@inproceedings{59907, abstract = {{Abstract. Flow forming is recognized for its precision in producing rotationally symmetric components, but the use of metastable austenitic stainless steel (AISI 304L) introduces challenges due to uncontrolled strain-induced α’ martensite formation. Variations in factors such as eccentricity and batch inconsistencies lead to unpredictable microstructural profiles, limiting reproducibility [1,2]. This study addresses these issues by incorporating thermal actuators for cryogenic cooling and induction heating to regulate forming temperatures, enabling control of the α’-martensite content. Experimental investigations demonstrate that local tempering during thermomechanical reverse flow forming produces discernible variations in microstructure, affecting mechanical and magnetic properties [3]. Controlled local adjustments of α’-martensite content allow for customization of properties in seamless tubes, advancing manufacturing capabilities for complex, defect-free components. The results presented demonstrate promising strategies for implementation within the context of closed-loop property control in flow forming.}}, author = {{Arian, Bahman and Homberg, Werner and Kersting, Lukas and Trächtler, Ansgar and Rozo Vasquez, Julian and Walther, Frank}}, booktitle = {{Materials Research Proceedings}}, editor = {{Carlone, Pierpaolo and Filice, Luigino and Umbrello, Domenico}}, issn = {{2474-395X}}, keywords = {{Flow Forming, Thermomechanical Forming, α’-Martensite, Property Control}}, location = {{Paestum, Italy}}, publisher = {{Materials Research Forum LLC}}, title = {{{Advanced thermomechanical flow forming: A novel approach to α’-martensite control for enhanced material properties}}}, doi = {{10.21741/9781644903599-127}}, volume = {{54}}, year = {{2025}}, } @article{62024, abstract = {{Abstract This paper presents a characterization of the microstructural evolution and its correlation with the magnetic structure due to flow forming of semi-finished tubes of austenitic stainless steel AISI 304L. The plastic deformation triggers a phase transformation of the metastable austenite into α’-martensite. Depending on the combination of production parameters, different fractions of strain-induced α’-martensite were measured by means non-destructive micromagnetic techniques and correlated with the evolution of hardness and the microstructure using electron backscatter diffraction analyses. The magneto-optical Kerr effect analysis was used as a tool to perform a qualitative analysis of the evolution of the magnetic domain structure correlated with the formation of α’-martensite. An analysis of these data allowed to derive surface magnetization hysteresis loops that were compared with integral hysteresis loops of the specimens. It was proven by both methods that the formation of martensite increases the magnetic energy and the spontaneous magnetization of the specimens. The results of this investigation contribute to a better understanding of micromagnetic sensors to monitor and control the formation of α’-martensite in a flow forming. Furthermore, various techniques have demonstrated the evolution of the magnetic properties of the material, which can be applied in applications for invisible coding of workpieces.}}, author = {{Rozo Vasquez, Julian and Tappe, Jan and Arian, Bahman and Kersting, Lukas and Homberg, Werner and Trächtler, Ansgar and Walther, Frank}}, issn = {{2195-8599}}, journal = {{Practical Metallography}}, number = {{9-10}}, pages = {{617--633}}, publisher = {{Walter de Gruyter GmbH}}, title = {{{Magneto-optical Kerr effect analysis of strain-induced martensite formation during flow forming of metastable austenitic steel AISI 304L}}}, doi = {{10.1515/pm-2025-0059}}, volume = {{62}}, year = {{2025}}, } @inproceedings{62022, abstract = {{Abstract. The incremental flow forming process features a large number of process parameter combinations that can be varied from pass to pass or during a pass. In the future however, a more efficient utilization of this large number of process parameter combinations and a compensation of process disturbances could be required. This is due to a rising demand for increasing the part complexity, e.g. by graded property structures or a more complex geometry. In this context, innovative approaches like closed-loop property control and optimal control are advantageous, but require fast process models of flow forming that are not state of the art. This paper thus proposes a new modelling approach of multi-pass flow forming especially taking the transfer behavior between process parameters and wall thickness evolution from pass to pass into focus. A hybrid modelling approach is developed that combines knowledge about the incremental process character with empirical data regression to a basic analytic relation. The basic relation is further extended by a multi-layer neural network to enhance the overall model accuracy. This hybrid modelling approach is finally validated using experimental data. Thus, it is shown that a suitable model structure was found in context of a future closed-loop control or optimal control for multi-pass flow forming.