This image shows Hans-Christian Möhring

Hans-Christian Möhring

Univ.-Prof. Dr.-Ing. Dr. h. c.

Chair and Director
Institute for Machine Tools
Management

Contact

+49 711 685 83773
 +49 711 685 70040

Holzgartenstr. 17
70174 Stuttgart
Germany
Room: 2.009

  1. 2025

    1. Derbas, M., Frömel-Frybort, S., Möhring, H.-C., & Riegler, M. (2025). Accelerated Singular Spectrum Analysis and Machine Learning to investigate wood machining acoustics. Mechanical Systems and Signal Processing, 223. https://doi.org/10.1016/j.ymssp.2024.111879
    2. Jaquemod, A., Reuter, M., Palalic, M., & Möhring, H.-C. (2025). AI-Supported Process Monitoring in Machining / In-Process Quality Assurance of Inhomogeneous Materials Using Feature- Based Machine Learning Methods. In ZWF - Zeitschrift für Wirtschaftlichen Fabrikbetrieb: Vol. KI in Engineering und Produktion (pp. 263–268). Walter de Gruyter. https://doi.org/10.1515/zwf.2024-0136
    3. Wolf, J., Eisseler, R., Bandaru, N. K., Dienwiebel, M., & Möhring, H.-C. (2025). A Novel Approach for Modelling Loads on Profiled Cutting Tools. Procedia CIRP, 133, 394–399. https://doi.org/10.1016/j.procir.2025.02.068
    4. Feng, Q., Werkle, K. T., Maier, W., & Möhring, H.-C. (2025). Intelligent soft jaws for clamping complex geometric surfaces using active-controlled MRF in a 3D-printed TPU-cushion. Production Engineering. https://doi.org/10.1007/s11740-025-01336-z
    5. Wolf, J., Bandaru, N. K., Dienwiebel, M., & Möhring, H.-C. (2025). Image Based Detection of Coating Wear on Cutting Tools With Machine Learning. Journal of Machine Engineering, 25, Article 1. https://doi.org/10.36897/jme/196725
    6. Güzel, K., & Möhring, H.-C. (2025). Geometry modifications of circular saw blades to reduce aeroacoustic noise emissions. The International Journal of Advanced Manufacturing Technology. https://doi.org/10.1007/s00170-024-14966-x

