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Iberian Robotics Conference (ROBOT)

作者： Christian Schroder Marco Schumann Rico Loser Philipp Klimant Martin Dix Fraunhofer Institute for Machine Tools and Forming Technology IWU Chemnitz Germany Professorship Virtual Technologies Hochschule Mittweida - University of Applied Sciences Mittweida Germany Institute for Machine Tools and Production Processes Chemnitz University of Technology Chemnitz Germany

ISBN: (数字)9798350376364

ISBN: (纸本)9798350376371

The European Union has committed to achieving the 1.5-degree Celsius limit set by the Paris Climate Agreement, emphasizing the necessity for substantial energy savings across various sectors, particularly in industry. This ambitious goal requires a delicate balance between reducing energy consumption and maintaining economic strength. Concurrently, there is a noticeable shift from mass production to mass customization, driven by the need for more flexible and adaptable manufacturing processes. Cognitive robotics emerges as a pivotal technology in this context, offering enhanced capabilities for flexible production lines. One significant advantage is the ability to assemble moving parts which optimizes cycle times and therefore contributes to energy savings. This paper presents a novel approach to object tracking using NC robot-based position control, demonstrating its potential to support the industry's transition towards more sustainable and efficient manufacturing practices. The image processing algorithm, which consists of a fused methodology merging an iterative 2D image registration and stereo vision-based point cloud registration, demonstrates the ability to track an object with a mean L2-error of 3.5 mm in a dynamic environment.

关键词： Industries Point cloud compression Service robots Heuristic algorithms Energy conservation Position control Production Visual servoing Object tracking Meteorology

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Novel method for manufacturing herringbone gears by power skiving

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Procedia CIRP 2022年 112卷 310-315页

作者： Ruben Bauer Martin Dix Fraunhofer Institute for Machine Tools and Forming Technology IWU Reichenainer Str. 88 09126 Chemnitz Germany

Due to the symmetrical flank configuration, herringbone gears have no resulting axial forces and a smaller tooth width than helical gears. Because of existing manufacturing limitations, currently only double helical gears with wide center space or assembled herringbone gears are applied. In the present work, a novel machining method for herringbone gears by power skiving is presented. For this purpose, tool and technology are designed using a mathematical process model and tested subsequently. It is shown that the process can produce the required geometry with significant improvements on productivity and accuracy. Additionally, the unused center area can be eliminated.

关键词： herringbone gears power skiving gear machining process model planetary gears

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Approach to a GPT-based Early Detection Tool to Evaluate Heterogeneous Data Sources and Identify Reconfiguration Needs of SMEs in the Production Sector

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Procedia CIRP 2024年 130卷 631-636页

作者： Adrian Jacob Anas Ben Achour Uwe Teicher Steffen Ihlenfeldt Fraunhofer Institute for Machine Tools and Forming Technology IWU Pforzheimer Str. 7a 01189 Dresden Germany TU Dresden Institute of Mechatronic Engineering Helmholtzstr. 7a 01062 Dresden Germany

In the face of a rapidly evolving commercial ecosystem, small and medium-sized enterprises (SMEs) must ensure their process chains are capable of swift reconfiguration to mitigate disruptions from supply chain volatility, regulatory changes, and demand shifts. This study addresses the need for reconfiguration in the context of data-driven opportunities for early identification of reconfiguration needs in SMEs, with a focus on the production sector. We identify a variety of diverse and heterogeneous data sources that are critical for tracking these disruptions, such as public news, economic reports, market analyses, legal documents, and internal corporate records. To make use of these data streams, we propose an innovative early detection tool that employs advanced machine learning techniques and private, locally operated Generative Pretrained Transformers (GPTs). This system is intended to process and analyze the various data formats that SMEs encounter including HTML, PDF and plain text as well as quantitative data. By combining public and company internal data while addressing privacy concerns, the tool aims to provide SMEs with a comprehensive tracking of their commercial environments. The tool also addresses the challenges posed by the limited availability of large datasets within SMEs, which are typically required for effective use of machine learning techniques, allowing for effective operation with smaller datasets. As these technologies continue to advance, their impact across various industries, including legal, manufacturing, and supply chain management, is set to expand significantly. The proposed tool offers SMEs enhanced decision-making, compliance assurance, and the ability to proactively adapt to the unpredictable global business landscape.