}}, author = {{Kersting, Lukas and Gunasagran, Sharin Kumar and Arian, Bahman and Rozo Vaszquez, Julian and Trächtler, Ansgar and Homberg, Werner and Walther, Frank}}, booktitle = {{Materials Research Proceedings}}, issn = {{2474-395X}}, publisher = {{Materials Research Forum LLC}}, title = {{{Real-time modelling of incremental multi-pass flow forming by a hybrid, data-based model}}}, doi = {{10.21741/9781644903599-140}}, volume = {{54}}, year = {{2025}}, } @article{62023, abstract = {{Zusammenfassung Die Eigenschaftsregelung mit einer online-Messung der Bauteileigenschaften ist ein in der Umformtechnik viel diskutiertes, aber kaum validiertes Konzept, um den Automatisierungsgrad bei der Bauteilfertigung weiter zu erhöhen. Dieser Artikel soll helfen, die Lücke beispielhaft für den Fertigungsprozess des Drückwalzens metastabiler Austenite zu schließen. Der metastabile austenitische Edelstahl ändert hierbei während der Verformung seinen α′-Martensitgehalt und damit verbunden die magnetischen Eigenschaften. Deshalb soll über die Regelung das definierte Einstellen des α′-Martensitgehaltes möglich werden. Im Rahmen des vorliegenden Artikels wird gezeigt, wie mittels des modellbasierten Entwurfs die Eigenschaftsregelung ausgelegt und parametriert werden kann. Zudem beinhaltet der Artikel experimentelle Validierungsergebnisse der zuvor entworfenen Eigenschaftsregelung.}}, author = {{Kersting, Lukas and Arian, Bahman and Rozo Vasquez, Julian and Trächtler, Ansgar and Homberg, Werner and Walther, Frank}}, issn = {{0178-2312}}, journal = {{at - Automatisierungstechnik}}, number = {{7}}, pages = {{527--540}}, publisher = {{Walter de Gruyter GmbH}}, title = {{{Modellbasierter Entwurf und Validierung einer Eigenschaftsregelung für das Drückwalzen metastabiler Austenite}}}, doi = {{10.1515/auto-2024-0127}}, volume = {{73}}, year = {{2025}}, } @article{62021, author = {{Kersting, Lukas and Arian, Bahman and Rozo Vasquez, Julian and Trächtler, Ansgar and Homberg, Werner and Walther, Frank}}, issn = {{2405-8963}}, journal = {{IFAC-PapersOnLine}}, number = {{1}}, pages = {{109--114}}, publisher = {{Elsevier BV}}, title = {{{State-space modelling approach for control and observer design in property-controlled reverse flow forming}}}, doi = {{10.1016/j.ifacol.2025.03.020}}, volume = {{59}}, year = {{2025}}, } @inbook{57190, abstract = {{This paper deals with the modeling of a soft sensor for detecting α’-martensite evolution from the micromagnetic signals that are measured during the reverse flow forming of metastable AISI 304L austenitic steel. This model can be prospectively used inside a closed-loop property-controlled flow forming process. To achieve this, optimization by means of a non-linear regression of experimental data was carried out. To collect the experimental data, specimens were produced by flow forming seamless tubes at room temperature. Using a combination of production parameters (like the infeed depth and feed rate), specimens with different α’-martensite contents and wall-thickness reductions were produced. An equation to compute α’-martensite from both specific production-process parameters and micromagnetic Barkhausen noise (MBN) measurements was obtained using numerical methods. In this process, the behavior of the quantity of interest (namely, the α’-martensite content) was mathematically evaluated with respect to non-destructive MBN data and the feed rate that was used to produce the components. A combination of exponential and potential functions was defined as the ansatz functions of the model. The obtained model was validated online and offline during the real flow forming of workpieces, obtaining average deviations of up to 7% α’-martensite with respect to the model. The implementation of the soft sensor model for property-controlled production represents an important milestone for producing high-added-value components on the basis of a well-understood process-microstructure-property relationship.