  2. 2024

    1. Maier, W., Möhring, H.-C., Feng, Q., & Wunderle, R. (2024). Augmented reality to visualize a finite element analysis for assessing clamping concepts. https://doi.org/10.21203/rs.3.rs-3941650/v1
    2. Maier, W., Möhring, H.-C., Feng, Q., & Wunderle, R. (2024). Augmented reality to visualize a finite element analysis for assessing clamping concepts. The International Journal of Advanced Manufacturing Technology. https://doi.org/10.1007/s00170-024-13960-7
    3. Reeber, T., Wolf, J., & Möhring, H. C. (2024). A Data-Driven Approach for Cutting Force Prediction in FEM Machining Simulations Using Gradient Boosted Machines. J. Manuf. Mater. Process., 8(3), Article 107. https://doi.org/10.3390/jmmp8030107
    4. Dünn, C., Kneifel, J., Roj, R., Jaquemod, A., Güzel, K., Pelshenke, C., Theiß, R., Möhring, H.-C., & Dültgen, P. (2024). AI-based Real-Time Analysis of Sawing Processes for the Identification of Materials. In G. G. zur Förderung angewandter Informatik e.V. (Ed.), AI4EA - Berlin Workshop on Artificial Intelligence for Engineering Applications. https://www.gfai.de/fileadmin/Downloads/Tagungsband/gfai-tagungsband-2024.pdf
    5. Bieg, F., Maucher, C., & Möhring, H.-C. (2024). Influence of the Substrate Size on the Cooling Behavior and Properties of the DED-LB Process. Journal of Machine Engineering, 24, Article 2. https://doi.org/10.36897/jme/189582
    6. Wolf, J., Werkle, K. T., & Möhring, H.-C. (2024). Study on Dynamic Behaviour in FFF 3D-printing with Crossed Gantry Kinematic. Procedia CIRP, 121, 162–167. https://doi.org/10.1016/j.procir.2023.09.244
    7. Möhring, H.-C., & Gutsche, D. (2024). Sensory chuck jaw for enhancing accuracy in turning thin-walled parts. CIRP annals, 73, Article 1. https://doi.org/10.1016/j.cirp.2024.04.082
    8. Wolf, J., Gerold, J., & Möhring, H.-C. (2024). Development of an Extraction Hood for Efficient Chip Collection during the Finishing Process of FFF 3D Printed Parts. Procedia CIRP, 122, 43. https://doi.org/10.1016/j.procir.2024.01.008
    9. Gutsche, D., & Möhring, H.-C. (2024). Development of a modelling approach for face-driving systems in turning. Cirp Cms 2024. https://doi.org/10.1016/j.procir.2024.10.305
    10. Georgi, P., Ehnert, S., Güzel, K., & Möhring, H.-C. (2024). Design and simulation of a multisensory-multi-process end-effector for application to various kinematics. Procedia CIRP, 130, 915–923. https://doi.org/10.1016/j.procir.2024.10.185
    11. Palalić, M., Güzel, K., & Möhring, H.-C. (2024). Intelligent image processing as a monitoring method for laser-based additive manufacturing.
    12. Reeber, T., Berndt, M., Simon, P. M., Henninger, J., Aurich, J. C., & Möhring, H.-C. (2024). A Comparative Analysis of Axis Drive Current Measurements in CNC Machine Tools for Machine Learning Assisted Process Monitoring. Procedia CIRP, 130, 214–219. https://doi.org/10.1016/j.procir.2024.10.078
    13. Wegert, R., Guski, V., Schmauder, S., & Möhring, H.-C. (2024). In-process approach for editing the subsurface properties during single-lip deep hole drilling using a sensor-integrated tool. Production Engineering. https://doi.org/10.1007/s11740-024-01265-3
    14. Reeber, T., Henninger, J., Weingarz, N., Simon, P. M., Berndt, M., Glatt, M., Kirsch, B., Eisseler, R., Aurich, J. C., & Möhring, H. C. (2024). Tool condition monitoring in drilling processes using anomaly detection approaches based on control internal data. Procedia CIRP, 121, 216–221. https://doi.org/10.1016/j.procir.2023.08.066
    15. Palalić, M., Jaquemod, A., Güzel, K., & Möhring, H.-C. (2024). In-Process Monitoring of Inhomogeneous Material Characteristics Based on Machine Learning for Future Application in Additive Manufacturing. Journal of Machine Engineering. https://doi.org/10.36897/jme/187872
    16. Tandler, T., & Möhring, H.-C. (2024). Active runout compensation using the guide elements on metal band saws for a longer tool life and reduced material loss. Production Engineering. https://doi.org/10.1007/s11740-024-01296-w
    17. Palalić, M., Güzel, K., & Möhring, H.-C. (2024). Vision-based Process Monitoring in Additive Manufacturing. https://www.ifsw.uni-stuttgart.de/slt/presentations2024
    18. Grimm, C., Menze, C., Saelzer, J., Sauer, F., Eisseler, R., Möhring, H.-C., Schulze, V., Zabel, A., & Uhlmann, E. (2024). Reproducibility analysis for different numerical models and experimental setups in dry orthogonal cutting of AISI 4140 steel. Procedia CIRP, 128, 650–655. https://doi.org/10.1016/j.procir.2024.04.018
    19. Wolf, J., Reeber, T., Bandaru, N. K., Dienwiebel, M., & Möhring, H.-C. (2024). Transient Wear Modelling of Coated Cutting Tools. Procedia CIRP, 130, 1827–1831. https://doi.org/10.1016/j.procir.2024.10.323

