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19th Global Conference on Sustainable Manufacturing, GCSM 2023

作者： Münnich, Marc Schönfelder, Annabell 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)9783031774287

Sustainability and digitalization are of high importance for companies to stay competitive and cope with market requirements from internal and external stakeholders. Especially the current changes in reporting standards and frameworks increase pressure to quickly adapt internal processes and acquire the relevant data. In this context, Industry 4.0 (I4.0) is discussed to enable companies to also foster sustainability. But many small and medium sized enterprises (SME) lack of experience and capacity and need support from experienced partners to develop suitable strategies and implement technologies. Appropriate support comprises general guidance through these domains and an evaluation of current and desired state of expertise to choose suitable actions. Maturity models (MM) are well-established to initiate and support the transformation of corporate structures. There are many models available that support digital and sustainable transformation, but almost no models are available that include both dimensions what results in decoupled developments in these domains. Hence, this contribution introduces a combined model for both domains and systematically describes the extension of an existing digitalization MM (DMM) that also considers rebound effects. The MM is tested within an industrial context use case. The results are evaluated and discussed for further development of the model and workflow. © The Author(s) 2025.

关键词： Sustainable development goals

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Integrating Hybrid Physics-Data Approaches for Enhanced Cutting Force Modeling in Digital Twins of Helical End Mills 20

Integrating Hybrid Physics-Data Approaches for Enhanced Cutt...

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20th CIRP Conference on Modeling of Machining Operations in Mons, CIRP CMMO 2025

作者： Jing, Yuan Gong, Guanchen Hänel, Albrecht Ihlenfeldt, Steffen Fraunhofer Insitute for Machine Tools and Forming Technology IWU Chemnitz Germany Chair of Machine Tools Development and Adaptive Controls Institute Fo Mechatronic Engineering Technische Universität Dresden Dresden Germany

Industry 4.0 has significantly improved data efficiency by leveraging key technologies such as the Internet of Things and machine Learning. Among these key technologies, digital twins stand out by offering a promising approach to intelligently utilize this data. In the virtual representation of a physical asset, data reflects the conditions of the physical entity, while models simulate and predict its behavior. In this paper, a hybrid cutting force model is proposed for digital twins of helical end mills, focusing on cutting force analysis during the utilization phase of the machining process. This model combines a fairly mature physical process modelling approach with a data-driven method, specifically a neural network trained on real process data, to address the limitations inherent in their respective applications. The physics-based model provides meaningful constraints on the neural network's training, ensuring reliable cutting force prediction, particularly in scenarios with limited process data availability. The cutter's profile, generated by the geometric model, and the cutter-workpiece engagement maps, derived from the virtual machining model, together serve as inputs for the hybrid cutting force model. © 2025 The Author(s).

关键词： Machining centers

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Structure and Validation of a Kinematic Surface Simulation Model for the ultrashort-pulse Direct-Laser-Writing Process 20

Structure and Validation of a Kinematic Surface Simulation M...

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20th CIRP Conference on Modeling of Machining Operations in Mons, CIRP CMMO 2025

作者： Wieland, Fabian Gärtner, Eric Wieland, Sebastian Fraunhofer Institute for Machine Tools and Forming Technology IWU Department Functional Surfaces and Micromanufacturing Reichenhainer Str. 88 Chemnitz09126 Germany

This paper presents the development and validation of a kinematic surface simulation model for the prediction of ultrashort-pulsed laser structured surfaces. The simulation is based on an existing kinematic simulation model for short-pulsed laser structuring and utilizes the stepwise Boolean intersection of a machined and digitized single point ablation with the workpiece to reproduce the microstructuring process. The existing short-pulse simulation model was extended by newly integrated description models to allow a more detailed representation of within the process changing influences, e.g. the surface fine-structure to enable a multi-layer processing. In addition, a reorganization of the simulation algorithm resulted in a general improvement of the run time and a resolution-independence. Based on the kinematic simulation principle, the manufacturing process for a wide range of material-machine combinations in the field of laser structuring can be described. The model enables a time-efficient, nanometer-resolved prediction of representative surfaces with a size of up to several square millimeters. Furthermore, complex influences such as material- and temperature-related properties do not need to be considered separately, as they are taken into account by the machined and digitized single point ablation. Compared to artificial intelligence approaches and numerical or multiphysical simulations, the need for preliminary studies is very low. Depending on the chosen laser machining parameters the simulation can reproduce the surface textures macro- and microstructure. © 2025 Elsevier B.V.. All rights reserved.

关键词： Kinematics

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Tool-holder integrated printed piezoceramic sensors for process state classification and tool-wear progress evaluation in turning 20

Tool-holder integrated printed piezoceramic sensors for proc...