}}, author = {{Rozo Vasquez, Julian and Kersting, Lukas and Arian, Bahman and Homberg, Werner and Trächtler, Ansgar and Walther, Frank}}, booktitle = {{Lecture Notes in Mechanical Engineering}}, isbn = {{9783031580055}}, issn = {{2195-4356}}, publisher = {{Springer International Publishing}}, title = {{{Soft Sensor Model of Phase Transformation During Flow Forming of Metastable Austenitic Steel AISI 304L}}}, doi = {{10.1007/978-3-031-58006-2_10}}, year = {{2024}}, } @inproceedings{57189, abstract = {{This paper deals with micromagnetic measurements for online detection of strain-induced α’-martensite during plastic deformation of metastable austenitic steel AISI 304L. The operating principles of the sensors are Barkhausen noise (MBN) and eddy currents (EC), which are suitable for detection of microstructure evolution due to formation of ferromagnetic phases. Nevertheless, the description of the calibration and transformation models of the micromagnetic measurements into quantitative α’-martensite fractions is beyond the scope of this paper. The focus will be put on the qualification of different micromagnetic methods as well as of different measurement systems under conditions similar to the real ones during production, which is crucial for implementation of a property-controlled flow forming process. The investigation was carried out on tubular specimens produced by flow forming, which have different content of α’-martensite. To characterize the sensitivity of the sensors, different contact conditions between sensors and workpieces were reproduced. MBN sensors are suitable for detecting amount of α’-martensite, but the measurements are affected by the surface roughness. This entails that the calibration models for MBN sensors must take account of these effects. EC sensors show a closer match with the amount of α’-martensite without having major affectation by other effects.}}, author = {{Rozo Vasquez, Julian and Kanagarajah, Hanigah and Arian, Bahman and Kersting, Lukas and Homberg, Werner and Trächtler, Ansgar and Walther, Frank}}, publisher = {{Authorea, Inc.}}, title = {{{Barkhausen noise- and eddy current-based measurements for online detection of deformation-induced martensite during flow forming of metastable austenitic steel AISI 304L}}}, year = {{2024}}, } @inproceedings{57173, abstract = {{Manufacturing processes benefit from property control enabling reproducibility, application oriented outcomes, and efficient part production. In reverse flow forming, state of the art practices focus primarily on geometry control, neglecting property control. Given the intricacies of the process involving the interaction of tool and machine behavior, process parameters, properties of semi finished products and temperatures, incorporating process control becomes an imperative for producing components with predefined properties. The property controlled within this reverse flow forming process is the local α’ martensite content. Therefore, process strategies to actively influence the α’ martensite content must be implemented. In this study seamless AISI 304L steel tubes are used, where α’ martensite formation is strain and/or temperature induced through phase transformation within the process. This paper presents innovative process strategies, methods, and specially developed mechanical and thermal actuator systems to locally increase or suppress the α’ martensite content. The use and implementation of these approaches and tools allows the creation of unique optically invisible microstructure profiles containing 3D gradings, implying a radial grading of α’ martensite. The locally implemented α’ martensite, forming these 3D gradings, offers potential applications for functional or sensory purposes. This paper extends beyond theoretical concepts, providing tangible component outcomes.}}, author = {{Arian, Bahman and Homberg, Werner and Kersting, Lukas and Trächtler, Ansgar and Rozo Vasquez, Julian and Walther, Frank}}, booktitle = {{Materials Research Proceedings}}, issn = {{2474-395X}}, publisher = {{Materials Research Forum LLC}}, title = {{{α’-martensite grading techniques in reverse flow forming of AISI 304L}}}, doi = {{10.21741/9781644903254-76}}, volume = {{44}}, year = {{2024}}, } @inproceedings{57178, abstract = {{The incremental flow forming process is currently enhanced in research context by special closed-loop property control concepts to increase the productivity and to control the product properties making invisible property structures like a magnetic barcode possible. However, it is preferred to establish property control concepts on single roller machines instead of conventional machines with three roller actuation due to the better machine accessibility. For those single roller machines, rather poor surface qualities of flow formed workpieces were observed in the past especially for hydraulic actuators. Thus, a new actuator closed-loop position control concept is developed in this paper using model-based control design methods and taking the flow forming forces as a load into account. The novel closed-loop control is validated during workpiece production at the actual single roller flow forming machine. An analysis of the manufactured workpieces show that the surface quality is significantly enhanced by the new control to a roughness level almost similar to conventional three roller flow forming. Thus, a sincere added value to the flow forming process is offered by the novel actuator closed-loop position control.