  3. 2023

    1. Palalić, M., Bieg, F., Maucher, C., Güzel, K., & Möhring, H.-C. (2023). Intelligent additive‐subtractive manufacturing for resilient production.
    2. Jaquemod, A., Güzel, K., & Möhring, H.-C. (2023). The influence of high cutting speeds on cutting forces, surface roughness and tool wearin the milling process of wood.
    3. Storchak, M., Stehle, T., & Möhring, H.-C. (2023). Numerical Modeling of Cutting Characteristics during Short Hole Drilling: Modeling of Kinetic Characteristics. Journal of Manufacturing and Materials Processing, 7, Article 6. https://doi.org/10.3390/jmmp7060195
    4. Ramme, J., Reeber, T., Rapp, M., & Möhring, H.-C. (2023). Process Stability Monitoring - Potential of Internal Control Data for Drilling Processes in the Aerospace Industry. 57–64.
    5. Bieg, F., Scheider, D., Kledwig, C., Maucher, C., Möhring, H.-C., & Reisacher, M. (2023). Development of a laser preheating concept for directed energy deposition. In Journal of Laser Applications (No. 4; Vol. 35). Laser Institute of America. https://doi.org/10.2351/7.0001124
    6. Derbas, M., Frömel-Frybort, S., Laaber, C., Möhring, H.-C., & Riegler, M. (2023). Supervised classification of wood species during milling based on extracted cut events from ultrasonic air-borne acoustic signals. Wood Material Science &Amp; Engineering, 18, Article 6. https://doi.org/10.1080/17480272.2023.2214118
    7. Riegler, M., Derbas, M., Jaquemod, A., Frömel-Frybort, S., Güzel, K., & Möhring, H.-C. (2023). Machine Learning for Predicting Wood Properties during Milling.
    8. Bleicher, F., Biermann, D., Drossel, W.-G., Möhring, H.-C., & Altintas, Y. (2023). Sensor and actuator integrated tooling systems. CIRP Annals Manufacturing Technology, 72, Article 2. https://doi.org/10.1016/j.cirp.2023.05.009
    9. Gutsche, D., Reeber, T., Georgi, P., & Möhring, H.-C. (2023). Cross-Machine Comparison of the Usability of Internal Machine Control Data for Process Monitoring in Machining Applications. Proceedings of the 13th Congress of the German Academic Association for Production Technology (WGP), 124–132. https://doi.org/10.1007/978-3-031-47394-4_13
    10. Güzel, K., & Möhring, H.-C. (2023). High-speed cutting of wood material.
    11. Jaquemod, A., Güzel, K., & Möhring, H.-C. (2023). Influence of Minimum Quantity Lubrication on Tool Temperature and Wear in Wood Machining. https://doi.org/10.1007/978-3-031-47394-4
    12. Derbas, M., Jaquemod, A., Frömel-Frybort, S., Güzel, K., Möhring, H.-C., & Riegler, M. (2023). Multisensor data fusion and machine learning to classify wood products and predict workpiece characteristics during milling. CIRP Journal of Manufacturing Science and Technology, 47, 103–115. https://doi.org/10.1016/j.cirpj.2023.09.003
    13. Maucher, C., Kang, Y., Bechler, S., Ruf, M., Steeb, H., Möhring, H.-C., & Hampp, F. (2023). Towards Bespoke Gas Permeability by Functionally Graded Structures in Laser-Based Powder Bed Fusion of Metals. SSRN eLibrary. https://doi.org/10.2139/ssrn.4550785
    14. Richter, M., Khalifa, O., Güzel, K., & Möhring, H.-C. (2023). Calibration of a strain gauge-equipped force measuring unit using machine learning algorithms. Procedia CIRP, 118, 181–186. https://doi.org/10.1016/j.procir.2023.06.032
    15. Feng, Q., Maier, W., Braun, S., & Möhring, H.-C. (2023). Dynamic modeling of the workpiece-fixture contact behavior for intelligent fixture design. Procedia CIRP, 119, Article 119. http://dx.doi.org/10.1016/j.procir.2023.02.126
    16. Feng, Q., Maier, W., Braun, S., & Möhring, H.-C. (2023). Detection and Identification of Nonlinear Contact Dynamics at Workpiece Clamping Positions. Journal of Machine Engineering, 1, Article 23. https://doi.org/10.36897/jme/161718
    17. Tandler, T., Stehle, T., & Möhring, H.-C. (2023). A Study of Low-Frequency Vibration-Assisted Bandsawing of Metallic Parts. Journal of Machine Engineering. https://doi.org/10.36897/jme/166530
    18. Georgi, P., Möhring, H.-C., & Stehle, T. (2023). Fachvortrag: Ultraschallunterstütztes Schleifen metallischer Werkstoffe.
    19. Georgi, P., Möhring, H.-C., & Stehle, T. (2023). Ultraschallunterstütztes Schleifen metallischer Werkstoffe.
    20. Maucher, C., Kordmann, L., & Möhring, H.-C. (2023). Design Rules for the Additive-Subtractive Process Chain. Procedia CIRP, 119, 1115–1121. https://doi.org/10.1016/j.procir.2023.03.153
    21. Tandler, T., Hirth, T., Eisseler, R., Stehle, T., & Möhring, H.-C. (2023). Einsatz von KI bei der Prozessvorhersage für Bandsägen/Use of AI in process prediction for band saws – Artificial intelligence in predicting process forces in band sawing. Wt Werkstattstechnik Online, 113, Article 01–02. https://doi.org/10.37544/1436-4980-2023-01-02-33

