Skip to content
Licensed Unlicensed Requires Authentication Published by Oldenbourg Wissenschaftsverlag October 15, 2020

Generation of tailored subsurface zones in steels containing metastable austenite by adaptive machining and validation by eddy current testing

Erzeugung definierter Randzonen in Stählen mit metastabilem Austenit durch adaptive Zerspanung und Validierung mittels Wirbelstromprüfung
  • Lara Vivian Fricke

    M. Sc. Lara Vivian Fricke, born in 1993, studied material engineering at the RWTH Aachen and since 2018 has been working as a scientific employee at the institute of Material Science at the Leibniz Universität Hannover.

    ORCID logo EMAIL logo
    , Hai Nam Nguyen

    M. Sc. Hai Nam Nguyen, born in 1992, studied industrial engineering at the Leibniz University of Hannover and since 2017 has been working as a scientific employee at the institute of Production Engineering and Machine Tools at the Leibniz Universität Hannover.

    , Bernd Breidenstein

    Apl. Prof. Dr. rer. nat. habil. Bernd Breidenstein, born 1957, after studying at the universities of Marburg, Göttingen and Clausthal and earning a doctorate, worked in various industrial companies. Since 2001 he has been head of surface and subsurface analysis at the Institute of Production Engineering and Machine Tools.

    , Berend Denkena

    Prof. Dr.-Ing. Berend Denkena is Head of the Institute of Production Engineering and Machine Tools at the Leibniz Universität Hannover. After obtaining doctorate at the Faculty of Mechanical Engineering at the Leibniz Universität Hannover in 1992, he worked as a design engineer and Head of various research groups for Thyssen Production Systems both in Germany and the United States. From 1996 to 2001 he was Head of Engineering and Turning Machine Development at Gildemeister Drehmaschinen in Bielefeld. Since 2001 he has been a full professor of Production Engineering and Machine Tools and director of the Institute of Production Engineering and Machine Tools at the Leibniz Universität Hannover. He is a CIRP Fellow Member. His primary areas of research are geometry and functionalizing manufacturing processes, machine tools for cutting and grinding, production planning and control, and simulation of manufacturing processes.

    , Marc-André Dittrich

    Dr.-Ing. Marc-André Dittrich studied industrial engineering at the Leibniz Universität Hannover and since 2012 has been working as a scientific employee at the institute of Production Engineering and Machine Tools (IFW) at the Leibniz Universität Hannover. In the period from 2014 to 2015 he was responsible for the management of the department Functionalization at the IFW. Since 2015 he is head of the department Production Systems.

    , Hans Jürgen Maier

    Prof. Dr.-Ing. Hans Jürgen Maier, born in 1960, studied material science in Erlangen. He received his doctorate in 1990 with a thesis on the influence of ambient media on the fatigue behaviour of steels. After completing his doctorate, he became head of the electron microscopy working group and moved to the University of Siegen as senior research engineer in 1993. In 1998 he received the Masing Memorial Prize of the DGM and after a research stay in the USA he was appointed to the chair of materials science at the University of Paderborn in 1999. Since October 2012 he is head of the Institute of Material Science at the Leibniz Universität Hannover. The focus of his research is the investigation of the microstructure-property correlation and the development of validated models that allow the prediction of the behaviour of highly stressed materials under practical conditions. The results of his research have been published in more than 500 scientific papers. Furthermore, he is a member of the editorial board of several international journals. Since 2018 he is a full member of the German Academy of Science and Engineering (acatech) and the Berlin-Brandenburg Academy of Sciences and Humanities.

    and David Zaremba

    Dr.-Ing. David Zaremba studied mechanical engineering at the Leibniz Universität Hannover. Following his studies, he completed his doctorate under the direction of Prof. Maier on the repair of fibre-reinforced plastics. Since 2017, he is head of the division “non-destructive testing methods” at the Institute of Materials Science. The focus of his research is the investigation of microstructural changes in combination with the change of magnetic material properties during and after production processes, and, based on this, property-oriented process control.

