Concept of Integrating a Hybrid Thermal Error Compensation Into an Existing Machine Tool Control Architecture
1
Machine Tools Technology, Fraunhofer Institute for Machine Tools and Forming Technology IWU, Germany
2
IIoT Controls, Fraunhofer Institute for Machine Tools and Forming Technology IWU, Germany
3
Automation and Monitoring, Fraunhofer Institute for Machine Tools and Forming Technology IWU, Germany
4
Head of Production systems and factory automation, Fraunhofer Institute for Machine Tools and Forming Technology IWU, Germany
Submission date: 2024-04-16
Final revision date: 2024-09-02
Acceptance date: 2024-09-02
Online publication date: 2024-09-25
Publication date: 2024-10-17
Corresponding author
Alexander Geist
Machine Tools Technology, Fraunhofer Institute for Machine Tools and Forming Technology IWU, Germany
Machine Tools Technology, Fraunhofer Institute for Machine Tools and Forming Technology IWU, Germany
Journal of Machine Engineering 2024;24(3):32-46
KEYWORDS
TOPICS
ABSTRACT
Thermal error compensation via a numeric control (NC) system is a proven option for upgrading the precision of machine tools. The main advantage is the generally cost-effective application, as no changes to the machine design are necessary. Since modern machine tools are equipped with standard numeric controls along with additional functions and integrated temperature sensors in the machine, compensation methods such as a characteristic diagram (CD) based compensation can be implemented. To increase the applicability and reliability of this CD regression method, a hybrid model approach with a virtual thermo-elastic finite element (FE) machine model and a real-time computable structural model of a machine tool was developed. The structural model uses model order reduction to calculate the current load case in real-time using continuously recorded machine data (motor current, axis position, temperatures). It acts as a virtual monitoring application to check, whether the current machine condition still matches the current CD based prediction. If the current load case is not suitable to the active CDs or any other stored CDs, the generation of new CDs is automatically triggered. In this article, the integration of the hybrid compensation method using an FE model and a structural model of a machine tool is methodically demonstrated. The main focus is on the integration of different software and hardware architectures and their interaction.
REFERENCES (31)
1.
MAYR J., JEDRZEJEWSKI J., UHLMANN E., ALKAN DONMEZ M., KNAPP W., HÄRTIG F., et al; 2012, Thermal Issues in Machine Tools, CIRP Annals, 61/2, 771–91, https://doi.org/10.1016/j.cirp....
2.
PUTZ M., RICHTER C., REGEL J., BRÄUNIG M., 2018, Industrial Relevance and Causes of Thermal Issues in Machine Tools, Proceedings Conference on Thermal Issues in Machine Tools, 1, 127–39.
3.
GEBHARDT M; 2014, Thermal Behaviour and Compensation of Rotary Axes in 5-Axis Machine Tools, Ph.D. Thesis, ETH Zürich, Zürich.
4.
GROßMANN K., 2015, Thermo-Energetic Design of Machine Tools, Cham: Springer International Publishing.
5.
TSENG P.-C., 1997, A Real-Time Thermal Inaccuracy Compensation Method on a Machining Centre, Int. J. Adv. Manuf. Technol., 13/3, 182–190, https://doi:10.1007/BF01305870.
6.
MARWITZ J.A., THEISSEN N.A., BASSANTE M.K., FRIEDRICH C., HELLMICH A., ARCHENTI A., et al, 2022, Accuracy Assessment of Articulated Industrial Robots Using the Extended- and the Loaded-Double-Ball-Bar, Journal of Machine Engineering, https://doi.org/10.36897/jme/1....
7.
FRIEDRICH C., IHLENFELDT S., 2021, Model Calibration for a Rigid Hexapod-Based End-Effector with Integrated Force Sensors, MDPI Sensors, 21/10, https://doi:10.3390/s21103537.
8.
MARES M., HOREJS O., STRAKA M., SVEDA J., KOZLOK T., 2022, An Update of Thermal Error Compensation Model Via On-Machine Measurement, MM Science Journal, 22/5, https://doi.org/10.17973/MMSJ. 2022_12_2022150.
9.
DENKENA B., SCHARSCHMIDT K.-H., 2007, Kompensation Thermischer Verlagerungen, wt, 97/11-12, 913–937, https://doi:10.37544/1436-4980....
10.
LI Y., YU M., BAI Y., HOU Z., WU W., 2021, A Review of Thermal Error Modeling Methods for Machine Tools, APPLIED SCIENCES-BASEL, 11/11, 5216, https://doi.org/10.3390/app111....
11.
NAUMANN C., FICKERT A., PENTER L., GIßKE C., WENKLER E., GLÄNZEL J., et al., 2023, Evaluation of Thermal Error Compensation Strategies Regarding Their Influence on Accuracy and Energy Efficiency of Machine Tools, KOHL, H. et al., editors, Manufacturing Driving Circular Economy, Cham: Springer International Publishing, 157–165.
12.
WENG L., GAO W., ZHANG D., HUANG T., DUAN G., LIU T., et al; 2023, Analytical Modelling of Transient Thermal Characteristics of Precision Machine Tools and Real-Time Active Thermal Control Method, International Journal of Machine Tools and Manufacture, 186, 104003, https://doi.org/10.1016/j.ijma....
13.
ESS M., 2012, Simulation and Compensation of Thermal Errors of Machine Tools, ETH Zürich, Zürich.
14.
