Dieses Bild zeigt Hans-Christian Möhring

Hans-Christian Möhring

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

Direktor des Instituts
Institut für Werkzeugmaschinen
Institutsleitung

Kontakt

+49 711 685 83773
 +49 711 685 70040

Holzgartenstr. 17
70174 Stuttgart
Deutschland
Raum: 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. The International Journal of Advanced Manufacturing Technology. https://doi.org/10.1007/s00170-024-13960-7
    2. 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
    3. 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
    4. 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
    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. 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
    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. 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
    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. 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
    15. 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
    16. Palalić, M., Güzel, K., & Möhring, H.-C. (2024). Vision-based Process Monitoring in Additive Manufacturing. https://www.ifsw.uni-stuttgart.de/slt/presentations2024
    17. 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
    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. 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
    2. 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.
    3. 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
    4. 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
    5. Riegler, M., Derbas, M., Jaquemod, A., Frömel-Frybort, S., Güzel, K., & Möhring, H.-C. (2023). Machine Learning for Predicting Wood Properties during Milling.
    6. 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
    7. 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
    8. Palalić, M., Bieg, F., Maucher, C., Güzel, K., & Möhring, H.-C. (2023). Intelligent additive‐subtractive manufacturing for resilient production.
    9. 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.
    10. Güzel, K., & Möhring, H.-C. (2023). High-speed cutting of wood material.
    11. 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
    12. 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
    13. 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
    14. 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
    15. 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
    16. 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
    17. Georgi, P., Möhring, H.-C., & Stehle, T. (2023). Fachvortrag: Ultraschallunterstütztes Schleifen metallischer Werkstoffe.
    18. Georgi, P., Möhring, H.-C., & Stehle, T. (2023). Ultraschallunterstütztes Schleifen metallischer Werkstoffe.
    19. 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
    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. 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
    2. 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
    3. 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).
    4. 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
    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., 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
    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., & Georgi, P. (2022). Surface-oriented process control based on a sensory milling tool.
    10. 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
    11. 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
    12. Möhring, H.-C., & Georgi, P. (2022). Technical presentation: Surface-oriented process control based on a sensory milling tool.
    13. Wegert, R., & Möhring, H.-C. (2022). Prozessregelung beim Einlippentiefbohren.
    14. 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
    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. 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
    17. 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.
    18. 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.

  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. 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
    8. 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
    9. 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
    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. Schneider, M., Meier, V., Güzel, K., Stehle, T., & Möhring, H.-C. (2021). IoT zur Überwachung der Staubbelastung. HOB - Die Holzbearbeitung, 68, 42–45.
    12. 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
    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. 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
    6. Möhring, H.-C., Eschelbacher, S., & Georgi, P. (2020). Online monitoring of the workpiece surface with a sensor integrated end-milling tool.
    7. 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
    8. Schneider, M., Stehle, T., & Möhring, H.-C. (2020). Ermittlung der Staubemissionen an Holz-Bearbeitungsmaschinen. Wt Werkstattstechnik Online, 110, 64–69.
    9. Möhring, H.-C., Eschelbacher, S., & Georgi, P. (2020). Technical presentation: Online monitoring of the workpiece surface with a sensor integrated end-milling tool.
    10. 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
    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. 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.
    3. 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.
    4. 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.
    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. 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.
    8. 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.
    9. 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
    10. 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.
    11. 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
    12. Möhring, H. C., Kushner, V., Storchak, M., & Stehle, T. (2018). Temperature calculation in cutting zones. CIRP Annals (On-Line).
    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.

Beruflicher und wissenschaftlicher Werdegang

seit 2019             Dekan der Fakultät für Konstruktions-, Produktions- und Fahrzeugtechnik

seit 2017             Vorsitzender des Prüfungsausschusses Technikpädagogik, Universität Stuttgart

seit 2017             Universitätsprofessur für Werkzeugmaschinen, Universität Stuttgart, Direktor des Instituts für Werkzeugmaschinen (IfW), Universität Stuttgart

2012 – 2017        Universitätsprofessor an der Otto-von-Guericke-Universität Magdeburg, Lehrstuhlleiter „Fertigungseinrichtungen“

2005 – 2012        Oberingenieur am IFW der Leibniz Universität Hannover

1993 – 1999        Studium Maschinenbau an der Leibniz Universität Hannover; Dipl.-Ing.

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