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11th CIRP Conference on Photonic Technologies, LANE 2020

作者： Aragaw, Endalkachew Mekonnen Gärtner, Eric Schubert, Andreas Institute for Machine Tools and Production Processes Chemnitz University of Technology Reichenhainer Str. 70 09107 Germany Fraunhofer Inistitute for Machine tools and Forming Technology IWU Reichenhainer Str. 88 09126 Germany

This paper deals with the tribological performance of forming tool steel 1.2379. Laser hardening and Laser surface texturing are proposed as processes to improve this tribological performance. Hardening influences the surface hardness and wear resistance. While considering the parameter and the specific material, the correlation between heating power and material property is first modelled using FEM of the heat transfer. Based on the modelling result, the realization is performed by nanosecond laser and analyzed by SEM and by comparing the micro - hardness comparison with a reference value. Then textures are integrated into the hardened surface by picosecond laser ablation while focusing on its suitability for smooth dimples and on the examination by pin-on-disk tests for the effect of incorporating textures on the friction performance. Lower friction coefficients between tool and workpiece improve tool durability and product quality as well. © 2020 The Authors. Published by Elsevier B.V.

关键词： Microhardness

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Infrared-based Detection of Porosity Formation in Laser-based Powder Bed Fusion of Ti6Al4V

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Procedia CIRP 2025年 134卷 443-448页

作者： Eckart Uhlmann Gustavo Reis de Ascencao Bernhard Hesse Jussi-Petteri Suuronen Paul Helmerking David Carlos Domingos Fraunhofer Institute for Production Systems and Design Technology (IPK) Pascalstraße 8-9 10587 Berlin Germany Technische Universität Berlin – Institute for Machine Tools and Factory Management (IWF) Pascalstraße 8-9 Berlin 10587 Germany XPLORAYTION GmbH Invalidenstraße 34 10115 Berlin Germany

The prospects of a broad industrial adoption of additive manufacturing technologies are strongly dependent on the capability of manufacturing systems to consistently deliver high quality parts. While closed loop control is still in its infancy, the in-situ identification of defects is currently of scientific and industrial interest. Radiative measurements have been gaining ground in the monitoring of laser-based powder bed fusion of Metals due to key features that can be extracted from the melt pool and surrounding regions. This paper presents an investigation of the use of high-speed short-wave infrared imaging and photodiodes for the detection of porosity formation in Ti6Al4V parts during processing. The formation of sparks and the material cooldown information are geometrically registered to micro computed tomography data of each sample, building a labelled database for the development of a logistic regression-based porosity prediction model. The model performance is assessed for low, mid, and high energy processing conditions, resulting in F1-scores between 0.51 and 0.81 for the classification of layers, depending on the dataset used for training and testing as well as on the defect threshold selected for binary labelling.

关键词： Additive Manufacturing Laser-based Powder Bed Fusion of Metals PBF-LB/M Process Monitoring Thermography Computed Tomography CT

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Development of Thin-film Sensors for In-process Measurement during Injection Molding

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Procedia CIRP 2023年 120卷 619-624页

作者： Anna Schott Martin Rekowski Frederic Timmann Christoph Herrmann Klaus Dröder Fraunhofer Institute for Surface Engineering and Thin Films IST Bienroder Weg 54 E 38108 Braunschweig Germany Institute of Machine Tools and Production Technology Technische Universität Braunschweig Langer Kamp 19b 38106 Braunschweig Germany

Resource and energy efficiency in manufacturing is of great significance for future developments. Digitization is becoming an important strategy for meeting these challenges and opening up different paths to sustainability. Injection molding as a high-volume process technology offers great opportunities for this approach due to its wide range of applications, producing polymer parts for use in industrial, automotive and consumer use. Due to process variation and individualizations, manufacturing ramp-ups currently produce significant volumes of scrap due to process variations. For improved process parameter setting and validation of simulation models in-process measurement data is mandatory and expected to be a key enabler for automated real-time quality monitoring in future production. One way to measure temperature and melt flow directly in the cavity with contact to the melt is to use thin-film sensors. They are applied to the surface of the tool with high hardness, high wear resistance, low coefficient of friction and high load capacity, are very small and only a few micrometers thick. This research describes the development of thin-film sensors, starting with the tool concept to integrate a sensor insert, followed by the physical operating principle. The developed thin-film layer system and its fabrication process using vacuum-based deposition techniques such as physical vapor deposition and chemical vapor deposition are explained. Combined with microstructuring techniques such as photolithography, the thin-film sensor structures were fabricated and their thermoresistive behavior is characterized. The applied sensor design with a high spatial resolution to detect both temperature and flow front movement is shown. Finally, the developed sensors were experimentally tested in the laboratory. Results of temperature measurements, sensor performance and flow front movement are presented and future potential for applications are discussed.