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20th CIRP Conference on Modeling of Machining Operations in Mons, CIRP CMMO 2025

作者： Panesso, Miguel Berthold, Jan Hamm, Lucas Li, Zongshuo Drossel, Welf-Guntram Bergs, Thomas Fraunhofer Institute for Machine Tools and Forming Technology Nöthnitzer Str. 44 Dresden01187 Germany RWTH Aachen University Campus-Boulevard 30 Aachen52074 Germany

Tool condition monitoring strategies in turning processes, using multiple sensor sources to measure dynamic quantities (e.g., force, acoustic emissions, acceleration), has gained significant attention in conjunction with machine learning methods. As a novel approach, the introduction of printed piezoceramic thick films in machine tools allows the customization of sensor shape and placement, optimized to fit the tool holder's geometry and process boundary conditions. This work proposes integration concepts using two configurations of printed piezoceramic sensors. This includes the use of a finite element simulation to estimate the generated electric charge from sensors on three locations on the tool holder, induced by transient mechanical loading. The design is validated under controlled mechanical loading and tested across various cutting conditions and tool-wear states. Signal information content from each sensor location, relative to different machining conditions, is assessed through recursive feature elimination and validated using dimensionality reduction. Finally, tool-wear progress is evaluated using the selected features. © 2025 The Author(s).

关键词： Thick films

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Topology optimization of nonlinear elastomer engine mounts considering the transfer behavior

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Forschung im Ingenieurwesen 2025年第1期89卷 1-10页

作者： Bahr, S. Jacobs, G. Höpfner, G. Hensel, E. Troge, J. Rapp, T. Institute for Machine Elements and Systems Engineering RWTH Aachen Aachen Germany Institute for Machine Tools and Forming Technology Fraunhofer Dresden Germany

Increasing global competition among electric vehicle manufacturers has elevated the Noise, Vibration, and Harshness (NVH) properties of drivetrains to a key quality feature. Unfavorable NVH properties occur when the drivetrain’s dynamic excitation forces excite modes of the sound-transmitting components at the respective eigenfrequencies. An established strategy to avoid this unwanted NVH behavior is topology optimization (TO), as it can shift unwanted modes of the drivetrain out of the excitation frequency range through geometrical adaptations using finite-element (FE) simulation. Another way to significantly influence unwanted NVH behavior in electric vehicle drivetrains are elastomer engine mounts which are employed to isolate the engine’s vibrations from the surrounding system and to dissipate vibrational energy. However, the effectiveness of these functionalities is limited in frequency ranges of local elastomer modes. Despite TO being well-established, challenges are given in shifting elastomer modes due to the complex material behavior. Firstly, the material’s softness results in an uncontrollably high density of local mount modes for TO, which presents a challenge in developing engine mounts without modes in the drivetrain’s excitation range, especially for electrified engines. Secondly, the elastomer’s nonlinear material impedes calculating the component’s modes with a linearized material approach. The goal of this contribution therefore is to develop a method that considers the complex material behavior of engine mounts in a TO process. To achieve this goal, the ideal transfer behavior of the engine mount, and consequently the positioning of mount modes within the frequency range, is determined based on the sound-transmitting structure and used as an objective for the optimization process. To consider the elastomer’s nonlinear transfer behavior during optimization, material parameters for each considered frequency are applied. The

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Coupled CFD model of tool environment and workspace to determine the convective heat transfer in jet cooling of milling processes in machine tools 20

Coupled CFD model of tool environment and workspace to deter...

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20th CIRP Conference on Modeling of Machining Operations in Mons, CIRP CMMO 2025

作者： Brier, Steffen Geist, Alexander Glänzel, Janine Naumann, Christian Regel, Joachim Dix, Martin Ihlenfeldt, Steffen Chemnitz University of Technology Professorship Production Systems and Processes Reichenhainer Str. 70 Chemnitz09126 Germany Fraunhofer-Institute for Machine Tools and Forming Technology IWU Reichenhainer Str. 88 Chemnitz09126 Germany Technical University Dresden Institute for Machine Tools Development and Adaptive Controls Helmholtzstraße 10 Dresden01069 Germany

The responsible use of resources is an essential part of the manufacturing of industrial products. This includes the economical use of cooling lubricant and requires precise knowledge of the cooling mechanisms and their effect on the accuracy of the machine tool and thus the thermal error. A temporal and spatial resolution of the dynamic coolant flow near the tool and in the entire workspace in a single model would require a large simulation time. Therefore, a composite model was developed, that consists of a near-tool model and a larger surrounding workspace model. The required static near-tool cooling lubricant distribution is obtained via data discretization methods from a separate static simulation that resolves the turbulence of the cooling lubricant created by the tool rotation. The identified coolant distribution is integrated into a CFD near-tool model (with simplified tool geometry) which is coupled with a surrounding CFD workspace model. The workspace model is thus able to identify the effects of the coolant wetting on the machine surface temperature and finally, using thermo-elastic FEM simulations, on the resulting thermal error. This approach allows the composite model to simulate the entire workspace with reduced simulation effort and map the coolant-influenced heat transfer coefficients on the machine surface. © 2025 The Author(s).