关键词： Early Detection Decision support Reconfiguration machine Learning GPT

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Silver-integrated EDM processing of TiAl6V4 implant material has antibacterial capacity while optimizing osseointegration

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Bioactive Materials 2024年第1期31卷 497-508页

作者： Hilmar Büssemaker Ann-Kathrin Meinshausen Viet Duc Bui Joachim Döring Vadym Voropai Adrian Buchholz Andreas J.Mueller Karsten Harnisch André Martin Thomas Berger Andreas Schubert Jessica Bertrand Department of Orthopaedic Surgery Otto-von-Guericke University MagdeburgGermany Professorship Micromanufacturing Technology Chemnitz University of TechnologyChemnitzGermany Institute of Molecular and Clinical Immunology Otto-von-Guericke University MagdeburgGermany Health Campus Immunology Infectiology and InflammationOtto-von-Guericke University MagdeburgMagdeburgGermany Institute of Materials and Joining Technology Otto-von-Guericke UniversityMagdeburgGermany Fraunhofer Institute for Machine Tools and Forming Technology ChemnitzGermany

Periprosthetic joint infections(PJI)are a common reason for orthopedic revision *** has been shown that the silver surface modification of a titanium alloy(Ti-6Al-4V)by PMEDM(powder mixed electrical discharge machining)exhibits an antibacterial effect on Staphylococcus *** the thickness of the silver-modified surface influences the adhesion and proliferation of bacteria as well as the ossification processes and in-vivo antibacterial capacity has not been investigated ***,the aim of this work is to investigate the antibacterial effect as well as the in vitro ossification process depending on the thickness of PMEDM silver modified *** attachment of *** on the PMEDM modified surfaces was significantly lower than on comparative control samples,independently of the tested surface *** proliferation,however,was not affected by the silver content in the surface *** observed a long-term effect of antibacterial capacity in vitro,as well as in *** induction of ROS,as indicator for oxidative stress,was observed in the bacteria,but not in osteoblast-like *** influence on the in vitro osteoblast function was observed,whereas osteoclast formation was drastically reduced on the silver *** changes in cell death,the metabolic activity and oxidative stress was measured in *** show that already small amounts of silver exhibit a significant antibacterial capacity while not influencing the osteoblast ***,PMEDM using silver nano-powder admixed to the dielectric represents a promising technology to shape and concurrently modify implant surfaces to reduce infections while at the same time optimizing bone ingrowth of endoprosthesis.

关键词： alloy silver powder

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Design and Damping Characterization of Sandwich Composite Made of Particle-Filled Hollow Spheres and Steel Sheets

SSRN

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SSRN 2024年

作者： Zhou, Xin Penter, Lars Jehring, Ulrike Göhler, Hartmut Weißgärber, Thomas Ihlenfeldt, Steffen Chair of Machine Tools Development and Adaptive Control Institute of Mechatronic Engineering Technische Universität Dresden Germany Fraunhofer Institute for Machine Tools and Forming Technology IWU Germany Fraunhofer Institute for Manufacturing Technology and Advanced Materials IFAM Branch Lab Dresden Germany

