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Improvement of Charpy impact toughness by using an AC magnet backing system for laser hybrid welding of thick S690QL steels

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Procedia CIRP 2022年 111卷 462-465页

作者： Ömer Üstündag Nasim Bakir Andrey Gumenyuk Michael Rethmeier Bundesanstalt für Materialforschung und -prüfung (BAM) Unter den Eichen 87 12205 Berlin Germany Fraunhofer Institute for Production Systems and Design Technology Pascalstraße 8-9 10587 Berlin Germany Institute of Machine Tools and Factory Management Technische Universität Berlin Pascalstraße 8-9 10587 Berlin Germany

The study deals with the influence of the heat input and the resulting cooling times on the microstructure and Charpy impact toughness of single-pass laser hybrid welded 20-mm thick high-strength steel S690QL. The main focus is on the change of the mechanical properties over the entire seam thickness. The cooling times were measured in-situ using a pyrometer and an optical fibre in three different depths of the seam where Charpy impact test specimens were also later taken. Thereby, three different heat inputs from 1.3 kJ/mm to 2 kJ/mm were investigated. Despite the observed decreased values of both t 8/5 -cooling time and the Charpy impact toughness in the root part of the seam, the required impact toughness of 38 J/cm 2 could be reached in dependance on applied heat input, especially at the heat input of 1.6 kJ/mm.

关键词： laser hybrid welding AC magnet backing Charpy impact toughness high-strength steel S690QL

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Energy efficiency measures for metal forming using hydraulic and mechanical presses

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AIP Conference Proceedings 2024年第1期2989卷

作者： Mandy Preuß Gregor Thiele Jörg Krüger Ökotec Energiemanagement GmbH Torgauer Straße 12 Berlin Germany Fraunhofer IPK Institute for Production Systems and Design Technology Pascalstraße 8-9 10587 Berlin Germany Technical University of Berlin Institute for Machine Tools and Factory Management Pascalstraße 8-9 10587 Berlin Germany

In conventional hydraulic presses only around 13 percent of the energy supplied is converted into the plastic forming of the metal. Mechanical presses achieve an overall efficiency of 13 to 30 percent. A variety of approaches aspire efficiency improvements by tuning process parameters. For the operation engineers it is a crucial task to find measures which are both technical suitable and economical promising. This paper summarizes popular tuning parameters and presents the assessment by seven experts who participated in semi-structured interviews. For hydraulic presses, the most recommend tuning parameter to be adjusted is the pressing force. For mechanical presses the continuous stroke operation is the most popular measure.

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Process data based Anomaly detection in distributed energy generation using Neural Networks

Process data based Anomaly detection in distributed energy g...

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International Conference on Control, Automation and Diagnosis (ICCAD)

作者： Max Klein Gregor Thiele Adalbert Fono Niloufar Khorsandi David Schade Jörg Krüger Fraunhofer Institute for Production Systems and Design Technology IPK Berlin Germany AUCOTEAM GmbH Berlin Germany Institute for Machine Tools and Factory Management Technical University of Berlin Berlin Germany

ISBN: (数字)9781728169996

ISBN: (纸本)9781728170008

The increasing share of renewable energies in the total energy supply includes a growing number of small, decentralized energy generation which also provides control energy. These decentralized stations are usually combined to a virtual power plant which takes over the monitoring and control of the individual participants via an Internet connection. This high degree of automation and the large number of frequently changing subscribers creates new challenges in terms of detecting anomalies. Quickly adaptable, variable and reliable methods of anomaly detection are required. This paper compares two approaches using Neural Networks (NN) with respect to their ability to detect anomalous behavior in real process data of a combined heat and power plant. In order to include process dynamics, one approach includes specifically engineered features, while the other approach uses Long-Short-Term-Memory (LSTM). Both approaches are able to detect rudimentary anomalies. For more demanding anomalies, the respective strengths and weaknesses of the two approaches become apparent.

关键词： Power generation Artificial neural networks Computer architecture Monitoring Anomaly detection Generators Time series analysis

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Automated continuous learn and improvement process of energy efficiency in manufacturing

Automated continuous learn and improvement process of energy...

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Annual Conference of Industrial Electronics Society

作者： Alperen Can Jessica Fisch Philipp Stephan Gregor Thiele Jörg Krüger Mercedes-Benz AG Berlin Germany Fraunhofer Institute for Production Systems and Design Technology IPK Berlin Germany Industrial Automation Technology Group Technische Universität Berlin Berlin Germany

ISBN: (数字)9781728154145

ISBN: (纸本)9781728154152

Optimizing the energy efficiency of machine tools automatically is promising. There are several metrics to be considered when it comes to automated optimization approaches in serial production which are especially quality, technical availability, and cycle time. These are not supposed to be impaired whereas they are indicated as a central obstacle. The measurements and the machine data show the actions happening in the machine which also leads to the data-driven traceability of machine states. This article presents a method to formulate the necessary expert knowledge to optimize the energy efficiency of a machine tool and is basically done by a decision tree which leads to a set of rules which will be explained in this article. This set of rules coordinate an optimization algorithm, which technically manipulates selected variables under the given rules. The development and is a result of a research which was done at the serial production of camshafts at the MB plant in Berlin.

