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International Joint Conference on Mechanics, Design Engineering and Advanced Manufacturing, JCM 2022

作者： Weisheit, Linda Wockenfuß, Wilhelm Richard Fraunhofer Institute for Machine Tools and Forming Technology IWU Nöthnitzer Straße 44 Dresden01187 Germany

ISBN: (纸本)9783031159275

Soft Robotics made of soft and compliant materials ensure systems with high inherent safety for a safe human-robot collaboration. Thereby current soft robots mostly lack the required stiffness to apply sufficient loads. To ensure inherent safety and at the same time a greater load capacity, structures with adjustable stiffness are required. In this paper, possible approaches for the realization of a switchable stiffness are analyzed and evaluated against the application background of human-oriented soft robotics, which focus mainly on high switching dynamics and high stiffness ratios. A concept for variable stiffness robotic segments based on particle and layer jamming for planar motion is shown, enabling highly dynamic switching between stiff and soft with a bending stiffness ratio K > 100. For this variable stiffness structural component, both the development steps and the characterization methodology are explained. Finally, an outlook on the design of a soft continuum robotic manipulator using three of these variable stiff segments and two tendons for an underactuated motion control of the whole structure is given. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Stiffness

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Intelligent parameter determination and quality control of an injection molding process 17

Intelligent parameter determination and quality control of a...

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17th CIRP Conference on Intelligent Computation in Manufacturing Engineering, CIRP ICME 2023

作者： Nahvi, Sina Schumann, Marco Dix, Martin Klimant, Philipp Fraunhofer Institute for Machine Tools and Forming Technology IWU Reichenhainer Straße 88 Chemnitz09126 Germany Institute for Machine Tools and Production Processes Chemnitz University of Technology Reichenhainer Str. 70 Chemnitz09126 Germany

One of the most extensively utilized techniques for material processing is injection molding, which is used to manufacture highly accurate and complex plastic items. In order to produce qualified items and ensure quality of the products, process parameter determination is crucial. We propose and compare two approaches for intelligently determining the parameters and controlling the quality within the injection molding process while aiming towards zero defects. These approaches are combinations of the process model trained using Automated machine Learning (AutoML) with optimization techniques based on Bayesian and genetic algorithms. © 2024 Elsevier B.V.. All rights reserved.

关键词： Injection molding

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Simulation-Based Improvement of Production in the Tex-Tile Industry—A Case Study 9th

Simulation-Based Improvement of Production in the Tex-Tile I...

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Production Processes and Product Evolution in the Age of Disruption - Proceedings of the 9th Changeable, Agile, Reconfigurable and Virtual Production Conference CARV2023 and the 11th World Mass Customization and Personalization Conference MCPC2023

作者： Grobis, Maxi Münnich, Marc Reinhardt, Heiner Ihlenfeldt, Steffen Fraunhofer Institute for Machine Tools and Forming Technology IWU Chemnitz Germany Institute of Mechatronic Engineering Technische Universität Dresden Dresden Germany

ISBN: (纸本)9783031348204

Due to the high volatility of market demand and an increasing individualization, traditional textile manufacturing companies are required to carry out efficient production planning and scheduling (PPS). Highly complex manufacturing operations and a heterogeneous landscape of production equipment in terms of age, technology and automation level as well as a low level of digitalization hamper transparency in PPS, even though the demands on delivery reliability, lead times and flexibility are continuously increasing. Therefore, decision-making is typically based on fragmented production data and practical knowledge of individual workers in daily production that makes overall production opaque. To overcome this, the authors conducted a detailed process analysis of a medium-sized textile manufacturer and carried out a simulation study to improve daily production routines on the shop floor. This included the analysis of the heterogeneous production data, the management of missing data and the decision to implement a discrete-event simulation model. The simulation study focused on testing isolated production strategies, identifying potential improvements in terms of organizational processes, detecting data leaks as well as designing a model for discrete-event simulation (DES). As a result, a roadmap to establish a seamlessly integrated hardware and software infrastructure was derived. This consists of a catalogue of best practices for lean production as well as an increased level of digitalization on the shop floor and considers the current state of digitalization of the company. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Textile industry

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Integration of Digitization and Sustainability Objectives in a Maturity Model-Based Strategy Development Process 18th

Integration of Digitization and Sustainability Objectives in...

