing an interpretable explanation of temporal dynamics as well as high-performance forecasting over multiple horizons. The models are trained and evaluated using a dataset of 100 participants of a simulated automated driving experiment, during which they signaled their level of discomfort using a manual device. Two TFT models, TFT-full and TFT-restricted, are investigated depending on which physiological, environmental, and vehicle automation signals are used as inputs. The results are compared with the auto-regressive model DeepAR. Different window sizes are used to analyze the impact of the window size on the model’s performance. Among the tested models, TFT-restricted with a window size of 300-time steps (about 5 seconds) demonstrates the best performance in predicting discomfort levels on our data, with a mean absolute error (MAE) of 0.037 and a root mean square error (RMSE) of 0.131. © 2025, The Authors. All rights reserved.

关键词： Physiological models

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Gathering of Process Data through Numerical Simulation for the Application of machine Learning Prognosis Algorithms

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Procedia Manufacturing 2020年 47卷 608-614页

作者： Mathias Jäckel Tobias Falk Julius Georgi Welf-Guntram Drossel Fraunhofer Institute for Machine Tools and Forming Technology IWU Nöthnitzer Straße 44 Dresden 01187 Germany

In recent years, FEA simulation of forming processes has increasingly developed as a good alternative to complex experimental work in the determination of process parameters and product properties. However, detailed material data (e.g. flow curves) are necessary for the execution of FEA simulations, which are often not available to manufacturers and users in the early stages of the product development. In this paper, a method is shown by which application it is possible, that only on the basis the general mechanical properties (e.g. tensile strength, sheet thickness) and the use of data-based prognosis models of supervised machine learning to predict directly a result regarding suitable process parameters as well as expected forming result properties. Thereby an extensive technological database was generated for the joining by forming process self-pierce riveting (SPR) by means of numerical simulation. Subsequently, different learning algorithms are trained using these numerical data and their prediction quality is compared.

关键词： machine Learning forming Simulation Self-pierce riveting

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Geometric empirical modelling of forces influenced by the cutting edge microgeometry in orthogonal cutting of unidirectional CFRP

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Procedia CIRP 2021年 102卷 25-30页

作者： Konstantin Sauer Alexander Nowak Joachim Regel Rafael Wertheim Martin Dix Chemnitz University of Technology Professorship Production Systems and Processes Reichenhainer Strasse 70 09126 Chemnitz Germany Chemnitz University of Technology Professorship Machine Elements and Product Development Reichenhainer Strasse 70 09126 Chemnitz Germany Fraunhofer Institue for Machine Tools and Forming Technology Reichenhainer Strasse 88 09126 Chemnitz Germany

In optimising the cutting of carbon fibre reinforced plastics (CFRP), increasing emphasis is placed on the cutting edge microgeometry. A significant challenge lies in understanding the engagement conditions between tool and workpiece, influencing tool wear mechanisms and performance. This paper aims to provide a more in-depth insight into the influence of cutting parameters on process forces when applying ideally rounded cutting edges in orthogonal cutting. A geometric empirical process model is developed for calculating the cutting force and the passive force, considering the cutting edge radius, the uncut chip thickness, and the fibre cutting angle. As a result, the minimum uncut chip thickness was determined, and process forces were calculated.

关键词： composite cutting edge modelling orthogonal cutting

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Development of a New Self-flaring Rivet Geometry Using Finite Element Method and Design of Experiments

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Procedia Manufacturing 2020年 47卷 383-388页

作者： Christian Kraus Tobias Falk Reinhard Mauermann Welf-Guntram Drossel Fraunhofer Institute for Machine Tools and Forming Technology IWU Nöthnitzer Straße 44 Dresden 01187 Germany

The paper presents a new joining process for mixed joints of metallic and non-metallic materials. The process bases on a self-flaring rivet, which lances the joining partners and, due to its geometry, produces an interlock. In contrast to conventional self-piercing processes such as self-pierce riveting with semi-tubular rivets (SPR), the new process does not require a special shaped die as counter tool. The development of the rivet geometry is carried out with the aid of FEM analyses in SFTC Deform-3D. Design of experiments (DoE) is used to find a suitable rivet geometry that is stable enough to lance high-strength steel. However, the rivet element must be flaring to produce an interlock. The challenges and solution approaches associated with the modelling of material damage and separation in the three-dimensional calculation models of the riveting process are presented. The consideration of macromechanical and geometrical criteria for element deletion is important in order to obtain robust models with useful results. The validation of the model is done by comparing the simulation results with experimental data.

关键词： Mechanical Joining Finite Element Method Design of Experiments

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Automated continuous fabrication of load-path adapted thermoplastic fiber prepregs 18

Automated continuous fabrication of load-path adapted thermo...