From the journal tm - Technisches Messen

Abstract

In order to withstand high mechanical and tribological loads, it is important that the components not only have a high core ductility but also a hard surface. Typically, a suitable microstructure is created by heat treatment processes before the workpiece is machined. However, these processes are time and energy consuming and can lead to component distortion. It would therefore be of great advantage if no additional heat treatment process would be required to produce a hardened subsurface zone. Since turning is often already integrated as a machining process in production lines, it would be advantageous to create a hardened subsurface within this process. As there is no possibility to measure the hardness directly during the turning process, a soft sensor was developed to determine the properties of the subsurface directly during the machining process. Steels with metastable austenite are of particular interest in this context, as metastable austenite can be converted into martensite by deformation. The amount of martensite produced in the subsurface can be adjusted provided that suitable turning parameters can be found. For this purpose, a process parallel material removal simulation was used to determine the actual conditions governing the process. It was found that there is a correlation between the martensite content and the amplitude of the 3rd harmonic of eddy current testing. Therefore, an eddy current sensor accompanying the process can be used as a basis for controlling the turning process for tailored martensite volume content adjustment.

Zusammenfassung

Um hohen mechanischen und tribologischen Belastungen standhalten zu können, ist es wichtig, dass die Bauteile nicht nur eine hohe Kernduktilität, sondern auch eine harte Oberfläche aufweisen. Typischerweise wird eine geeignete Mikrostruktur durch Wärmebehandlungsprozesse erzeugt, bevor das Werkstück bearbeitet wird. Diese Prozesse sind jedoch zeit- und energieaufwändig und können zu Bauteilverzug führen. Daher wäre es von großem Vorteil, wenn kein zusätzlicher Wärmebehandlungsprozess erforderlich wäre, um eine gehärtete Randzone zu erzeugen. Da das Drehen bereits häufig als Bearbeitungsprozess in Fertigungslinien integriert ist, wäre es vorteilhaft, innerhalb dieses Prozesses eine gehärtete Randzone zu erzeugen. Noch gibt es keine Möglichkeit die Härte während des Drehprozesses direkt zu messen. Deswegen wurde ein Soft-Sensor entwickelt, um die Eigenschaften der Randzone direkt während der Bearbeitung zu bestimmen. Dafür sind Stähle mit metastabilem Austenit besonders geeignet, da metastabiler Austenit durch Verformung in Martensit umgewandelt werden kann und die Menge des in der Randzone erzeugten Martensits durch die richtige Wahl der Drehparameter eingestellt werden kann. Dazu wurden mit einer prozessparallelen Materialabtragssimulation die tatsächlichen Eingriffsbedingungen im Prozess ermittelt und überprüft. Des Weiteren wurde eine Korrelation zwischen dem Martensitgehalt und der Amplitude der 3. Harmonischen der Wirbelstromprüfung festgestellt. Daher kann ein prozessbegleitender Wirbelstromsensor als Grundlage für die Steuerung des Drehprozesses zur gezielten Einstellung des Martensitvolumengehaltes verwendet werden.

Award Identifier / Grant number: 401800578

Funding statement: Financial support of this study by the German Research Foundation (DFG) within the research priority program SPP 2086 (grant project number 401800578) is gratefully acknowledged.

About the authors

Lara Vivian Fricke

M. Sc. Lara Vivian Fricke, born in 1993, studied material engineering at the RWTH Aachen and since 2018 has been working as a scientific employee at the institute of Material Science at the Leibniz Universität Hannover.

Hai Nam Nguyen

M. Sc. Hai Nam Nguyen, born in 1992, studied industrial engineering at the Leibniz University of Hannover and since 2017 has been working as a scientific employee at the institute of Production Engineering and Machine Tools at the Leibniz Universität Hannover.

Bernd Breidenstein

Apl. Prof. Dr. rer. nat. habil. Bernd Breidenstein, born 1957, after studying at the universities of Marburg, Göttingen and Clausthal and earning a doctorate, worked in various industrial companies. Since 2001 he has been head of surface and subsurface analysis at the Institute of Production Engineering and Machine Tools.