  4. 2022

    1. Maier, W., Rothmund, J., Möhring, H.-C., Dang, P.-D., Hoffarth, E., Zinn, B., & Wyrwal, M. (2022). Experiencing the structure and features of a machine tool with mixed reality. Procedia CIRP, 106, 244–249. https://doi.org/10.1016/j.procir.2022.02.186
    2. Jaquemod, A., Güzel, K., & Möhring, H.-C. (2022). Investigation of the Effect of Minimum Quantity Lubrication on the Machining of Wood. In LectureNotes in Production Engineering. German Academic Association for Production Technology (WGP).
    3. Ramme, J., Wegert, R., Guski, V., Schmauder, S., & Möhring, H.-C. (2022). Development of a Multi-Sensor Concept for Real-Time Temperature Measurement at the Cutting Insert of a Single-Lip Deep Hole Drilling Tool. Applied sciences, 12, Article 14. https://doi.org/10.3390/app12147095
    4. Güzel, K., Jaquemod, A., Stehle, T., & Möhring, H.-C. (2022). Influence of minimum quantity lubrication on surface quality during circular sawing of wood (No. 1/2). 112, Article 1/2. https://doi.org/doi.org/10.37544/1436-4980-2022-01-02
    5. Rapp, M., Schneider, M., Gauggel, C., & Möhring, H.-C. (2022). Advances in the machining finishing of ceramic composite components for aerospace applications. SSRN Electronic Journal.
    6. Schneider, M., Rapp, M., Gauggel, C., Pudłowski, M., & Möhring, H.-C. (2022). Machinability of C/C-SiC Ceramics for Components in High-Temperature Applications. Proceedings of the Machining Innovations Conference for Aerospace Industry (MIC) 2021, 21. https://ssrn.com/abstract=3942458 or http://dx.doi.org/10.2139/ssrn.3942458
    7. Möhring, H.-C., & Georgi, P. (2022). Surface-oriented process control based on a sensory milling tool.
    8. Menze, C. J., Reeber, T., Möhring, H.-C., Stegmann, J., & Kabelac, S. (2022). Modelling of sawing processes with internal coolant supply. Manufacturing letters, 32, Article April. https://doi.org/10.1016/j.mfglet.2022.04.006
    9. Möhring, H.-C., Becker, D., Maucher, C., Eisseler, R., & Ringger, J. (2022). Influence of the support structure on the bandsawing process when separating LPBF components from the building platform. Journal of Machine Engineering. https://doi.org/10.36897/jme/151498
    10. Maucher, C., Cera, P., & Möhring, H.-C. (2022). Quantification and Surface Analysis on Blasting of PBF-LB Additively Manufactured Components. Procedia CIRP, 108, 560–565. https://doi.org/10.1016/j.procir.2022.03.088
    11. Möhring, H.-C., & Georgi, P. (2022). Technical presentation: Surface-oriented process control based on a sensory milling tool.
    12. Wegert, R., & Möhring, H.-C. (2022). Prozessregelung beim Einlippentiefbohren.
    13. Wegert, R., Tandler, T., Badie, R., Eisseler, R., Möhring, H.-C., Guski, V., & Schmauder, S. (2022). Prozessregelung beim Einlippentiefbohren. WT WerkstattsTechnik, 11/12, 750–756. https://doi.org/10.37544/1436-4980-2022-11-12-24
    14. Feng, Q., Maier, W., & Möhring, H.-C. (2022). Application of machine learning to optimize process parameters in fused deposition modeling of PEEK material. Procedia CIRP, 107, 1–8. https://doi.org/10.1016/j.procir.2022.04.001
    15. Guski, V., Wegert, R., Schmauder, S., & Möhring, H.-C. (2022). Correlation between subsurface properties, the thermo-mechanical process conditions and machining parameters using the CEL simulation method. Procedia CIRP, Article 108. https://doi.org/doi.org/10.1016/j.procir.2022.03.021
    16. Schneider, M., Meier, V., Güzel, K., Stehle, T., & Möhring, H.-C. (2022). Augmented Reality-Unterstützung zur Umsetzung der Digitalisierung. HOB - Die Holzbearbeitung, 69, 18–21.
    17. Schneider, M., Finckh, H., Sirtautas, J., Häusler, A., Stehle, T., Dinkelmann, A., Fritz, F., Möhring, H.-C., & Gresser, G. T. (2022). Leichte Werkzeuge für die Holzbearbeitung – Entwicklung hochdynamisch belastbarer leichter Werkezuggrundkörper. Wt Werkstattstechnik Online, 12, 182–190.
    18. Maucher, C., Gutsche, D., & Möhring, H.-C. (2022). Investigation on anisotropic behavior of additively manufactured maraging steel during orthogonal cutting. Procedia CIRP, 113, 294–300. https://doi.org/10.1016/j.procir.2022.09.162