Sandwich composites of particle-filled hollow sphere structures (PHSS) and steel plates offer outstanding lightweight and damping properties, making them ideal for high-speed machine tool components under dynamic loads. Previous research has focused on single particle-filled hollow sphere (PHS) and small-sized PHSS, leaving gap in understanding of the behavior of PHSS/steel sandwich composites. As a result, this material cannot yet be used in the design of machine tools. In this study, a test rig was developed, a design of experiments approach and response surface analysis were used to investigate the effect of design parameters (shell and core thickness), and particle parameters (filling ratio and particle size) on the damping performance of PHSS/steel sandwich. The experimental results indicate that the design parameters have a more significant influence on damping, so they should be given priority in the design of PHSS/steel sandwiches. Secondly, the correlation between design and particle parameters substantially affects the damping performance of the sandwich. Minimizing particle size, increasing filling ratio, thinning the face layer, and thickening the core layer significantly increase structural *** address the manufacturing tolerances of the cellular structure, this study develops a finite element (FE) model-based optimization approach that accurately determines the material parameters of PHSS. These parameters were used in a FE-model of PHSS/steel composite using identified contact parameters by minimizing the difference of measurement and simulation. It shows that the homogenized material model and linear model using global damping parameters accurately replicates the dynamic properties of PHSS/steel sandwich composite in low vibration modes. © 2024, The Authors. All rights reserved.

关键词： Damping

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A New Paradigm in Surface Reconstruction: LTP Features from Surface Images for Inverse Process Modeling

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Procedia CIRP 2025年 134卷 975-980页

作者： Mei Yun Liu Thomas Wiener Martin Dix Professorship Production Systems and Processes Chemnitz University of Technology Straße der Nationen 62 09111 Chemnitz Germany Fraunhofer Institute for Machine Tools and Forming Technology IWU Reichenhainer Str. 88 09126 Chemnitz Germany

This study explores the adaptation of Local Ternary Patterns (LTP) for surface reconstruction, extending its use beyond traditional texture analysis. A systematic methodology, including patch optimization, parameter optimization, and feature selection, is proposed to extract surface-relevant features from images. Applied to spark-eroded surfaces, LTP enables differentiation of surface structures, with slightly reduced classification performance for surfaces with very fine or very coarse roughness. Despite this, the method demonstrates high potential for inverse process modeling, offering a cost-effective alternative for correlating manufacturing parameters with surface characteristics, contributing to improved process optimization and quality control in precision manufacturing.

关键词： Inverse Process Model Local Ternary Patterns (LTP) Surface Reconstruction Electrical discharge machining (EDM)

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UV-Imprint of micro-textured polymer films for biomedical disposables 22

UV-Imprint of micro-textured polymer films for biomedical di...

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22nd International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2022

作者： Gärtner, Eric Edelmann, Jan Hackl, Claudia Roussak, Liudmila Tomasova, Lea Guttenberg, Zeno Gnüchtel, Sebastian Fraunhofer Institute for Machine Tools and Forming Technology IWU Chemnitz Germany Leipzig Germany SensLab GmbH Leipzig Germany Ibidi GmbH Gräfelfing Germany WESKO GmbH Stollberg Germany

ISBN: (纸本)9781998999118

In the life science sector, increasing demands on the reproducibility and accuracy of lab-on-chip systems require new manufacturing technologies for the production of polymer films with multifunctional surfaces. A mass-production capable and cost-effective way to pattern microfluidic films is the manufacturing process of UV injection molding. Therefore, the aim of the project is to develop microstructured polymer films with multifunctional surface properties by means of an injection molding UV plate-to-plate (P2P) replication process. For this purpose, a special film injection molding system was developed that allows filling with different formulations, curing by UV light and molding of the required microstructures. In respect to the application of the microstructured polyacrylate films in cell-based assays as well as biosensor disposables, microstructures of various geometries were designed and produced in the P2P process. In addition, cell tests were performed in this study in order to evaluate the biocompatibility and optical quality of the substrates, and to verify the functionality of the microstructures. Here, we show that the structured polyacrylate foil is a suitable substrate that can be implemented in plastic microfluidic chips for cell-based assays and biosensor disposables. © European Society for Precision Engineering and Nanotechnology, Conference Proceedings - 22nd International Conference and Exhibition, EUSPEN 2022. All rights reserved.

关键词： Polymer films

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Development of general data-based process models for self-pierce riveting 24

Development of general data-based process models for self-pi...