Berend Denkena

Prof. Dr.-Ing. Berend Denkena is Head of the Institute of Production Engineering and Machine Tools at the Leibniz Universität Hannover. After obtaining doctorate at the Faculty of Mechanical Engineering at the Leibniz Universität Hannover in 1992, he worked as a design engineer and Head of various research groups for Thyssen Production Systems both in Germany and the United States. From 1996 to 2001 he was Head of Engineering and Turning Machine Development at Gildemeister Drehmaschinen in Bielefeld. Since 2001 he has been a full professor of Production Engineering and Machine Tools and director of the Institute of Production Engineering and Machine Tools at the Leibniz Universität Hannover. He is a CIRP Fellow Member. His primary areas of research are geometry and functionalizing manufacturing processes, machine tools for cutting and grinding, production planning and control, and simulation of manufacturing processes.

Marc-André Dittrich

Dr.-Ing. Marc-André Dittrich studied industrial engineering at the Leibniz Universität Hannover and since 2012 has been working as a scientific employee at the institute of Production Engineering and Machine Tools (IFW) at the Leibniz Universität Hannover. In the period from 2014 to 2015 he was responsible for the management of the department Functionalization at the IFW. Since 2015 he is head of the department Production Systems.

Hans Jürgen Maier

Prof. Dr.-Ing. Hans Jürgen Maier, born in 1960, studied material science in Erlangen. He received his doctorate in 1990 with a thesis on the influence of ambient media on the fatigue behaviour of steels. After completing his doctorate, he became head of the electron microscopy working group and moved to the University of Siegen as senior research engineer in 1993. In 1998 he received the Masing Memorial Prize of the DGM and after a research stay in the USA he was appointed to the chair of materials science at the University of Paderborn in 1999. Since October 2012 he is head of the Institute of Material Science at the Leibniz Universität Hannover. The focus of his research is the investigation of the microstructure-property correlation and the development of validated models that allow the prediction of the behaviour of highly stressed materials under practical conditions. The results of his research have been published in more than 500 scientific papers. Furthermore, he is a member of the editorial board of several international journals. Since 2018 he is a full member of the German Academy of Science and Engineering (acatech) and the Berlin-Brandenburg Academy of Sciences and Humanities.

David Zaremba

Dr.-Ing. David Zaremba studied mechanical engineering at the Leibniz Universität Hannover. Following his studies, he completed his doctorate under the direction of Prof. Maier on the repair of fibre-reinforced plastics. Since 2017, he is head of the division “non-destructive testing methods” at the Institute of Materials Science. The focus of his research is the investigation of microstructural changes in combination with the change of magnetic material properties during and after production processes, and, based on this, property-oriented process control.

References

1. P. Mayer, B. Kirsch, C. Müller, H. Hotz, R. Müller, S. Becker, E. von Harbou, R. Skorupski, A. Boemke, M. Smaga, D. Eifler, T. Beck, J.C. Aurich, Deformation induced hardening when cryogenic turning, CIRP Journal of Manufacturing Science and Technology 23 (2018) 6–19.10.1016/j.cirpj.2018.10.003Search in Google Scholar

2. P. Mayer, B. Kirsch, R. Müller, S. Becker, E.v. Harbou, J.C. Aurich, Influence of Cutting Edge Geometry on Deformation Induced Hardening when Cryogenic Turning of Metastable Austenitic Stainless Steel AISI 347, Procedia CIRP 45 (2016) 59–62.10.1016/j.procir.2016.02.148Search in Google Scholar

3. M. Moallemi, A. Kermanpur, A. Najafizadeh, A. Rezaee, H.S. Baghbadorani, P.D. Nezhadfar, Deformation-induced martensitic transformation in a 201 austenitic steel, Materials Science and Engineering: A 653 (2016) 147–152.10.1016/j.msea.2015.12.006Search in Google Scholar