  5. 2021

    1. Möhring, H.-C., Eschelbacher, S., & Georgi, P. (2021). Machine learning approaches for real-time monitoring and evaluation of surface roughness using a sensory milling tool. Procedia CIRP.
    2. Feng, Q., Maier, W., Stehle, T., & Möhring, H.-C. (2021). Optimization of a clamping concept based on machine learning. Production Engineering. https://doi.org/10.1007/s11740-021-01073-z
    3. Tandler, T., Becker, D., Eisseler, R., Stehle, T., & Möhring, H.-C. (2021). Effekt der Sägekinematik auf die Prozesseffizienz/Kinematic variation with a circular sawbalde process. Wt Werkstattstechnik Online, 111, Article 01–02. https://doi.org/10.37544/1436-4980-2021-01-02-6
    4. Meier, V., Schneider, M., Güzel, K., Stehle, T., & Möhring, H.-C. (2021). Bearbeitungsmaschinen twittern. HOB - Die Holzbearbeitung, 68, 44–46.
    5. Maucher, C., Werkle, K. T., & Möhring, H.-C. (2021). In-Situ defect detection and monitoring for laser powder bed fusion using a multi-sensor build platform. Procedia CIRP, 104, 146–151. https://doi.org/10.1016/j.procir.2021.11.025
    6. Menze, C., Güzel, K., Stojanovic, A., Stehle, T., & Möhring, H.-C. (2021). Entwicklung und Erprobung eines Heißdrahtschneidaggregats für einen Industrieroboter. WT WerkstattsTechnik, Article 1/2.
    7. Menze, C. J., Wegert, R., Reeber, T., Erhardt, F., Möhring, H.-C., Stegmann, J., & Kabelac, S. (2021). Numerical Methods for the Simulation of Segmented Chips and Experimental Validation in Machining of TI-6AL-4V. MM Science Journal, 2021, Article November. https://doi.org/10.17973/mmsj.2021_11_2021152
    8. Schneider, M., Rapp, M., Gauggel, C., Pudłowski, M., & Möhring, H.-C. (2021). Machinability of C/C-SiC Ceramics for Components in High-Temperature Applications. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3942458
    9. Teich, H., Maucher, C., & Möhring, H.-C. (2021). Influence of LPBF Parameters and Strategies on Fine Machining of Pre-Built Bores. Journal of Machine Engineering, 91–100. https://doi.org/10.36897/jme/133344
    10. Schneider, M., Rapp, M., Gauggel, C., Pudłowski, M., & Möhring, H.-C. (2021). Machinability of C/C-SiC Ceramics for Components in High-Temperature Applications. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3942458
    11. Maucher, C., Teich, H., & Möhring, H.-C. (2021). Improving machinability of additively manufactured components with selectively weakened material. Production Engineering, 15, Article 3. https://doi.org/10.1007/s11740-021-01038-2
    12. Schneider, M., Meier, V., Güzel, K., Stehle, T., & Möhring, H.-C. (2021). IoT zur Überwachung der Staubbelastung. HOB - Die Holzbearbeitung, 68, 42–45.
    13. Georgi, P., Eschelbacher, S., & Möhring, H.-C. (2021). Utilization of machine learning approaches for tool wear detection and prediction in the circular sawing process of metallic materials.