}}, author = {{Kersting, Lukas and Sander, Sebastian and Arian, Bahman and Rozo Vasquez, Julian and Trächtler, Ansgar and Homberg, Werner and Walther, Frank}}, booktitle = {{Materials Research Proceedings}}, issn = {{2474-395X}}, publisher = {{Materials Research Forum LLC}}, title = {{{Improving the flow forming process by a novel closed-loop control}}}, doi = {{10.21741/9781644903131-158}}, volume = {{41}}, year = {{2024}}, } @inproceedings{57171, abstract = {{In manufacturing, property control ensures efficient part production. However, in reverse flow forming, current practices focus on geometry control rather than property control. To address the complexity of the process and tool machine interaction, process control is crucial for defined component properties. This study focuses on controlling local α’ martensite content in reverse flow forming of seamless AISI 304L steel tubes. Strategies and systems are presented to influence α’ martensite content, creating unique microstructure profiles for 1D and 2D Gradings, with tangible component outcomes.}}, author = {{Arian, Bahman and Homberg, Werner and Kersting, Lukas and Trächtler, Ansgar and Rozo Vasquez, Julian and Walther, Frank}}, booktitle = {{Materials Research Proceedings}}, issn = {{2474-395X}}, publisher = {{Materials Research Forum LLC}}, title = {{{Thermomechanical reverse flow forming of AISI 304L}}}, doi = {{10.21741/9781644903131-151}}, volume = {{41}}, year = {{2024}}, } @article{62025, abstract = {{ABSTRACTThis paper deals with micromagnetic measurements for online detection of strain‐induced α′‐martensite during plastic deformation of metastable austenitic steel AISI 304L. The operating principles of the sensors are magnetic Barkhausen noise (MBN) and eddy currents (EC), which are suitable for detection of microstructure evolution due to formation of ferromagnetic phases. The focus of this study was put on the qualification of different micromagnetic techniques and different measurement systems under conditions similar to the real ones during production, which is crucial for implementation of a property‐controlled flow forming process. The investigation was carried out on tubular specimens produced by flow forming, which have different content of α′‐martensite. To characterize the sensitivity of the sensors, different contact conditions between sensors and workpieces were reproduced. MBN sensors are suitable for detecting amount of α′‐martensite, but the measurements are affected by the surface roughness. This entails that the calibration models for MBN sensors must take account of these effects. EC sensors show a closer match with the amount of α′‐martensite without having major affectation by other effects.}}, author = {{Rozo Vasquez, Julian and Kanagarajah, Hanigah and Arian, Bahman and Kersting, Lukas and Homberg, Werner and Trächtler, Ansgar and Walther, Frank}}, issn = {{2577-8196}}, journal = {{Engineering Reports}}, number = {{1}}, publisher = {{Wiley}}, title = {{{Barkhausen Noise‐ and Eddy Current‐Based Measurements for Online Detection of Deformation‐Induced Martensite During Flow Forming of Metastable Austenitic Steel AISI 304L}}}, doi = {{10.1002/eng2.13070}}, volume = {{7}}, year = {{2024}}, } @article{62053, abstract = {{ABSTRACTThis paper deals with micromagnetic measurements for online detection of strain‐induced α′‐martensite during plastic deformation of metastable austenitic steel AISI 304L. The operating principles of the sensors are magnetic Barkhausen noise (MBN) and eddy currents (EC), which are suitable for detection of microstructure evolution due to formation of ferromagnetic phases. The focus of this study was put on the qualification of different micromagnetic techniques and different measurement systems under conditions similar to the real ones during production, which is crucial for implementation of a property‐controlled flow forming process. The investigation was carried out on tubular specimens produced by flow forming, which have different content of α′‐martensite. To characterize the sensitivity of the sensors, different contact conditions between sensors and workpieces were reproduced. MBN sensors are suitable for detecting amount of α′‐martensite, but the measurements are affected by the surface roughness. This entails that the calibration models for MBN sensors must take account of these effects. EC sensors show a closer match with the amount of α′‐martensite without having major affectation by other effects.