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18th Global Conference on Sustainable Manufacturing, GCSM 2022

作者： Münnich, Marc Stange, Maximilian Süße, Marian Ihlenfeldt, Steffen Fraunhofer Institute for Machine Tools and Forming Technology IWU Chemnitz Germany Institute of Mechatronic Engineering Technische Universität Dresden Dresden Germany

ISBN: (纸本)9783031288388

Political, technological and economic changes force manufacturing companies to shift their strategic alignment towards green and digitized technologies. The parallel advances in those technologies raise questions regarding economic, environmental and social sustainability issues that are challenging to integrate into corporate strategy. Recently, sustainable energy supply has gained additional attention as a critical resource for production. Digital transformation is a diverse intracompany process and requires adequate strategies. Maturity models are a well-known and established approach to define strategic improvement measures. Various versions of separate maturity models to either examine the current state of digitization or sustainability have been developed and there are few models to support both dimensions adequately. Therefore, the authors propose a strategy development process, which utilizes a combined maturity model for both domains in one framework. A review on sustainability-related maturity models as well as the connection to digitization aspects is conducted. Based on this, an existing model is extended. The model is tested in a case study to compare the impact of the models’ adaptions. © 2023, The Author(s).

关键词： Sustainable development

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Investigation of alternative attention modules in transformer models for remaining useful life predictions: Addressing challenges in high-frequency time-series data 31

Investigation of alternative attention modules in transforme...

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31st CIRP Conference on Life Cycle Engineering, LCE 2024

作者： Boos, Eugen Zimmermann, Jan Wiemer, Hajo Ihlenfeldt, Steffen Technische Universität Dresden Germany Fraunhofer Institute for Machine Tools and Forming Technology Germany

Predicting the Remaining Useful Life of a machine components or systems is a pivotal technology in condition-based maintenance and essential for ensuring the reliability and safety in various production-engineering applications. The influx of extensive industrial data has notably enhanced the efficacy of data-driven Remaining Useful Life prediction models, especially deep learning models. One of the promising deep learning model architectures is the Transformer-based model with the Self-Attention mechanism at its core. However, inherent limitation arise when applying Self-Attention to high- frequency time-series data with large window sizes. Due to its high computational complexity, hardware limitations hinder the practical implementation of Transformer with Self-Attention in production-engineering applications. This study looks into the utilization of alternative Attention modules with reduced complexity, making it more applicable to high-frequency time-series data. In order to allow comparability, this study uses the well-known C-MPASS dataset for benchmarking Remaining Useful Life approaches. Although this dataset does not consist of high-frequency data, it demonstrates the usefulness of alternative Attention modules without noteworthy losses in model accuracy. © 2024 Elsevier B.V.. All rights reserved.

关键词： Forecasting

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Adhesion Reduction in Plastics Processing by means of laser-generated Microstructuring

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Procedia CIRP 2024年 125卷 130-135页

作者： Eric Gärtner Justus von Freeden Michael Schreiter Fraunhofer Institute for Machine Tools and Forming Technology IWU Reichenhainer Strasse 88 09126 Chemnitz Germany Fraunhofer Institute for Machine Tools and Forming Technology IWU Hermann-Münch-Strasse 2 38440 Wolfsburg Germany

Almost all production processes for manufacturing plastic or fiber reinforced plastic (FRP) components have in common that plastic and a steel surface are pressed together in the process. To avoid adhesion, the steel belts are coated with polytetrafluoroethylene (PTFE), ceramics or perfluoroalkoxy (PFA) during calendering, for example. However, the high temperatures of over 250 °C and the alternating mechanical load lead to damage of the coating. This results in adhesion of the coating to the product and loosening of the coating. Due to this, the surface quality of the organic sheets is reduced, and the production process is negatively affected. As the surface function can be controlled by material and surface patterns with different length scales (nm - µm), the surface topography of the belt steel was specifically modified in the roughness and microstructure level in order to reduce the adhesive interaction with the organic sheet. These microstructures were tested in extensive experiments and the results will be presented in this publication. True to the motto from nature to innovation, the micro- and nanostructured surface of the lotus leaf, which is provided with a fine substructure, was used as reference. The aim was to generate such a hierarchical structure by means of direct laser writing in order to avoid adhesions on production surfaces and to substitute the coating of steel strip surfaces. Additionally, a testing method close to the process was developed and evaluated to test the laser structured microstructures, which will also be presented.

关键词： adhesion reduction laser microstruturing surface functionalisation calendering

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Simulation of geometrical errors during application of a confocal sensor system for the measurement of large components with high aspect ratios 15

Simulation of geometrical errors during application of a con...

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15th International Conference and Exhibition on Laser Metrology, Coordinate Measuring machine and machine Tool Performance, LAMDAMAP 2023

作者： Teicher, Uwe Gollee, Christian Seidel, André Ihlenfeldt, Steffen Fraunhofer Institute for Machine Tools and Forming Technology IWU Dresden Germany Institute of Mechatronic Engineering Technische Universität Dresden Dresden Germany

ISBN: (纸本)9781998999125

Machining of large components for the aerospace industry requires, in addition to sophisticated machining strategies a targeted monitoring of the machining quality due to the enormous demands on precision. For the acquisition of the as-is geometry after single machining steps, a non-contact system based on a confocal chromatic sensor was developed, with whose help the as-is geometry can be compared with the target geometry even in deep cavities at aspect ratios up to 40. The sensor system is coupled with the standard interfaces to a machine tool and performs measuring cycles based on modified NC programs. Data acquisition is done with a control-connected EDGE system. The result of the target/as-is comparison is the basis for CAM planning for subsequent machining. In addition to the design of the measuring system and the integration into the ecosystem of the machine system, a concept to calibrate the measuring system for operation on the machine tool was developed. Based on a simulation model of the measurement system various aspects of the calibration approach were analysed. © euspen Headquarters March 2023.