  6. 2020

    1. Menze, C., Zizelmann, C., Schneider, M., Güzel, K., & Möhring, H.-C. (2020). Numerical Modelling of the Aeroacoustic and Flow Behaviour of Chip Fans. Lecture Notes in Production Engineering, 315–323. https://doi.org/10.1007/978-3-662-62138-7_32
    2. Güzel, K., Stehle, T., & Möhring, H.-C. (2020). Simulationsgestützte Optimierung des aeroakustischen Verhaltens von Kreissägeblättern. Werkstattstechnik Online, Article 1/2. https://www.werkstattstechnik.de/wt/currentarticle.php?dataarticle_id=92630
    3. Meier, V., Schneider, M., Güzel, K., Stehle, T., & Möhring, H.-C. (2020). IoT-Plattform für die Holzbearbeitung. HOB - Die Holzbearbeitung, Article 11/12.
    4. Palalić, M., Möhring, H.-C., Maier, W., Gonzalez de Mendoza, A., & Riemeier, F. (2020). Multiaxial Force Platform with Disturbance Compensation for Machine Tools. Journal of Machine Engineering, 20, Article 3. http://jmacheng.not.pl/Multiaxial-Force-Platform-with-Disturbance-Compensation-for-Machine-Tools,127105,0,2.html
    5. Wegert, R., Guski, V., Möhring, H.-C., & Schmauder, S. (2020). Determination of thermo-mechanical quantities with a sensor-integrated tool for single lip deep hole drilling. Procedia Manufacturing, 52, 73–78. https://doi.org/10.1016/j.promfg.2020.11.014
    6. Georgi, P., Eschelbacher, S., Stehle, T., & Möhring, H.-C. (2020). Erfahrungen mit alternativen Kraftmessungen. Werkstattstechnik online, Article 1/2. https://www.werkstattstechnik.de/wt/currentarticle.php?dataarticle_id=92639
    7. Möhring, H.-C., Eschelbacher, S., & Georgi, P. (2020). Online monitoring of the workpiece surface with a sensor integrated end-milling tool.
    8. Möhring, H.-C., Eschelbacher, S., & Georgi, P. (2020). Technical presentation: Online monitoring of the workpiece surface with a sensor integrated end-milling tool.
    9. Möhring, H.-C., Werkle, K., & Maier, W. (2020). Process monitoring with a cyber-physical cutting tool. Procedia Cirp, Vol. 93, 1466–1471. https://doi.org/10.1016/j.procir.2020.03.034
    10. Schneider, M., Stehle, T., & Möhring, H.-C. (2020). Ermittlung der Staubemissionen an Holz-Bearbeitungsmaschinen. Wt Werkstattstechnik Online, 110, 64–69.
    11. Werkle, K. T., Maier, W., Mayer, S., & Möhring, H.-C. (2020). Additive manufacturing of sensors - printing of conductor paths in loaded structures. Euspen’s 20th International Conference & Exhibition, 20155, 4. https://www.euspen.eu/resource/additive-manufacturing-of-sensors-printing-of-conductor-paths-in-loaded-damping-structures/
    12. Möhring, H.-C., Eschelbacher, S., & Georgi, P. (2020). Fundamental investigation on the correlation between surface properties and acceleration data from a sensor integrated milling tool. Procedia Manufacturing - 5th International Conference on System-Integrated Intelligence, 52, 79–84. https://doi.org/10.1016/j.promfg.2020.11.015