关键词： Optimization Machine tools production systems Monitoring Process control Tools Data analysis

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Die-sinking EDM of a SiC-boride-composite 19

Die-sinking EDM of a SiC-boride-composite

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19th International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2019

作者： Uhlmann, E. Polte, J. Jahnke, C. Wolf, C.-S. Degenhardt, U. Fraunhofer Institute for Production Systems and Design Technology IPK Germany Institute for Machine Tools Factory Management IWF Technische Universität Berlin Germany FCT Ingenieurkeramik GmbH Frankenblick Germany

ISBN: (纸本)9780995775145

Silicon carbide-based composites are highly demanded for industrial applications, like heat exchangers in corrosive environments. In consequence of the mechanical properties like high hardness H and brittleness, cutting processes are still challenging. An opportunity for processing difficult-to-cut materials with sufficient electrical conductivity σ is electrical discharge machining (EDM). In order to develop suitable machining technologies, known parameters for common material combinations can serve as a starting point. Hence, standard technologies from the database of a commercial die-sinking EDM machine tool were applied for machining a silicon carbide-boride-composite. The material removal rate QW and the arithmetical mean deviation Ra for finishing and roughing operations are observed. The formation of cracks and the extend of the typical deposition layer formed at the surface of the workpiece is analysed through scanning electron microscopy. While the material removal rate QW is increasing with higher discharge energies W in this investigation, the arithmetical mean deviation Ra is not dependent on this property. Furthermore, spalling is identified as main material removal mechanism occurring in this process. Overall, the machinability of silicon carbide-boride composites with EDM, applying commercial available parameter technologies, is successfully demonstrated. © 2019 European Society for Precision Engineering and Nanotechnology, Conference Proceedings - 19th International Conference and Exhibition, EUSPEN 2019. All rights reserved.

关键词： Scanning electron microscopy

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Registration of pre- and postoperative surface scans for pediatric neurosurgery

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Current Directions in Biomedical Engineering 2018年第1期4卷 657-660页

作者： Katanacho, Manuel Lack, John-Certus Fehlhaber, Felix Krüger, Jörg Fraunhofer Institute Production Systems and Design Technology IPK Pascalstrasse 8 - 9 Berlin Germany

A software for automatic registration and differential visualization of pre- and postoperative surface scans for use in pediatric neurosurgery is developed and implemented. The core operations of the registration include an automatic head extraction, a rough registration by aligning the main axes, a depth map-based registration for robust determination and registration of feature points in the facial area, and a fine registration. A graphical user interface is implemented for the difference visualization and program control. © 2018 Manuel Katanacho et al.

关键词： Graphical user interfaces

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Result quality evaluation of Directed Energy Deposition Additive Manufacturing simulations with progressive simplification of transient heat-source motion

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Procedia CIRP 2022年 111卷 277-281页

作者： M. Biegler B.A.M. Elsner I. Neubauer J. Lemke M. Rethmeier Fraunhofer Institute of Production Systems and Design Engineering (IPK) Pascalstrasse 8-9 10587 Berlin Simufact Engineering GmbH Tempowerkring 19 21079 Hamburg Germany Institut für Werkzeugmaschinen und Fabrikbetrieb IWF Technische Universität Berlin Straße des 17. Juni 135 10623 Berlin Germany Bundesanstalt für Materialforschung und -prüfung (BAM) Unter den Eichen 87 12205 Berlin Germany

Directed Energy Deposition (DED) additive manufacturing has recently been adopted in the industry for the build-up of structural components with weld lengths up to kilometers. As with all welding processes, DED suffers from thermal distortion, causing loss of dimensional accuracy and risk of cracking. Currently, process optimization with objective to minimize distortion requires expensive experimental trial-and-error. With numerical simulation of the DED process, this distortion compensation can be performed virtually, significantly reducing experimental trials. Although such approaches are generally available, their widespread adoption is currently being hampered by long computational times for large builds. This work presents a novel approach to reduce the calculation time by a simplification of the transient heat-source motion. This approach is assessed in terms of result accuracy for an industrial-scale component by progressively reducing the resolution of the heat-source motion. Calculation times as well as distortions in comparison to experimental trials are investigated.