}}, author = {{Rozo Vasquez, Julian and Kanagarajah, Hanigah and Arian, Bahman and Kersting, Lukas and Homberg, Werner and Trächtler, Ansgar and Walther, Frank}}, issn = {{2577-8196}}, journal = {{Engineering Reports}}, number = {{1}}, publisher = {{Wiley}}, title = {{{Barkhausen Noise‐ and Eddy Current‐Based Measurements for Online Detection of Deformation‐Induced Martensite During Flow Forming of Metastable Austenitic Steel AISI 304L}}}, doi = {{10.1002/eng2.13070}}, volume = {{7}}, year = {{2024}}, } @inproceedings{44316, author = {{Rozo Vasquez, Julian and Arian, Bahman and Kersting, Lukas and Walther, Frank and Homberg, Werner and Trächtler, Ansgar}}, location = {{Krakau}}, title = {{{Softsensor model of phase transformation during flow forming of metastable austenitic steel AISI 304L}}}, year = {{2023}}, } @inproceedings{44314, abstract = {{Abstract. Workpiece property-control permits the application-oriented and time-efficient production of components. In reverse flow forming, for example, a control of the microstructure profile is not yet part of the state of the art, in contrast to the geometry control. This is, due to several reasons, particularly challenging when forming seamless tubes made of metastable austenitic stainless AISI 304L steel. Inducing mechanical and/or thermal energy can cause a phase transformation from austenite to martensite within this steel. The resulting α’-martensite has different mechanical and micromagnetic properties, which can be advantageous depending on the application. For purposes of local property control, the resulting α’-martensite content should be measured and controlled online during the forming process. This paper presents results from the usage of a custom developed cryo-system and different application strategies to use liquid nitrogen as a coolant for local enhancement of the forming-temperature depending α’-martensite content. }}, author = {{Arian, Bahman and Homberg, Werner and Kersting, Lukas and Trächtler, Ansgar and Rozo Vasquez, Julian and Walther, Frank}}, booktitle = {{Materials Research Proceedings}}, issn = {{2474-395X}}, publisher = {{Materials Research Forum LLC}}, title = {{{Cryogenic reverse flow forming of AISI 304L}}}, doi = {{10.21741/9781644902479-219}}, year = {{2023}}, } @article{49705, author = {{Stebner, Sophie Charlotte and Arian, Bahman and Martschin, Juri and Dietrich, Stefan and Feistle, Martin and Hütter, Sebastian and Lafarge, Rémi and Laue, Robert and Li, Xinyang and Schulte, Christopher and Spies, Daniel and Thein, Ferdinand and Wendler, Frank and Wrobel, Malte and Vasquez, Julian Rozo and Dölz, Michael and Münstermann, Sebastian}}, journal = {{Electrical Engineering: Systems and Control}}, title = {{{Monitoring the evolution of dimensional accuracy and product properties in property-controlled forming processes}}}, doi = {{10.48550/ARXIV.2305.19601}}, year = {{2023}}, } @article{48075, abstract = {{AbstractThe constantly increasing challenges of production technology for the economic and resource-saving production of metallic workpieces require, among other things, the optimisation of existing processes. Forming technology, which is confronted with new challenges regarding the quality of the workpieces, must also organise the individual processes more efficiently and at the same time more reliably in order to be able to guarantee good workpiece quality and at the same time to be able to produce economically. One way to meet these challenges is to carry out the forming processes in closed-loop control systems using softsensors. Despite the many potential applications of softsensors in the field of forming technology, there is still no definition of the term softsensor. This publication therefore proposes a definition of the softsensor based on the definition of a sensor and the distinction from the observer, which on the one hand is intended to stimulate scientific discourse and on the other hand is also intended to form the basis for further scientific work. Based on this definition, a wide variety of highly topical application examples of various softsensors in the field of forming technology are given.