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18th European Conference on Composite Materials, ECCM 2018

作者： Gabriel, Felix Nebel, Daniel Fürst, Alexander TU Braunschweig Institute of Machine Tools and Production Technology Langer Kamp 19b Braunschweig38106 Germany Fraunhofer Institute for Machine Tools and Forming Technology STEX Department Fraunhofer Project Center Wolfsburg Hermann-Münch-Straße 2 Wolfsburg38440 Germany TU Braunschweig Institute for Engineering Design Langer Kamp 8 Braunschweig38106 Germany

ISBN: (纸本)9781510896932

Due to the lack of suitable production processes, most up-to-date composite components show a rather simple shell design with constant laminate build-up. Such designs are also known as "black metal" and lead to high costs and incomplete material utilization. In contrast, a special load-path adapted design with a high utilization of deployed materials can increase the lightweight degree and reduce costs at the same time. This paper proposes a first practical approach to provide the automated continuous fabrication of load-path adapted thermoplastic fiber prepregs in a calendaring process. For the complete impregnation of the textile, additional matrix is added in powder form in order to ensure a homogenous fiber volume ratio. An adjustable powder application system is proposed, which can be directly integrated into the calender and is able to follow the load-path adapted design routes provided as continuous semifinished material. A sensor-driven control strategy for the application module is presented in order to cope with the challenge of synchronization of the conveyed semifinished textile with the positioning and powder dosing mechanisms of the application system. © CCM 2020 - 18th European Conference on Composite Materials. All rights reserved.

关键词： Fabrication

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Temporal analysis of event-discrete alarm data for improved manufacturing

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Procedia CIRP 2020年 93卷 742-746页

作者： Heiner Reinhardt Jan-Peter Bergmann Anke Stoll Matthias Putz Fraunhofer Institute for Machine Tools and Forming Technology IWU Reichenhainer Straße 88 09126 Chemnitz Germany

Efficient response to machine failures is crucial for improving machine availability. In practice, the number of alarms occurring during the operation of manufacturing systems could overwhelm even experienced machine operators. Manufacturing execution systems (MES) therefore often allow for alarm data acquisition as well as its filtering and aggregation to reduce the occurring information overload. However, manual configuration of these systems may be cumbersome and time-consuming. Hence, we propose an event-discrete method for temporal alarm data analysis to support the configuration process.

关键词： Man-machine system Maintenance Pattern recognition Knowledge management Algorithm Analysis Automation Condition monitoring Manufacturing system Complexity

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Impact of Cyber-physically enhanced manufacturing on the product requirement documentation in high-tech applications

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Procedia CIRP 2021年 102卷 210-215页

作者： Albrecht Hänel André Seidel Carl Willy Mehling Alexander Dementyev Karol Kozak Rudi Seidel Uwe Teicher Arvid Hellmich Welf-Guntram Drossel Steffen Ihlenfeldt Fraunhofer Institute for Machine Tools and Forming Technology IWU Dresden 01187 Germany Technische Universität Dresden Center for Evidence-based Healthcare Dresden 01307 Germany Technische Universität Chemnitz Institute for Machine Tools and Production Processes Chemnitz 09126 Germany Technische Universität Dresden Institute of Mechatronic Engineering Dresden 01062 Germany

Conventional machining of high-tech parts and components is often associated with complex processes, long lead times and small to medium batch sizes. Obviously, there is great interest to shorten process development periods and increase process reliability. The transformation of conventional machines into cyber-physical production systems (CPPS) promises significant improvements here. In fact, CPPS allows real-time data acquisition and processing, enabling to target integrated process improvement and quality assurance. In the present work, a methodical procedure for structured data aggregation is introduced for a Cyber-physical enhanced machining process while being explained from a high-tech application point of view. This includes data generation, extraction, transfer and storage, data-consolidation, linkage, visualization and interpretation. Finally, the paper illustrates these aspects in terms of the effects on the “digital product requirements” in order to achieve the presented “analytics-ready” data model using the example of a high-tech application.

关键词： Digital Manufacturing System Modelling Process control Cyber-physical production

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Laser structuring with DLIP technology of tungsten carbide with different binder content

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Procedia CIRP 2022年 111卷 601-604页

作者： Uwe Teicher Robert Baumann Yasmine Bouraoui Anas Ben Achour Andrés Fabián Lasagni Steffen Ihlenfeldt Fraunhofer Institute for Machine Tools and Forming Technology IWU Nöthnitzer Straße 44 01187 Dresden Germany Institute for Manufacturing Technology Technische Universität Dresden George-Baehr-Str. 3c 01069 Dresden Germany Fraunhofer Institute for Material and Beam Technology IWS Winterbergstraße 28 01277 Dresden Germany Institute of Mechatronic Engineering Technische Universität Dresden Helmholtzstraße 7a 01069 Dresden Germany

In machining, tool wear is one of the main influence factors for the resulting quality of the product. Several wear mechanisms have to be addressed to prevent unwanted deterioration of the tool integrity. For aluminium alloys, adhesion of the workpiece material on the cutting tool is one of the most challenging wear mechanisms. Engineering surface microtopographies has been proved as a convenient strategy to tackle this issue. Particularly, the direct laser interference patterning (DLIP) technique enables the integration of periodic structures on the micrometer or sub-micrometer scale. In this study the structuring of tungsten carbide with different cobalt content is presented. The interference of two laser beams leads to periodic line-like structures with a spatial period of 5.5 µm. A maximum structure depth of 2.2 µm is reached by controlling the processing parameters. Moreover, the wettability of the structured samples was analyzed by contact angle measurements with selected cooling lubricants, revealing a hydrophilic behavior with a decreased contact angle of 10°. This work gives an insight into the possibilities of structuring tungsten carbide materials with a picosecond laser source in combination with an innovative beam shaping setup from the point of view of an analysis to explore the formation of structured surfaces and their wetting behavior with cooling lubricants.

关键词： Laser structuring cutting tool DLIP Surface modification tungsten carbide

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