关键词： Thin-film Sensor In-process Temperature Measurement Data Analysis Process Monitoring Injection Molding

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Interaction of Digital Twins in a Sustainable Battery Cell Production 55

Interaction of Digital Twins in a Sustainable Battery Cell P...

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55th CIRP Conference on Manufacturing Systems, CIRP CMS 2022

作者： Kies, Alexander D. Krauß, Jonathan Schmetz, Arno Schmitt, Robert H. Brecher, Christian Fraunhofer Institute for Production Technology IPT Steinbachstr. 17 Aachen52074 Germany Fraunhofer Research Institution for Battery Cell Production FFB Mendelstr. 11 Münster48149 Germany Laboratory for Machine Tools and Production Engineering WZL of RWTH University Campus-Boulevard 30 Aachen52074 Germany

In this paper, we propose a procedure for identifying suitable fields of action for digital twins, selecting meaningful use-cases to realize the benefits of digital twins, and prototyping their implementation in the context of battery cell production. For this purpose, we present a framework that maps out the various fields of action for realizing the benefits of digital twins in the sustainable factory of the future. In addition, the identification of suitable use-cases in the respective fields of action is described. Using the example of prototypical implementations from battery cell production, it is illustrated how different digital twins interact with each other towards the vision of sustainable production. This focuses on the digital machine, building, and product twin. The aggregation of the twins and their use enables a conservation of resources and an increase in efficiency in the production of the cells and enables the optimization of subsequent value chain steps. © 2022 The Authors. Published by Elsevier B.V.

关键词： Battery Battery cell Battery cell production Digital twin Sustainability

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Distributed real-time production control for resilient manufacturing systems

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Procedia CIRP 2023年 120卷 1274-1279页

作者： Eckart Uhlmann Julian Polte Christopher Mühlich Technische Universität Berlin Institute for Machine Tools and Factory Management IWF Pascalstraße 8-9 10587 Berlin Germany Fraunhofer Institute for Production Systems and Design Technology IPK Pascalstraße 8-9 10587 Berlin Germany

To enable resilient manufacturing, production control systems must be able to adapt quickly and flexibly to unexpected changes. Motivated by Industrie 4.0, multi-agent systems offer a promising approach to meet these requirements. This paper presents a method for distributed production control that enables production entities to make optimal decisions regarding capacity utilization and the compliance of delivery dates in real-time despite disruptive events. Based on a multi-agent Markov Decision Process, production entities are modeled as autonomous software agents that can solve Flexible Job-Shop Problems through message passing. The performance of the proposed method is evaluated in a simulated production environment.

关键词： Industrie 4.0 resilient manufacturing systems distributed production control multi-agent system Flexible Job-Shop Problem

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Data Acquisition Framework for spatio-temporal analysis of path-based welding applications

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Procedia CIRP 2024年 130卷 1644-1652页

作者： Georgij Safronov Heiko Theisinger Vasco Sahlbach Christoph Braun Andreas Molzer Anabelle Thies Christian Schuba Majid Shirazi Thomas Reindl Albrecht Hänel Philipp Engelhardt Steffen Ihlenfeldt Peter Mayr BMW AG Petuelring 130 80788 München Germany Technical University of Munich Chair of Materials Engineering of Additive Manufacturing Freisinger Landstraße 52 85748 Garching bei München Germany Fraunhofer Institute for Machine Tools and Forming Technology IWU Nöthnitzer Straße 44 01187 Dresden Germany nebumind GmbH Willy-Messerschmitt-Straße 1 82024 Taufkirchen Germany

