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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： Stange, Maximilian Jäpel, Nicole Reichelt, Dirk Ihlenfeldt, Steffen Fraunhofer Institute for Machine Tools and Forming Technology IWU Chemnitz Germany Hochschule Für Technik Und Wirtschaft Dresden Dresden Germany Institute of Mechatronic Engineering Technosphere Universität Dresden Dresden Germany

ISBN: (纸本)9783031348204

Manufacturing companies are operating in an environment that is becoming steadily more challenging and uncertain. The most serious risks in developed countries increasingly concern the shortage of skilled workers, growing competition from emerging countries, and ever-shorter development cycles for products that are expected to meet a growing variety of individual customer requirements. In addition, on a macroeconomic level, labour productivity growth is declining. This is a warning sign for the overall economic outlook, which is particularly true for the European economic area. One of the reasons for this is the decreasing diffusion of innovations. A holistic approach is needed to address these challenges. One direction that has been discussed in recent years is the concept of open source hardware. This concept takes up the philosophy of open source software and aims to transfer this open and collaborative approach to physical products. The paper will present the current state of OSH, specifically focusing on its use in manufacturing companies. Based on this, opportunities and risks for the application of OSH to manufacturing companies will be derived. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Open source software

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Intelligent dressing for continuous generating grinding with convolutional neural networks and knowledge distillation

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Procedia CIRP 2024年 126卷 513-518页

作者： Martin Boesler Marco Schumann Philipp Klimant Martin Dix Fraunhofer Institute for Machine Tools and Forming Technology IWU Reichenhainer Straße 88 Chemnitz 09126 Germany Institute for Machine Tools and Production Processes Chemnitz University of Technology Reichenhainer Str. 70 09126 Chemnitz Germany

Continuous generating grinding is a highly productive and precise way to finish hardened gears. However, the dressing of the tool has a huge potential for optimization. Detecting the optimal point to stop the dressing process would save cost and reduce machine downtime. This paper provides a proof of concept of how machine learning models can achieve these goals based on acoustic emission data. Therefore, different ML-Classifiers were trained and compared. Particular emphasis was placed on the robustness of the models. In addition, the trade-off between fast and robust models was examined.

关键词： Continuous generating grinding Dressing machine learning Convolutional neural network Distillation

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Intelligent parameter determination and quality control of an injection molding process

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Procedia CIRP 2024年 126卷 721-726页

作者： Sina Nahvi Marco Schumann Martin Dix Philipp Klimant Fraunhofer Institute for Machine Tools and Forming Technology IWU Reichenhainer Straße 88 09126 Chemnitz Germany Institute for Machine Tools and Production Processes Chemnitz University of Technology Reichenhainer Str. 70 09126 Chemnitz 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.

关键词： Injection molding Process parameter determination Quality control Optimization machine Learning

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Effects of abrasive waterjet cutting on surface properties of hardened steel 16

Effects of abrasive waterjet cutting on surface properties o...

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16th CIRP Conference on Intelligent Computation in Manufacturing Engineering, CIRP ICME 2022

作者： Redžic, Nermin Kieweg, Philipp Regel, Joachim Dix, Martin Chemnitz University of Technology Institute for Machine Tools and Production Processes Reichenhainer Str. 70 Chemnitz09126 Germany Franke GmbH Obere Bahnstraße 64 Aalen73431 Germany Fraunhofer Institute for Machine Tools and Forming Technology IWU Reichenhainer Str. 88 Chemnitz09126 Germany

The importance of cutting hardened materials without influencing their structural properties makes abrasive waterjet machining a favorable choice in certain applications in comparison with other manufacturing technologies. Using this technology, faulty surface structures and errors caused by high thermal loads such as burrs, burns and cracks, can be avoided. In this paper, the results of applying the abrasive waterjet technology for cutting of hardened steel and its advantageous properties in comparison with cut-off grinding will be presented. The influence of process parameters on surface properties and burr formation has been determined by experimental analysis. © 2023 Elsevier B.V.. All rights reserved.

关键词： Grinding (machining)

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Incorporating Shape Knowledge into Regression Models

arXiv

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arXiv 2024年

作者： Poursanidis, Miltiadis Link, Patrick Schmid, Jochen Teicher, Uwe Fraunhofer Institute for Industrial Mathematics ITWM Kaiserslautern67663 Germany Fraunhofer Institute for Machine Tools and Forming Technology IWU Chemnitz09126 Germany

Informed learning is an emerging field in machine learning that aims to compensate for insufficient data with prior knowledge. Shape knowledge covers many types of prior knowledge concerning the relationship of a function's output with respect to input variables, for example, monotonicity, convexity, etc. This shape knowledge - when formalized into algebraic inequalities (shape constraints) - can then be incorporated into the training of regression models via a constraint problem formulation. The defined shape-constrained regression problem is, mathematically speaking, a semi-infinite program (SIP). Although off-the-shelf algorithms can be used at this point to solve the SIP, we recommend an adaptive feasible-point algorithm that guarantees optimality up to arbitrary precision and strict fulfillment of the shape constraints. We apply this semi-infinite approach for shape-constrained regression (SIASCOR) to three application examples from manufacturing and one artificial example. One application example has not been considered in a shape-constrained regression setting before, so we used a methodology (ISI) to capture the shape knowledge and define corresponding shape constraints. Finally, we compare the SIASCOR method with a purely data-driven automated machine learning method (AutoML) and another approach for shape-constrained regression (SIAMOR) that uses a different solution algorithm. © 2024, CC BY.