4. T. Oršulová, P. Palček, M. Roszak, M. Uhríčik, M. Smetana, J. Kúdelčík, Change of magnetic properties in austenitic stainless steels due to plastic deformation, Procedia Structural Integrity 13 (2018) 1689–1694.10.1016/j.prostr.2018.12.352Search in Google Scholar

5. A.M. Beese, D. Mohr, Identification of the Direction-Dependency of the Martensitic Transformation in Stainless Steel Using In Situ Magnetic Permeability Measurements, Exp Mech 51 (2011) 667–676.10.1007/s11340-010-9374-ySearch in Google Scholar

6. T. Oršulová, P. Palček, J. Kúdelčík, Effect of Plastic Deformation on the Magnetic Properties of Selected Austenitic Stainless Steels, PEA 14 (2017) 15–18.10.30657/pea.2017.14.04Search in Google Scholar

7. M. Shirdel, H. Mirzadeh, M.H. Parsa, Estimation of the kinetics of martensitic transformation in austenitic stainless steels by conventional and novel approaches, Materials Science and Engineering: A (2015) 256–260.10.1016/j.msea.2014.11.087Search in Google Scholar

8. V.M.A. Silva, C.G. Camerini, J.M. Pardal, J.C.G.d. Blás, G.R. Pereira, Eddy current characterization of cold-worked AISI 321 stainless steel, Journal of Materials Research and Technology 7 (2018) 395–401.10.1016/j.jmrt.2018.07.002Search in Google Scholar

9. S.H. Khan, F. Ali, A. Nusair Khan, M.A. Iqbal, Eddy current detection of changes in stainless steel after cold reduction, Computational Materials Science 43 (2008) 623–628.10.1016/j.commatsci.2008.01.034Search in Google Scholar

10. Y. Altintas, P. Kersting, D. Biermann, E. Budak, B. Denkena, I. Lazoglu, Virtual process systems for part machining operations, CIRP Annals 63 (2014) 585–605.10.1016/j.cirp.2014.05.007Search in Google Scholar

11. B. Denkena, M.-A. Dittrich, F. Uhlich, Augmenting Milling Process Data for Shape Error Prediction, Procedia CIRP 57 (2016) 487–491.10.1016/j.procir.2016.11.084Search in Google Scholar

12. M. Armendia, F. Cugnon, L. Berglind, E. Ozturk, G. Gil, J. Selmi, Evaluation of Machine Tool Digital Twin for machining operations in industrial environment, Procedia CIRP 82 (2019) 231–236.10.1016/j.procir.2019.04.040Search in Google Scholar

13. Y. Altintas, S.D. Merdol, Virtual High Performance Milling, CIRP Annals 56 (2007) 81–84.10.1016/j.cirp.2007.05.022Search in Google Scholar

14. A. Saadallah, F. Finkeldey, K. Morik, P. Wiederkehr, Stability prediction in milling processes using a simulation-based Machine Learning approach, Procedia CIRP 72 (2018) 1493–1498.10.1016/j.procir.2018.03.062Search in Google Scholar

15. D. Plakhotnik, L. Berglind, M. Stautner, D. Euhus, E. Ozturk, T. Fürtjes, Y. Murtezaoglu, Integration of Process Monitoring Data into CAM Simulation, 2018.Search in Google Scholar

16. C. Brecher, W. Lohse, Evaluation of toolpath quality, CIRP Journal of Manufacturing Science and Technology 6 (2013) 233–245.10.1016/j.cirpj.2013.07.002Search in Google Scholar

17. J. García-Martín, J. Gómez-Gil, E. Vázquez-Sánchez, Non-Destructive Techniques Based on Eddy Current Testing, Sensors 11 (2011) 2525–2565.10.3390/s110302525Search in Google Scholar PubMed PubMed Central