The use of digital technologies in industrial manufacturing reduces operational costs and improves production quality. The “Framework for Spatiotemporal Production Data Acquisition” (PathSense) aims to improve access and usability of production data by applying a common data ecosystem. Through integrating operational technology (OT) and information technology (IT), PathSense supports decision-making and process optimization. The framework uses the concept of digital shadows to collect critical information from sensors within the continuous manufacturing processes, e.g., welding or gluing lines. Spatial and temporal digital shadows are developed in accordance with human spatial cognition to support sophisticated–yet intuitive–human-computer interactions without the need for advanced data science skills. The backbone of the framework consists of robust data pipelines with a setup incorporating modern IT protocols, such as OPC UA and MQTT, to support the efficient acquisition and management of data. The paper addresses the challenges associated with the combination of IT and OT in cyber-physical systems, stressing modern complex data-intensive manufacturing as one exemplary domain to be tackled by scalable and secure data architectures. The paper identifies two major future directions: refining data integration processes and embedding advanced machine learning algorithms to enable automated data analysis and improve process quality monitoring. In summary, PathSense proposes a data-driven approach for quality inspection in manufacturing, which may eventually enhance industry practices and move towards data-driven decisions and increased operational flexibility.

关键词： PathSense digital twin welding process data acquisition spatiotemporal analysis defect detection OPC UA MQTT AI

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Geometric empirical modelling of forces influenced by the cutting edge microgeometry in orthogonal cutting of unidirectional CFRP 18

Geometric empirical modelling of forces influenced by the cu...

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18th CIRP Conference on Modeling of Machining Operations, CMMO 2021

作者： Sauer, Konstantin Nowak, Alexander Regel, Joachim Wertheim, Rafael Dix, Martin Chemnitz University of Technology Professorship Production Systems and Processes Reichenhainer Strasse 70 Chemnitz09126 Germany Chemnitz University of Technology Professorship Machine Elements and Product Development Reichenhainer Strasse 70 Chemnitz09126 Germany Fraunhofer Institue for Machine Tools and Forming Technology Reichenhainer Strasse 88 Chemnitz09126 Germany

In optimising the cutting of carbon fibre reinforced plastics (CFRP), increasing emphasis is placed on the cutting edge microgeometry. A significant challenge lies in understanding the engagement conditions between tool and workpiece, influencing tool wear mechanisms and performance. This paper aims to provide a more in-depth insight into the influence of cutting parameters on process forces when applying ideally rounded cutting edges in orthogonal cutting. A geometric empirical process model is developed for calculating the cutting force and the passive force, considering the cutting edge radius, the uncut chip thickness, and the fibre cutting angle. As a result, the minimum uncut chip thickness was determined, and process forces were calculated. © 2021 Elsevier B.V.. All rights reserved.

关键词： Carbon fiber reinforced plastics

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High-Speed-Microscopy for Scalable Quality Control in Automated Production of Stem Cell Spheroids for Tissue Engineering

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Procedia CIRP 2023年 120卷 303-307页

作者： J. Krieger B. Nießing N. König R.H. Schmitt Fraunhofer Institute for Production Technology IPT Steinbachstr. 17 52074 Aachen Germany Laboratory for Machine Tools and Production Engineering (WZL) RWTH Aachen University Campus-Boulevard 30 52074 Aachen Germany

The EU Horizon 2020 project »JointPromise« implies the conception and implementation of an end-to-end automated production platform for three-dimensional joint implants, paving the way for tissue-engineered implants able to regenerate deep osteochondral defects. Spheroid-based implants provide a novel approach in tissue engineering by aggregating progenitor cells into potent microtissues. After the differentiation of cartilaginous microtissues, functional joint implants are assembled via 3D bioprinting to match the complex structural organization of native cartilage tissue. As the automation approach of the project aims to overcome bottlenecks in manual production such as product variability, lack of scalability and high personnel costs, a high-throughput quality control system is crucial for the production of reliable Advanced Therapy Medicinal Products (ATMPs). By establishing not only a technical solution for the full digitization of the cell culture plates but also an intelligent image processing algorithm for the detection of the cell spheroids, relevant process parameters like size distribution and growth curves can be detected. Critical thresholds in spheroid growth are evaluated to minimize risks of carcinogenic tissue formation in vivo as well as to define harvest criteria to prevent inhomogeneous bioprinting results. In order to calculate the required throughput and elaborate optimization potentials of the automated spheroid production, voids in the cultivation vessel or disrupted aggregates due to media changes or transportation are detected. Ultimately, the highspeed-microscopy complies with the requirements of a high-throughput automated cell production platform to meet the rising demand for alternative therapeutic approaches in regenerative medicine.