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24th International ESAFORM Conference on Material forming, ESAFORM 2021

作者： Jäckel, Mathias Falk, Tobias Kropp, Thomas Drossel, Welf-Guntram Fraunhofer Institute for Machine Tools and Forming Technology IWU Nöthnitzer Straße 44 Dresden01187 Germany

ISBN: (纸本)9782870193020

The determination of ideal process parameters for mechanical joining processes such as self-pierce riveting currently requires a comprehensive understanding of the process, the availability of the materials to be joined and the corresponding system technology. General process models can simplify the use of these joining technologies, accelerate development cycles and thereby reduce the effort for implementation into production. In this paper, the development of general data-based process models for the mechanical joining method self-pierce riveting with semi-tubular rivet is described. Extensive experimental and numerical investigations with more than 2300 joint combinations for steel and aluminum sheets with tensile strengths between 240 - 1020 MPa were generated for the building of the models. Based on these results, different meta-models are fused into general data-based process models for the self-pierce riveting process in order to show the general relationships between material properties, process parameters and joining results. The paper discusses the acquisition of the experimental and numerical data, the statistical methods for evaluation and the application of the data-based process models. © ESAFORM 2021 - 24th Inter. Conf. on Mat. forming. All rights reserved.

关键词： Riveting

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Enhancing Tool Wear Segmentation with LoRA-SAM and Point Prompts

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Procedia CIRP 2025年 134卷 705-710页

作者： Zongshuo Li Ding Huo Markus Meurer Miguel Panesso Welf-Guntram Drossel Thomas Bergs Manufacturing Technology Institute (MTI) of RWTH Aachen University Campus-Boulevard 30 52074 Aachen Germany Fraunhofer Institute for Machine Tools and Forming Technology IWU Nöthnitzer Str. 44 01187 Dresden Germany Fraunhofer Institute for Production Technology IPT Steinbachstr. 17 52074 Aachen Germany

Automated optical measurement of cutting tools offers a rapid and direct approach to monitoring tool wear. While the Segment Anything Model (SAM) exhibits strong zero-shot generalization capabilities in typical scenarios due to its powerful image encoder and prompt engineering, it underperforms in tool wear segmentation because of its lack of domain-specific knowledge. In this study, an image dataset containing various tools with different prompts was initially established, and SAM was fine-tuned using Low-Rank Adaptation (LoRA) and Mixture-of-Expert (MoE) LoRA to incorporate domain-specific knowledge of tool wear. The results consistently show that both LoRA-SAM and MoE-LoRA-SAM significantly outperform the original SAM in tool wear segmentation with over 55% improvement. Additionally, using a combination of three prompt points is sufficient for accurate tool wear segmentation. This finding highlights the potential applicability of SAM in industrial scenarios.

关键词： Tool wear Deep learning Image segmentation SAM

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Enhancing cooling tower performance with condition monitoring and machine learning based drift detection 15

Enhancing cooling tower performance with condition monitorin...

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15th CIRP Conference on Intelligent Computation in Manufacturing Engineering, ICME 2021

作者： Nahvi, Sina Polster, Stefan Melzer, Sebastian Stoll, Anke Münnich, Marc Mannstadt, Stefan Klimant, Philipp Fraunhofer Institute for Machine Tools and Forming Technology IWU Reichenhainer Straße 88 Chemnitz09126 Germany Multi Kühlsysteme GmbH Zschorlauer Straße 56 Aue08280 Germany

Process cooling is crucial to many manufacturing processes. To monitor the performance of a cooling tower, it was equipped with extensive sensors for internal and environmental data acquisition. The aim is to improve reactive and predictive maintenance by estimating the actual condition as well as predicting defective behavior of the cooling tower. We designed a method, which derives the degree of defect from data of the non-defective cooling tower. A concept drift detection approach was implemented, which monitors the model estimation error of a multilayer perceptron model. Increasing model estimation error indicates changing system behavior and increasing risk of failure. © 2022 The Author(s).

关键词： Condition monitoring

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