18. S. Barton, G. Mroz, W. Reimche, H.J. Maier, Inherent Load Measurement and Component Identification by multi-dimensional Coded Data in the Component’s Subsurface Region, Procedia Technology 26 (2016) 537–543.10.1016/j.protcy.2016.08.067Search in Google Scholar

19. O. Bruchwald, W. Frackowiak, W. Reimche, H. Maier, Non-destructive in situ monitoring of the microstructural development in high performance steel components during heat treatment, La Metallurgia Italiana 11/12 (2015) 29–37.Search in Google Scholar

20. G. Mroz, W. Reimche, Bach Fr.-W., The use of component’s edge region as inherent information carriers and loading indicators, 1st Joint Int. Symp. on System-integrated Intelligence: New Challenges for Product and Production Engineering (2012) 158–160.Search in Google Scholar

21. U. Krupp, C. West, H.-J. Christ, Deformation-induced martensite formation during cyclic deformation of metastable austenitic steel, Materials Science and Engineering: A 481-482 (2008) 713–717.10.1016/j.msea.2006.12.211Search in Google Scholar

22. G. Faninger, U. Hartmann, Physikalische Grundlagen der quantitativen röntgenographischen Phasenanalyse, HTM 27 (1972) 233–244.Search in Google Scholar

23. Y. Yu, Y. Yan, F. Wang, G. Tian, D. Zhang, An approach to reduce lift-off noise in pulsed eddy current nondestructive technology, NDT & E International 63 (2014) 1–6.10.1016/j.ndteint.2013.12.012Search in Google Scholar

24. G.Y. Tian, A. Sophian, Reduction of lift-off effects for pulsed eddy current NDT, NDT & E International 38 (2005) 319–324.10.1016/j.ndteint.2004.09.007Search in Google Scholar

25. Y. Le Bihan, Lift-off and tilt effects on eddy current sensor measurements, Eur. Phys. J. AP 17 (2002) 25–28.10.1051/epjap:2001002Search in Google Scholar

26. B. Denkena, V. Böß, Technological NC Simulation for Grinding and Cutting Processes Using CutS, Proceedings of the 12th CIRP Conference on Modelling of Machining Operations (2009) 563–566.Search in Google Scholar

27. V. Böß, B. Denkena, B. Breidenstein, M.-A. Dittrich, H.N. Nguyen, Improving technological machining simulation by tailored workpiece models and kinematics, Procedia CIRP 82 (2019) 224–230.10.1016/j.procir.2019.04.157Search in Google Scholar

28. A. Weiß, H. Gutte, J. Mola, Contributions of ε and α TRIP Effects to the Strength and Ductility of AISI 304 (X5CrNi18-10) Austenitic Stainless Steel, Metall and Mat Trans A 47 (2016) 112–122.10.1007/s11661-014-2726-ySearch in Google Scholar

29. X.T. Deng, M. Cheng, S.H. Zhang, H.W. Song, M.A. Taha, Residual stresses and martensite transformation in AISI 304 austenitic stainless steel, Mater. Res. Express 6 (2018) 1–10.10.1088/2053-1591/aae292Search in Google Scholar

30. S. Gupta, R. Twardowski, P. Kucharczyk, S. Münstermann, Experimental and Numerical Inverstigations of the TRIP Effect in 1.4301 Austenitic Stainless Steel Under Static Loading, Steel research international 84 (2013) 793–802.Search in Google Scholar

31. B. Denkena, B. Breidenstein, W. Reimche, G. Mroz, T. Mörke, H.J. Maier, Changes of Subsurface Properties due to Fatigue Determined by Sin2ψ-method and Harmonic Analysis of Eddy Current Signals, Procedia Technology 15 (2014) 503–513.10.1016/j.protcy.2014.09.010Search in Google Scholar

Received: 2020-07-17
Accepted: 2020-09-16
Published Online: 2020-10-15
Published in Print: 2020-11-26

© 2020 Walter de Gruyter GmbH, Berlin/Boston

Downloaded on 22.9.2023 from https://www.degruyter.com/document/doi/10.1515/teme-2020-0045/html
Scroll to top button