关键词： Automation Osteoarthritis Tissue Engineering Regenerative Medicine Microscopy

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Cause-Effect Relationships in Battery Cell Production - Data based validation of expert knowledge in electrode production 56

Cause-Effect Relationships in Battery Cell Production - Data...

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56th CIRP International Conference on Manufacturing Systems, CIRP CMS 2023

作者： Fitzner, A. Abramowski, J.-P. Schmetz, A. Krauß, J. Borzutzki, K. Eckstein, M. Pouls, K. Baum, C. Schmitt, R.H. Kampker, A. Fraunhofer Research Institution for Battery Cell Production FFB Bergiusstr. 8 Münster48165 Germany Fraunhofer Institute for Production Technology IPT Steinbachstr. 17 Aachen52074 Germany Laboratory for Machine Tools and Production Engineering WZL RWTH University Campus-Boulevard 30 Aachen52074 Germany Production Engineering of E-Mobility Components PEM of RWTH University Bohr 12 Aachen52072 Germany

The advancing climate change requires a shift from conventional energy sources to renewable ones, which is accompanied by the indispensability of an efficient and sustainable storage of electrical energy. The production of lithium-ion battery cells comprises an enormous complexity, as it consists of several interlinked process steps, each with different quality requirements for the (intermediate) products and the processes itself. This complexity means that a supposedly insignificant process parameter can lead to errors and deviations in the manufactured products via complex cause-effect relationships, that are not fully known. The missing knowledge of the processes and inter-process interdependencies lead to difficulties in the setup of a suitable quality assurance in battery cell production to reduce scrap rates. Beside these potentials in planning and optimizing the process chain of the battery cell factory of tomorrow are impeded. We developed a method to build up a relevant knowledge base on cause-effect relationships for battery cell production. Expert knowledge based on experience and intuition has been collected and quantitative cause-effect relationships are established. This knowledge is used to set up the initial data acquisition, ensuring relevant data being available for analysis. Afterwards, the data analysis, that validates and extends this expert knowledge, is defined. This approach is applied to real-world use-cases including machinery and laboratory equipment in battery cell production. The electrode production is selected as the basis for validation. The found inter-relationships either validate the qualitative expert knowledge, contradict this prior knowledge or else add new insights about the battery cell electrode production process that have not been considered in the qualitative expert knowledge. Methods used include correlations and a predictive power score for non-linear interdependencies. The cause-effect relationships are constantly updat

关键词： battery cell production cause-effect relationships digital factory

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Biologicalisation of manufacturing on a factory scale – Taking a wider approach to envision a biologically transformed pulp-factory

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Procedia CIRP 2023年 120卷 350-355页

作者： Oliver Schömig Robar Arafat Tim Abraham Christoph Herrmann TU Braunschweig Institute of Machine Tools and Production Technology Chair of Sustainable Manufacturing and Life Cycle Engineering Langer Kamp 19b 38106 Braunschweig Germany Fraunhofer Institute for Surface Engineering and Thin Films IST 38108 Braunschweig Germany

The biologicalisation of manufacturing (BoM) is becoming a major driver for innovation, rendering conventional production processes more sustainable and efficient. So far, most biological transformation approaches focus on improving single technologies or materials in the production chain irrespective of the adjacent processes. However, the potential for BoM might even be greater if a broader approach is taken. Similar to how biological systems achieve efficiency by utilizing self-sufficient, highly interconnected processes, linking multiple individual BoM-technologies in a factory environment could lead to previously unattained improvements. This paper examines the potential of such a holistic transformation using the example of a manufacturing process from the pulp and paper industry. A production process for bleached pulp based on the chemical kraft process was chosen and screened for its inherent environmental challenges. Existing bio-based optimization approaches were then collected and assigned to the production steps followed by an evaluation of possible synergies and interactions concerning their simultaneous implementation on a factory scale. The survey revealed similarities and interlocking functions for a wide variety of BoM-technologies that might help to overcome some of the current hurdles faced in their individual implementation. Based on the findings a vision is presented about i) how a factory scale BoM holds the potential to improve sustainability of kraft pulp production in the short term and ii) how it could play a role in enabling more flexible and circular processes in the long term. The presented ideas should thereby serve as an impulse for a general investigation of wider biologicalisation approaches and provide a starting point for the creation of systematic methodical procedures to investigate and evaluate biological transformation processes on a factory scale.

关键词： Sustainability Biologicalisation of manufacturing Pulp and Paper

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