  7. 2019

    1. Möhring, H.-C., Eschelbacher, S., Güzel, K., Kimmelmann, M., Schneider, M., Zizelmann, C., Häusler, A., & Menze, C. (2019). En route to intelligent wood machining - Current Situation and future perspectives. Journal of Machine Engineering, 19, Article 4. http://www.not.pl/wydawnictwo/2019JOM/V4/1_MOHRING.pdf
    2. Menze, C., Güzel, K., Stehle, T., Möhring, H.-C., Königs, M., Heidemann, R., & Schütz, A. (2019). Digitale Werkstatt und Kollege Roboter unterstützen das Handwerk. HOB - Die Holzbearbeitung, Article 11.
    3. Möhring, H.-C., Stehle, T., & Schneider, M. (2019). Lightweight machine housings for dynamic and efficient production processes. Journal of Machine Engineering, 19, Article 2. https://doi.org/10.5604/01.3001.0013.2350
    4. Möhring, H. C., Stehle, T., Dobrinski, A., & Mazey, R. (2019). Bogenverzahnungen für Zahnradpumpen. Wt Werkstattstechnik Online, 109 (2019), Article Heft 1/2.
    5. Eschelbacher, S., Duntschew, J., & Möhring, H.-C. (2019). Recognition of wood and wood-based materials during machining using acoustic emission. Production at the Leading Edge of Technology.
    6. Werkle, K. T., Maier, W., & Möhring, H.-C. (2019). Additive manufacturing for intelligent lightweight tools. In J. P. Wulfsberg, W. Hintze, & BA. Behrens (Eds.), Production at the leading edge of technology (pp. 269–275). Springer Vieweg. https://doi.org/10.1007/978-3-662-60417-5_27
    7. Möhring, H.-C., Eisseler, R., & Weiland, S. (2019). Mit Einzahntests schneller zu neuen Sägewerkzeugen. Forscher der Universität Stuttgart sorgen für Zeiteinsparungen bei Standzeituntersuchungen. Mav, Article 1/2.

  8. 2018

    1. Merz, S., Maier, W., Baumann, F., Spiller, Q., Möhring, H.-C., & Fleischer, J. (2018). 3D-Print-Cloud Baden-Württemberg - Eine offene Plattform für die Prozesskette der Additiven Fertigung. wt-online, Band 108, Article 7/8.
    2. Möhring, H.-C., Fleischer, J., Maier, W., Spiller, Q., Baumann, F., & Merz, S. (2018). Die additive Fertigung als vollständige Prozesskette auf der Online Plattform 3D-Print-Cloud Baden-Württemberg (P. Hoyer, C. Leyens, T. Niendorf, V. Ploshikhin, V. Schulze, & G. Witt, eds.; pp. 84–89). DGM.
    3. Güzel, K., Talpeanu, D., Kimmelmann, M., & Möhring, H.-C. (2018). Potentiale in der Bohrbearbeitung von CFK-Aluminium-Stacks imt plasmageschäften Bohrwerkzeugen. Wt Werkstatttechnik Online, 108, Article 1/2.
    4. Fleischer, J., Teti, R., Lanza, G., Mativenga, P., Möhring, H.-C., & Caggiano, A. (2018). Composite materials parts manufacturing. CIRP Annals - Manufacturing Technology, 67, Article 2.
    5. Möhring, H.-C., Stehle, T., Güzel, K., & Zizelmann, C. (2018). Numerical flow simulation of rotating circular saw blades for the investigation of sound generation mechanisms. 18.
    6. Maier, W., Möhring, H.-C., & Werkle, K. (2018). Tools 4.0 – Intelligence starts on the cutting edge. Procedia Manufacturing, 24 (2018), Article 24 2018. https://doi.org/10.1016/j.promfg.2018.06.024
    7. Schneider, M., Stehle, T., & Möhring, H.-C. (2018). Absaugung von Span- und Staubpartikeln, Entwicklung eines Prozesses zur Bewertung des Erfassungsgrades bei Absaugeinrichtungen. Wt Werkstattstechnik Online, 108, Article 1/2.
    8. Möhring, H.-C., Maier, W., & Werkle, K. (2018). Increasing the Accuracy of an Intelligent Milling Tool with Integrated Sensors. european society for precision engineering and nanotechnology, 18th International Conference & Exhibition.
    9. Eisseler, R., Drewle, K., Grötzinger, K. C., & Möhring, H.-C. (2018). Using an Inverse Cutting Simulation-Based Method to Determine the Johnson-Cook Material Constants of Heat-Treated Steel. Procedia CIRP, 77, 26–29. https://doi.org/10.1016/j.procir.2018.08.198
    10. Möhring, H. C., Kushner, V., Storchak, M., & Stehle, T. (2018). Temperature calculation in cutting zones. CIRP Annals (On-Line).
    11. Möhring, H.-C., Kimmelmann, M., Eschelbacher, S., Güzel, K., & Gauggel, C. (2018). Process monitoring on drilling fiber-reinforced plastics and aluminum stacks using acoustic emissions. 18. https://www.sciencedirect.com/science/article/pii/S2351978918313234
    12. Güzel, K., Talpeanu, D., Kimmelmann, M., & Möhring, H.-C. (2018). Potentiale in der Bohrbearbeitung von CFK-Aluminium-Stacks mit plasmageschärften Bohrwerkzeugen. Wt Werkstatttechnik Online, Article 108.
    13. Möhring, H.-C., Stehle, T., & Schneider, M. (2018). Holzstaubemissionen an CNC-Bearbeitungszentren.