关键词： Contrastive Learning

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Component reuse strategy (CRS) for continuous reinforced thermo-sets enabling circular economy

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Journal of Remanufacturing 2022年第3期12卷 339-355页

作者： von Freeden, Justus Husemann, Alexander Caba, Stefan Fraunhofer Institute or Machine Tools and Forming Technology Chemnitz Germany EDAG Engineering GmbH Fulda Germany

A circular economy, effective technologies for the recycling and reuse of fiber-reinforced plastics (FRPs) are essential to keep these materials attractive for use in various products against the backdrop of stricter environmental regulations. This paper provides an overview of the current state of the art in the recycling and reuse of end-of-life (EOL) fiber reinforced plastic (FRP) products. A significant proportion of EOL FRP products are thermally recycled or used as fillers in the cement industry. Complementary to the existing approaches of structural reuse of FRP is presented in this paper as component reuse strategies (CRS). Both approaches avoid separation or destruction (downgrading) of the composite materials. An application example for the reuse of a carbon-fiber reinforced plastics (CFRP) base frame of an electric vehicle platform is given and analyzed with respect to known design for reuse approaches. The proposed CRS has great potential to complement existing approaches and slow down resource consumption. In addition, extended service life can make CFRP materials more economically attractive. However, further developments are needed as well as the transfer of the principle to other applications. © 2022, The Author(s).

关键词： Automotive Carbon fiber Circular economy Design for reuse Fiber reinforced plastics

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Target Costing as an Approach to reduce Costs in closed-loop Agriculture Systems - Application for the Cultivation of Algae in Photobioreactors 30

Target Costing as an Approach to reduce Costs in closed-loop...

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30th CIRP Life Cycle Engineering Conference, LCE 2023

作者： Stange, Maximilian Tieding, Marc Brinitzer, Gordon Ihlenfeldt, Steffen Fraunhofer Institute for Machine Tools and Forming Technology IWU Reichenhainer Strasse 88 Chemnitz09126 Germany Fraunhofer Institute for Interfacial Engineering and Biotechnology IGB Nobelstrasse 12 Stuttgart70569 Germany Institute of Mechatronic Engineering Technische Universität Dresden Dresden01069 Germany

The rapidly growing world population, the consequences of climate change and conventional agriculture as well as the limited resources of our planet threaten the food supply of humanity, especially with vital proteins. Therefore, innovation of agricultural systems is crucial for global food security and sustainable development. One proposed system is the cultivation of algae in artificially illuminated photobioreactors, which is a promising technology to limit land and water use. To achieve a competitive position between other agricultural systems and to reduce costs in a systematic and proactive approach, we suggest using Target Costing (TC) at an early stage of development. The paper aims to provide an overview of the state of the art in TC of agricultural systems. The authors identify a suitable approach for the economic evaluation of algae cultivation in bioreactors and adapt it specifically for the extraction of proteins. Based on this, different scenarios are discussed how a cost reduction of the existing systems can be achieved. The focus is on the reduction of energy costs, a suitable site selection and the use of side streams and products. © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0)

关键词： Proteins

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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

关键词： Shape optimization

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Modeling the Impact of Laser Powder Bed Fusion on Nd-Fe-B Permanent Magnets

Modeling the Impact of Laser Powder Bed Fusion on Nd-Fe-B Pe...

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Magnetic Conference - Short Papers (INTERMAG Short Papers), IEEE International

作者： Juliane Thielsch Florian Bittner Welf-Guntram Drossel Fraunhofer Institute for Machine Tools and Forming Technology IWU Dresden Germany Institute for Machine Tools and Production Processes Chemnitz University of Technology Chemnitz Germany

Statistical modelling was successfully applied to Laser Powder Bed Fusion (LPBF) of Nd-Fe-B permanent magnets to identify the potential impact of different process parameters and their interactions on resulting magnetic properties. Process models for the magnetic properties coercivity H c , remanence J r as well as for the shape of the demagnetization curve are obtained. The model quality for H c is excellent (R 2 = 0.99). The model for J r only allows a rough statement on the impact of the LPBF process due to a weaker quality of the model (R 2 = 0.77). It will not be possible to maximize H c and J r of LPBF manufactured Nd-Fe-B magnets at the same time due to their contrary dependencies on different LPBF parameters. We have predicted an optimized parameter set with a resulting high H c of 816 kA/m and a maximized J r of 0.65 T. From these properties and the calculated shape of the demagnetization curve we predict a (BH) max of 60.77 kJ/m 3 for a magnet processed on a LPBF machine AconityMINI using MQP™-S powder.

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