关键词： Milling machines

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Integrating Hybrid Physics-Data Approaches for Enhanced Cutting Force Modeling in Digital Twins of Helical End Mills

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Procedia CIRP 2025年 133卷 358-363页

作者： Yuan Jing Guanchen Gong Albrecht Hänel Steffen Ihlenfeldt Fraunhofer Insitute for Machine Tools and Forming Technology IWU Chemnitz Germany Chair of Machine Tools Development and Adaptive Controls Institute fo Mechatronic Engineering Technische Universität Dresden Dresden Germany

Industry 4.0 has significantly improved data efficiency by leveraging key technologies such as the Internet of Things and machine Learning. Among these key technologies, digital twins stand out by offering a promising approach to intelligently utilize this data. In the virtual representation of a physical asset, data reflects the conditions of the physical entity, while models simulate and predict its behavior. In this paper, a hybrid cutting force model is proposed for digital twins of helical end mills, focusing on cutting force analysis during the utilization phase of the machining process. This model combines a fairly mature physical process modelling approach with a data-driven method, specifically a neural network trained on real process data, to address the limitations inherent in their respective applications. The physics-based model provides meaningful constraints on the neural network’s training, ensuring reliable cutting force prediction, particularly in scenarios with limited process data availability. The cutter’s profile, generated by the geometric model, and the cutter-workpiece engagement maps, derived from the virtual machining model, together serve as inputs for the hybrid cutting force model.

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Structure and Validation of a Kinematic Surface Simulation Model for the ultrashort-pulse Direct-Laser-Writing Process

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Procedia CIRP 2025年 133卷 227-232页

作者： Fabian Wieland Eric Gärtner Sebastian Wieland Fraunhofer Institute for Machine Tools and Forming Technology IWU Department Functional Surfaces and Micromanufacturing Reichenhainer Str. 88 Chemnitz 09126 Germany

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Tool-holder integrated printed piezoceramic sensors for process state classification and tool-wear progress evaluation in turning

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Procedia CIRP 2025年 133卷 382-387页

作者： Miguel Panesso Jan Berthold Lucas Hamm Zongshuo Li Welf-Guntram Drossel Thomas Bergs Fraunhofer Institute for Machine Tools and Forming Technology Nöthnitzer Str. 44 01187 Dresden Germany Manufacturing Technology Institute (MTI) of RWTH Aachen University Campus-Boulevard 30 52074 Aachen Germany

Tool condition monitoring strategies in turning processes, using multiple sensor sources to measure dynamic quantities (e.g., force, acoustic emissions, acceleration), has gained significant attention in conjunction with machine learning methods. As a novel approach, the introduction of printed piezoceramic thick films in machine tools allows the customization of sensor shape and placement, optimized to fit the tool holder’s geometry and process boundary conditions. This work proposes integration concepts using two configurations of printed piezoceramic sensors. This includes the use of a finite element simulation to estimate the generated electric charge from sensors on three locations on the tool holder, induced by transient mechanical loading. The design is validated under controlled mechanical loading and tested across various cutting conditions and tool-wear states. Signal information content from each sensor location, relative to different machining conditions, is assessed through recursive feature elimination and validated using dimensionality reduction. Finally, tool-wear progress is evaluated using the selected features.

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Characterization of the high-pressure suspension jet for efficient cutting and abrasive circularity

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CIRP Annals 2025年

作者： Morczinek, Florian Dix, Martin Wertheim, Rafael Institute for Machine Tools and Production Processes Technical University of Chemnitz Chemnitz Germany Fraunhofer Institute for Machine Tools and Forming Technology Chemnitz Germany Braude College of Engineering Karmiel Israel

To optimize the workpiece removal process and maximize the fraction of reusable abrasive particles, it is necessary to ascertain the characteristics of the high-pressure suspension jet process, including the kinetic energy of the particles in the jet. In this study, the particle velocity and the change in their size were measured and analyzed. It was found that due to breakage the average particle size decreases by up to 35 % during the acceleration process in the nozzle. The results showed that the particle size has insignificant influence on particle velocity, while the kinetic energy of an average particle decreased by up to 72 %. © 2025 The Authors

关键词： Kinetic energy

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