Acta Mechanica Slovaca 2022, 26(4):44-53 | DOI: 10.21496/ams.2022.019

Monitoring the Performance of the Drive Mechanisms During CNC Milling

Michal Demko1, Peter Ižol1, Marek Vrabeľ2, Jozef Brindza2, Ján Džugan3
1 Technical University of Košice, Faculty of Mechanical Engineering, Department of Computer Aided Production, Mäsiarska 74, 040 01 Košice, Slovakia
2 Technical University of Košice,Faculty of Mechanical Engineering, Prototyping and Innovation Centre, Park Komenského 12A, 040 01 Košice, Slovakia
3 Continental Automotive Systems Slovakia s.r.o, Production Department PR1, Cesta ku Continentálu 8950/ 1, 960 01 Zvolen, Slovakia

The article deals with a monitoring system designed for the needs of a specific production plant. Its primary purpose is to provide online information about ongoing production processes at monitored workplaces. The system will make it possible to monitor the usability of the machines and the load on individual machine elements to increase production efficiency and prevent machine breakdowns. Furthermore, it will allow to monitor the load on the tool and predict its wear in order to prevent irreversible damage and the production of scrap. To test the applicability of the system on a milling machine, a sample was designed, the elements of which were produced in two ways - HPC and trochoidal milling. With these methods of milling, different manifestations of the tool load were assumed. The experiments proved the functionality of the system. The method of transmission, recording and storage of data has proven to be fully functional. The additional results were knowledge of machine load during both milling methods.

Keywords: signal processing, CNC machine, OPC UA client, HPC milling, iMachining

Received: August 17, 2022; Revised: October 27, 2022; Accepted: November 7, 2022; Published: December 15, 2022  Show citation

ACS AIP APA ASA Harvard Chicago Chicago Notes IEEE ISO690 MLA NLM Turabian Vancouver
Demko, M., Ižol, P., Vrabeľ, M., Brindza, J., & Džugan, J. (2022). Monitoring the Performance of the Drive Mechanisms During CNC Milling. Acta Mechanica Slovaca, 26(4), 44-53. doi: 10.21496/ams.2022.019
Share...
Download citation
  • BibTeX (.bib)
  • Bookends (.ris)
  • EasyBib (.ris)
  • EndNote (.enw)
  • EndNote 8 (.xml)
  • ISI WoS (.isi)
  • Medlars (.medlars)
  • Mendeley (.ris)
  • MODS (.xml)
  • Papers (.ris)
  • RefWorks (.txt)
  • RefManager (.ris)
  • RIS (.ris)
  • MS Word (.xml)
  • Zotero (.ris)
    • Open full article

    References

    1. Baur, M., Albertelli, P., Monno, M.A. (2020). Review of prognostics and health management of machine tools. The International Journal of Advanced Manufacturing, 107, 2843-2863. doi:10.1007/s00170-020-05202-3. Go to original source...
    2. Ahmad, M.I., Yusof, Y., Daud, M.E., Latiff, K., Kadir, A.Z.A.K., Siaf, Y. (2020). Machine monitoring system: a decade in review. The International Journal of Advanced Manufacturing Technology, 108, 3645-3659. doi:10.1007/s00170-020-05620-3. Go to original source...
    3. Mohamed, A., Hassan, M., M'Saoubi, R., Attia, H. (2022). Tool condition monitoring for High-Performance Machining systems - a review. Sensors, 22, 2206. doi: 10.3390/s22062206. Go to original source...
    4. Mohanraj, T., Shankar, S., Rajasekar, R., Sakthivel, N.R., Pramanik, A. (2020). Tool condition monitoring techniques in millingprocess - a review. Journal of Material Research and Technology, 9, 1032-1042. doi:10.1016/j.jmrt.2019.10.031. Go to original source...
    5. Miura, K., Bergs, T. A (2019). Method of Cutting Power Monitoring for Feed Axes in Milling by Power Measurement Device. IFAC PapersOnLine, 52-13, 2471-2476. doi:10.1016./j.facol.2019.11.577. Go to original source...
    6. Brecher Ch., Quintana, G., Rudolf, T., Ciurana, J. (2011). Use of NC kernel data for surface roughness monitoring in milling operations. The International Journal of Advanced Manufacturing Technology, 53, 953-962. doi: 10.1007/s00170-010-2904-z. Go to original source...
    7. 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, 102, 264-269. doi: 10.1016/j.procir.2021.09.045. Go to original source...
    8. Müller, J., Michos, G., Koch L., Hermann, M., Hubert, M., Franke, J. (2016). Process and energy data acquisition on machining center and individual machine components. Applied Mechanics and Materials, 856, 123-130. doi:10.4028/www.scientific.net/amm.856.123. Go to original source...
    9. Martins, A., Lucas, J., Costelha, H., Neves, C. (2021) Developing an OPC UA Server for CNC machines. Procedia Computer Science, 180, 561-570. doi:10.1016/j.procs.2021.01.276. Go to original source...
    10. Lu, Y., Xu, X., Wang, L. (2020). Smart manufacturing process and system automation - a critical review of the standards and envisioned scenarios. Journal of Manufacturing Systems, 56, 312-325. doi:10.1016/j.jmsy.2020.06.010. Go to original source...
    11. Ceratizit group. MonsterMill - Plunge milling cutter with corner radius, from https://cuttingtools.ceratizit.com/gb/en/products/52614100.html, date of access 26.5.2022.
    12. Ceratizit group. CircularLine - End milling cutter from https://cuttingtools.ceratizit.com/gb/en/products/53585100.html, date of access 26.5.2022.

    This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.


    Return to the content