}}, author = {{Homberg, Werner and Arian, Bahman and Arne, Viktor and Borgert, Thomas and Brosius, Alexander and Groche, Peter and Hartmann, Christoph and Kersting, Lukas and Laue, Robert and Martschin, Juri and Meurer, Thomas and Spies, Daniel and Tekkaya, A. Erman and Trächtler, Ansgar and Volk, Wolfram and Wendler, Frank and Wrobel, Malte}}, issn = {{0944-6524}}, journal = {{Production Engineering}}, keywords = {{Industrial and Manufacturing Engineering, Mechanical Engineering}}, publisher = {{Springer Science and Business Media LLC}}, title = {{{Softsensors: key component of property control in forming technology}}}, doi = {{10.1007/s11740-023-01227-1}}, year = {{2023}}, } @article{44312, abstract = {{Zusammenfassung Aufgrund aktueller Transformationsprozesse kommt der automatisierten und ressourceneffizienten Fertigung hochfester Leichtbauteile eine steigende Bedeutung zu, beispielsweise im Flugzeug- und Fahrzeugbau. Für kleine Losgrößen bietet sich hier insbesondere das Fertigungsverfahren des Drückwalzens an. Der konventionelle, industriell genutzte Drückwalzprozess stößt allerdings aufgrund der Prozesskomplexität hinsichtlich der Reproduzierbarkeit an seine Grenzen. Dies wird in der Praxis teilweise durch personengebundenes Erfahrungswissen kompensiert. Auch ist es nicht möglich, Bauteileigenschaften definiert einzustellen. Aus diesem Grund bietet der Einsatz einer neuartigen Eigenschaftsregelung Chancen zur Weiterentwicklung des Fertigungsprozesses und die Möglichkeit zur Prozessautomatisierung. Hier werden die Werkzeugbahnen abhängig einer Online-Eigenschaftsmessung über eine zusätzliche Reglerkaskade manipuliert. Die Entwicklung einer solchen Eigenschaftsregelung erfordert den Einsatz geeigneter, modellbasierter Entwurfsmethoden. In diesem Beitrag wird daher ein regelungstechnisches Systemmodell für das Drückwalzen metastabiler austenitischer Edelstähle vorgestellt. Das Simulationsmodell weist aufgrund seiner Echtzeitfähigkeit neben dem Einsatz als reines Entwurfsmodell weitere Nutzungsmöglichkeiten z.B. in Beobachtern auf und grenzt sich somit von domänenspezifischen Simulationstools wie der FEM ab.}}, author = {{Kersting, Lukas and Arian, Bahman and Rozo Vasquez, Julian and Trächtler, Ansgar and Homberg, Werner and Walther, Frank}}, issn = {{0178-2312}}, journal = {{at - Automatisierungstechnik}}, keywords = {{Electrical and Electronic Engineering, Computer Science Applications, Control and Systems Engineering}}, number = {{1}}, pages = {{68--81}}, publisher = {{Walter de Gruyter GmbH}}, title = {{{Echtzeitfähige Modellierung eines innovativen Drückwalzprozesses für die eigenschaftsgeregelte Bauteilfertigung}}}, doi = {{10.1515/auto-2022-0106}}, volume = {{71}}, year = {{2023}}, } @inproceedings{44315, abstract = {{Abstract. Climate change, rare resources and industrial transformation processes lead to a rising demand of multi-complex lightweight forming parts, especially in aerospace and automotive sectors. In these industries, flow forming is often used to produce cylindrical forming parts by reducing the wall thickness of tubular semifinished parts, e.g. for the production of hydraulic cylinders or gear shafts. The complexity and functionality of flow forming workpieces could be significantly increased by locally graded microstructure and geometry structures. This enables customized complex hardness distributions at wear surfaces or magnetic QR codes for a unique, tamper-proof product identification. The production of those complex, 2D (axial and angular) graded forming parts currently depicts a great challenge for the process and requires new solutions and strategies. Hence, this paper proposes a novel control strategy that includes online measurements from an absolute encoder to determine the angular workpiece position. Workpieces of AISI 304L stainless steel with 2D-graded structures are successfully manufactured using this new strategy and analyzed regarding the possible accuracy and resolution of the gradation. At this point, a dependency of the gradations on the sensor and actuator dynamics, accuracy and geometry could be noted. It is further evaluated how the control strategy could be extended by an observer-based closed-loop property control approach to enhance the accuracy of the suggested strategy. }}, author = {{Kersting, Lukas and Arian, Bahman and Rozo Vasquez, Julian and Trächtler, Ansgar and Homberg, Werner and Walther, Frank}}, booktitle = {{Materials Research Proceedings}}, issn = {{2474-395X}}, publisher = {{Materials Research Forum LLC}}, title = {{{Control strategy for angular gradations by means of the flow forming process}}}, doi = {{10.21741/9781644902479-220}}, year = {{2023}}, } @article{44318, author = {{Rozo Vasquez, Julian and Arian, Bahman and Kersting, Lukas and Walther, Frank and Homberg, Werner and Trächtler, Ansgar}}, journal = {{Metals}}, title = {{{Detection of phase transformation during plastic deformation of metastable austenitic steel AISI 304L by means of X-ray diffraction pattern analysis}}}, year = {{2023}}, } @inproceedings{34001, author = {{Arian, Bahman and Homberg, Werner and Kersting, Lukas and Trächtler, Ansgar and Rozo Vasquez, Julian}}, booktitle = {{36. Aachener Stahlkolloquium – Umformtechnik “Ideen Form geben“}}, isbn = {{978-3-95886-460-3}}, pages = {{333--347}}, title = {{{Produktkennzeichnung durch lokal definierte Einstellung von ferromagnetischen Eigenschaften beim Drückwalzen von metastabilen Stahlwerkstoffen}}}, year = {{2022}}, }