BLASER P., PAVLIČEK F., MORI K., MAYR J., WEIKERT S., WEGENER K., 2017, Adaptive Learning Control for Thermal Error Compensation of 5-Axis Machine Tools, Journal of Manufacturing Systems, 44, 302–309, https://doi.org/10.1016/j.jmsy....
15.
BLASER P., 2020, Adaptive Learning Control for Thermal Error Compensation, Ph.D. Thesis, ETH Zürich, Zürich.
16.
STOOP F., MAYR J., SULZ C., KAFTAN P., BLEICHER F., YAMAZAKI K., et al., 2023, Cloud-Based Thermal Error Compensation with a Federated Learning Approach, Precision Engineering, 79, 135–45. https://doi.org/ 10.1016/j.precisioneng.2022.09.013.
17.
STOOP F., MAYR J., SULZ C., BLEICHER F., WEGENER K., 2021, Fleet Learning of Thermal Error Compensation in Machine Tools, ETH Zurich.
18.
ZHU M., MENG Z., 2023, Full Compensation Method of Thermal Error of NC Machine Tool Based on Sequence Depth Learning, IJMTM, 37/2, 138–150, https://doi.org/10.1504/IJMTM.....
19.
ZIMMERMANN N., BÜCHI T., MAYR J., WEGENER K., 2022, Self-Optimizing Thermal Error Compensation Models with Adaptive Inputs Using Group-LASSO for ARX-Models, Journal of Manufacturing Systems, 64, 615–25, https://doi.org/10.1016/j.jmsy....
20.
GLÄNZEL J., KUMAR T.S., NAUMANN C., PUTZ M., 2019, Parameterization of Environmental Influences by Automated Characteristic Diagrams for the Decoupled Fluid and Structural-Mechanical Simulations, Journal of Machine Engineering, 19/1, 98–113, https://doi.org/10.5604/01.300....
21.
NAUMANN C., GLÄNZEL J., DIX M., IHLENFELDT S., KLIMANT P., 2022, Optimization of Characteristic Diagram Based Thermal Error Compensation Via Load Case Dependent Model Updates, Journal of Machine Engineering, https://doi.org/10.36897/jme/1....
22.
NAUMANN C., RIEDEL I., IHLENFELDT S., PRIBER U., 2016, Characteristic Diagram Based Correction Algorithms for the Thermo-Elastic Deformation of Machine Tools, Procedia CIRP, 41, 801–805, https://doi.org/10.1016/j.proc....
23.
IHLENFELDT S., NAUMANN C., PUTZ M., 2018, On the Selection and Assessment of Input Variables for the Characteristic Diagram Based Correction of Thermo-Elastic Deformations in Machine Tools, Journal of Machine Engineering, 18/4, 25–38, https://doi.org/10.5604/01.300....
24.
THIEM X., KAUSCHINGER B., IHLENFELDT S., 2019, Online Correction of Thermal Errors Based on a Structure Model, IJMMS,12/1, 49, https://doi.org/10.1504/IJMMS.....
25.
PUTZ M., IHLENFELDT S., KAUSCHINGER B., NAUMANN C., THIEM X., RIEDEL M., 2016, Implementation and Demonstration o Characteristic Diagram as Well as Structure Model Based Correction of Thermo-Elastic Tool Center Point Displacements, Journal of Machine Engineering, 16/3, 88–101.
26.
THIEM X., KAUSCHINGER B., IHLENFELDT S., 2017, Structure Model Based Correction of Thermally Induced Motion Errors of Machine Tools, Procedia Manufacturing, 14, 128–135, https://doi.org/10.1016/j.prom.... 2017.11.015.
27.
NAUMANN C., 2023, Kennfeldbasierte Korrektur Thermo-Elastischer Verformungen an Spanenden Werkzeugmaschinen, Dissertation, Technische Universität Chemnitz; Verlag Wissenschaftliche Scripten, Chemnitz.
28.
GEIST A., NAUMANN C., GLANZEL J., PUTZ M., 2023, Methodology for Determining Thermal Errors in Machine Tools by Thermo-Elastic Simulation in Connection with Thermal Measurement in a Climate Chamber, MM Science Journal, 2, https://doi.org/10.17973/MMSJ.....
29.
BEITELSCHMIDT M., GALANT A., GROßMANN K., KAUSCHINGER B., 2015, Innovative Simulation Technology for Real-Time Calculation of the Thermo-Elastic Behaviour of Machine Tools in Motion, AMM, 794, 363–370, https://doi.org/10.4028/www.sc....
30.
FRIEDRICH C., GEIST A., YAQOOB M.F., HELLMICH A., IHLENFELDT S., 2024, Correction of Thermal Errors in Machine Tools by a Hybrid Model Approach, APPLIED SCIENCES, 14/2, 671. https://doi.org/ 10.3390/app14020671.
31.
NAUMANN C., GEIST A., PUTZ M., 2023, Handling Ambient Temperature Changes in Correlative Thermal Error Compensation, Journal of Machine Engineering, 23/4, 43–63, https://doi.org/ 10.36897/jme/175397.
Share
RELATED ARTICLE
| eISSN: | 2391-8071 |
| ISSN: | 1895-7595 |
We process personal data collected when visiting the website. The function of obtaining information about users and their behavior is carried out by voluntarily entered information in forms and saving cookies in end devices. Data, including cookies, are used to provide services, improve the user experience and to analyze the traffic in accordance with the Privacy policy. Data are also collected and processed by Google Analytics tool (more).
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