关键词： DED A FEM FEA finite-element analysis calculation time computational time dimensional accuracy distortion

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Environmental and technical evaluation of additive manufacturing: Enabling process chain perspective by energy value stream mapping

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Procedia CIRP 2022年 105卷 440-445页

作者： Mathias Wiese Christopher Rogall Nadja Henningsen Christoph Herrmann Sebastian Thiede Polymer Additive Manufacturing Center AUDI AG Auto-Union-Straße 1 Ingolstadt 85045 Germany Chair of Sustainable Manufacturing and Life Cycle Engineering Institute of Machine Tools and Production Technology Technische Universität Braunschweig Langer Kamp 19b Braunschweig 38106 Germany Fraunhofer Institute for Surface Engineering and Thin Films (IST) Bienroder Weg 54 E Braunschweig 38108 Germany Manufacturing Systems Faculty of Engineering Technology Department of Design Production & Management University of Twente De Horst 2 Building 20 Enschede 7522 LW The Netherlands

Additive manufacturing (AM) currently evolves from a prototyping process to an alternative manufacturing process for end-use parts, advancing into fabrication of low to medium product volumes. Moreover, increasing awareness of environmental impacts of manufacturing lead to the necessity of holistic evaluation among traditional evaluation criteria in the technical and economic domains. However, existing evaluation approaches seldom consider a complete AM process chain and are lacking a production-oriented notation which enables comparability across technologies and support in identification of improvement potentials on technical and environmental level. To address this gap, this paper highlights the way from structured data acquisition to setup of an energy value stream map (EVSM) for AM process chains in end-use part production, augmenting methods of lean manufacturing by the energy dimension. Consequently, it contributes to a holistic and transparent process chain perspective to assess AM as a manufacturing alternative. The proposed methodology is applied to a case study covering two different process chains, a first based on powder bed fusion via Multi-jet Fusion (MJF) and a second utilizing vat-photopolymerization via Continuous Liquid Interphase Printing (CLIP). While the MJF process chain’s energetical hot spot is situated in the printing process itself, the hot spot for CLIP is found in thermal post-processing, exceeding the comparably efficient printing process by magnitudes and ultimately resulting in higher energy intensity per part compared to the MJF process chain. These results highlight the necessity of a holistic evaluation method for complete AM-based process chains and their influence on the product properties. Insights may help engineers, designers and decision makers in pre-selection of suitable manufacturing strategies with a more complete view on AM process chains.

关键词： Additive manufacturing rapid manufacturing process chains value stream mapping sustainable manufacturing decision support

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Dry-ED milling of micro-scale contours with high-speed rotating tungsten tube electrodes

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Procedia CIRP 2020年 95卷 533-538页

作者： E. Uhlmann I. Perfilov S. Yabroudi R. Mevert M. Polte Institute for Machine Tools and Factory Management IWF Technische Universität Berlin Pascalstr. 8-9 Berlin 10587 Germany Fraunhofer Institute for Production Systems and Design Technology IPK Pascalstr. 8-9 Berlin 10587 Germany

This paper presents machining results for dry-ED milling of micro-scale contours by use of a new machine tool, including a relaxation generator, designed for dry-EDM. To implement the dry-ED milling process tungsten tube electrodes were used. The gas is injected through the tubular tool electrode under high pressure. Additionally, a high-speed EDM spindle was used to overcome process instabilities and increase the material removal rate due to better flushing conditions. Further, fluid simulations of the flushing conditions are presented in this paper. It is found that the use of gaseous dielectrics enables much better machining results in terms of shape accuracy and tool wear. The simulations provide new insights in the flushing conditions when using gaseous dielectrics. The calculated fluid flow pattern shows a great agreement with the observed depositions of reattached molten material on the tool and workpiece surface. The results presented as well as the hardware introduced enable the industrial application of dry-EDM for the first time.

关键词： EDM Dry-EDM ED milling CFD flushing

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Uncertainty Quantification in Deep Residual Neural Networks

arXiv

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arXiv 2020年

作者： Wandzik, Lukasz Garcia, Raul Vicente Krüger, Jörg Fraunhofer Institute for Production Systems and Design Technology Pascalstraße 8-9 Berlin10587 Germany

Uncertainty quantification is an important and challenging problem in deep learning. Previous methods rely on dropout layers which are not present in modern deep architectures or batch normalization which is sensitive to batch sizes. In this work, we address the problem of uncertainty quantification in deep residual networks by using a regularization technique called stochastic depth. We show that training residual networks using stochastic depth can be interpreted as a variational approximation to the intractable posterior over the weights in Bayesian neural networks. We demonstrate that by sampling from a distribution of residual networks with varying depth and shared weights, meaningful uncertainty estimates can be obtained. Moreover, compared to the original formulation of residual networks, our method produces well-calibrated softmax probabilities with only minor changes to the network’s structure. We evaluate our approach on popular computer vision datasets and measure the quality of uncertainty estimates. We also test the robustness to domain shift and show that our method is able to express higher predictive uncertainty on out-of-distribution samples. Finally, we demonstrate how the proposed approach could be used to obtain uncertainty estimates in facial verification applications. Copyright © 2020, The Authors. All rights reserved.

关键词： Uncertainty analysis

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