  9. 2017

    1. Albrecht, D., & Möhring, H.-C. (2017). Potentials for the optimization of sawing processes using the example of bandsawing machines. Procedia Manufacturing.
    2. Möhring, H.-C., Maier, W., & Grötzinger, K. (2017). Kontruktion und Designmerkmale additiv gefertigter Bauteile–Teileanzahl reduziert und Flexibilität erhöht. Mav- Innovation in Der Spanenden Fertigung, Article 10–2017.
    3. Möhring, H. C. (2017). Composites in Production Machines. Procedia CIRP, 66, 2–9.
    4. Wegener, K., Mayr, J., Merklein, M., Behrens, B.-A., Aoyama, T., Sulitka, M., Fleischer, J., Groche, P., Kaftanoglu, B., Jochum, N., & Möhring, H.-C. (2017). Fluid elements in machine tools. In CIRP (Ed.), CIRP Annals (No. 2; Vol. 66, pp. 611–634). CIRP.
    5. Nguyen, L. T., & Möhring, H.-C. (2017). Stiffness and Damping Properties of a Swing Clamp: Model and Experiment. 58, 299–304.

  10. 2016

    1. Möhring, H.-C., & Wiederkehr, P. (2016). Intelligent Fixtures for High Performance Machining. In CIRP (Ed.), Procedia CIRP (Vol. 46, pp. 383–390). CIRP.
    2. Möhring, H.-C., Nguyen, Q. P., Kuhlmann, A., Lerez, C., Nguyen, L. T., & Misch, S. (2016). Intelligent Tools for Predictive Process Control. In CIRP (Ed.), Procedia CIRP (Vol. 57, pp. 539–544). CIRP.

  11. 2015

    1. Lerez, C., Siebrecht, T., Möhring, H.-C., & Kersting, P. (2015, December). Entwicklung eines intelligenten Werkstückhalters für die Fertigung dünnwandiger Bauteile.
    2. König, A., Möhring, H.-C., & Gessler, W. (2015, December). Experimentelle Analyse von Mineralguss-Proben zur Parametrisierung von mechanischen und thermischen FE-Simulationsmodellen für die Auslegung von Mineralguss-Stahl-Hybridstrukturen eines modularen Vorrichtungsbaukastens.
    3. Möhring, H.-C., Brecher, C., Abele, E., Fleischer, J., & Bleicher, F. (2015). Materials in machine tool structures. In CIRP (Ed.), CIRP Annals (No. 2; Vol. 64, pp. 725–748). CIRP.
    4. Leopold, M., Hense, R., Möhring, H.-C., & Kersting, P. (2015, December). Intelligente Werkstückspannsysteme für die verzugsfreie Fertigung dünnwandiger Aluminiumbauteile.

Professional and Scientific Career

since 2019          Dean of the Faculty of Engineering Design, Production Engineering and Automotive Engineering

since 2017          Chairman of the Examining Board for Technical Education, University of Stuttgart

since 2017          University Professor for Machine Tools, University of Stuttgart, Director of the Institute for Machine Tools (IfW), University of Stuttgart

2012 – 2017        University Professor at the Otto-von-Guericke University Magdeburg, Chair of Production Facilities

2005 – 2012        Chief Engineer at the IFW of the Leibniz University Hannover

1993 – 1999        Student of Mechanical Engineering at the Leibniz University Hannover; Dipl.-Ing.

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