关键词： Geometry

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Memory Adaptive and Spatially Specialized Model Ensembles for Industrial Anomaly Detection 27

Memory Adaptive and Spatially Specialized Model Ensembles fo...

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27th European Conference on Artificial Intelligence, ECAI 2024

作者： Wagenstetter, Marco Landerer, Niklas Thyroff, Johannes Aicher, Thomas Hellmich, Arvid Ihlenfeldt, Steffen Powertrain Production System Planning BMW Group Germany School of Computation Information and Technology Technical University of Munich Germany Institute for Machine Tools and Forming Technology Fraunhofer IWU Germany

ISBN: (纸本)9781643685489

Industrial anomaly detection models proved to be a viable solution for automating the task of visual inspection. Despite their effectiveness, the deployment of current deep learning models for anomaly detection for high-resolution images involves large memory requirements, which are unattainable in industrial deployments on edge devices. In this paper we introduce a tiling approach for a memory bank based feature embedding model to reduce the memory requirements during training and inference. Additionally, we analyze the correlations between image size, dataset size and required memory. To evaluate the detection performance of different tiling schemes, we create and apply a real industrial training and validation dataset collected in the electric motor housing production of the BMW Group. Our experiments show that depending on the tiling scheme the overall required memory can be decreased by a factor of 12 while leaving the detection performance unchanged and even increase the detection performance when the memory requirement is only halved. This venture underscores the viability of our tiling approach in real-world industrial applications but also marks a significant leap towards resolving the issue of resolution limitations in deploying advanced anomaly detection models. © 2024 The Authors.

关键词： Anomaly detection

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Split CFD-simulation approach for effective quantification of mixed convective heat transfer coefficients on complex machine tool models

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Procedia CIRP 2023年 118卷 199-204页

作者： Tharun Suresh Kumar Alexander Geist Christian Naumann Janine Glänzel Steffen Ihlenfeldt Fraunhofer Institute for Machine Tools and Forming Technology IWU Chemnitz Germany

Estimation of mixed heat transfer coefficients on complex CFD-simulation models of 5-axis machine tools/ machining centers poses a whole new set of challenges. The enclosure around the machine which protects the user from chips and machining-process is also responsible for creation of an additional environment which has coolant supply, chips and moving air due to temperature changes and oil-emulsion exhaust. This results in a highly complex CFD model which has inner and outer environments along with multiphase fluid domains. The computational effort required is extremely large. The split-simulation approach divides the simulation model into internal and external environments. The natural convection is emphasized for external environment model and forced convection for internal multiphase environment model. This division significantly reduces the computational efforts involved by neglecting uninfluential solid bodies, cavities etc. and thereby the model size. The external and internal influences are mapped separately onto natural and forced convection coefficients using neural networks, which can be used to predict the combined heat transfer coefficients for any load cases within the training boundaries. The temperature fields obtained from split-simulation model are validated with thermography and temperature sensor readings taken from the machine in the form of a use-case study.

关键词： heat transfer coeffcients CFD simulation Decoupling Genetic Algorithms

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Development of a material selection decision support system for an automotive application

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Discover Mechanical Engineering 2024年第1期3卷 1-21页

作者： Chirinda, Gibson P. Matope, Stephen Nagel, Matthias University of Stellenbosch Private Bag X1 Matieland Stellenbosch 7602 South Africa Fraunhofer Institute of Machine Tools and Forming Technology IWU Reichenhainer Straße 88 Chemnitz 09126 Germany

This study presents the development of a material selection decision support system for an automotive rooftop tent. The system uses five parameters of material cost, formability, corrosion resistance, tensile strength and hardness to optimize material choice from a list of aluminium alloy options. This was done before production via the deep drawing process can commence. The parameters were quantified using the average market prices for each alloy, product requirements obtained from the case study and the performance data that was obtained from the uniaxial tensile and hardness tests. These inputs were combined with the developed material selection framework and then programmed into a web-based decision support system for automated, data-driven material selection. The output presents the recommendation for the optimum material that balances cost-effectiveness and performance. The decision support system was successfully used to select the optimum alloy for the rooftop tent. Results show that AA1050 is the optimum material, providing weight reduction at the minimum achievable cost without compromising the product requirements for the rooftop tent. The decision support system is also scalable, and this allows it to be used with larger datasets for different products and processes in the future. © The Author(s) 2024.

关键词： Aluminium alloy Automotive industry Decision support system Deep drawing Lightweighting Material selection

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