APPLICATION OF A COMPUTER TOOL MONITORING SYSTEM IN CNC MACHINING CENTRES

Damian KOLNY

dkolny@ath.bielsko.pl
University of Bielsko-Biala, Faculty of Mechanical Engineering and Computer Science, 43-309 Bielsko-Biała, Willowa 2 (Poland)

Dorota WIĘCEK


 University of Bielsko-Biala, Faculty of Mechanical Engineering and Computer Science, 43-309 Bielsko-Biała, Willowa 2 (Poland)

Paweł ZIOBRO


ZPT Industry | Automation | Research & Development | Innovations (Poland)

Martin KRAJČOVIČ


University of Zilina, Industrial Engineering Department, 010 26 Žilina, Univerzitná 1, (Slovakia)

Abstract

The article presents practical knowledge about production process optimisation as a result of implementing a specialized system monitoring the work of machining tools. It features complex results of the conducted research with use of dedicated equipment and software, whose unconventional application may appear to be an effective IT tool for taking operational and strategic decisions in the machining area. This results from the possibility of analysing the obtained data in both current and long-term perspective, and taking decisions on this basis, which significantly conditions the rationality of using this type of solutions.


Keywords:

current process control, tool wear monitoring system, process optimization

Addona, D. M. D., & Teti, R. (2013). Image data processing via neural networks for tool wear prediction. Procedia CIRP, 12, 252–257. https://doi.org/10.1016/j.procir.2013.09.044
DOI: https://doi.org/10.1016/j.procir.2013.09.044   Google Scholar

Barreiro, J., Fernández-Abia, A. I., González-Laguna, A., & Pereira, O. (2017). TCM system in contour milling of very thick-very large steel plates based on vibration and AE signals. Journal of Materials Processing Technology, 246, 144–157. https://doi.org/10.1016/j.jmatprotec.2017.03.016
DOI: https://doi.org/10.1016/j.jmatprotec.2017.03.016   Google Scholar

Jemielniak, K. (2002). Automatyczna diagnostyka stanu narzędzia i procesu skrawania. Warszawa: Oficyna Wydawnicza Politechniki Warszawskiej.
  Google Scholar

Jurko, J. (2007). Monitoring and Diagnosis of Drill Wear and the Thermodynamic Phenomenas of Material Removal by drilling of Stainless Steels. In: E.E. Gdoutos (Ed.) Experimental Analysis of Nano and Engineering Materials and Structures (vol. 37, 77–78). Dordrecht: Springer. https://doi.org/10.1007/978-1-4020-6239-1_37
DOI: https://doi.org/10.1007/978-1-4020-6239-1_37   Google Scholar

Kious, M., Ouahabi, A., Boudraa, M., Serra, R., & Cheknane, A. (2010). Detection process approach of tool wear in high speed milling. Measurement, 43, 1439–1446. https://doi.org/10.1016/j.measurement.2010.08.014
DOI: https://doi.org/10.1016/j.measurement.2010.08.014   Google Scholar

Kuljanic, E., & Sortino, M. (2005). TWEM a method based on cutting forces monitoring tool wear in face milling, Mach. Tools Manuf. J., 45, 29–34. https://doi.org/10.1016/j.ijmachtools.2004.06.016
DOI: https://doi.org/10.1016/j.ijmachtools.2004.06.016   Google Scholar

Kuryjański, R. (2011). Obróbka skrawaniem i obrabiarki. Warszawa: Expol.
  Google Scholar

Nouri, M., Fussell, B. K., Ziniti, B. L., & Linder, E. (2015). Real-time tool wear monitoring in milling using a cutting condition independent method. International Journal of Machine Tools and Manufacture, 89, 1–13. https://doi.org/10.1016/j.ijmachtools.2014.10.011
DOI: https://doi.org/10.1016/j.ijmachtools.2014.10.011   Google Scholar

Storch, B. (2001). Podstawy obróbki skrawaniem. Koszalin: Wydaw. Politechniki Koszalińskiej.
  Google Scholar

Więcek, D. (2013). Implementation of Artificial Intelligence in Estimating Prime Costs of Producing Machine Elements. Advances in Manufacturing Science and Technology, 37, 43–53. https://doi.org/10.2478/amst-2013-0004
DOI: https://doi.org/10.2478/amst-2013-0004   Google Scholar

Wittbrodt, P. (2014). Nadzorowanie i prognozowanie stanu narzędzi skrawających w procesie skrawania. Innowacje w Zarządzaniu i Inżynierii Produkcji (cz. 1, 833–834). Zakopane: Oficyna Wydawnicza Polskiego Towarzystwa Zarządzania Produkcją.
  Google Scholar

Download


Published
2017-12-30

Cited by

KOLNY, D. ., WIĘCEK, D. ., ZIOBRO, P., & KRAJČOVIČ, M. . (2017). APPLICATION OF A COMPUTER TOOL MONITORING SYSTEM IN CNC MACHINING CENTRES. Applied Computer Science, 13(4), 7–19. https://doi.org/10.23743/acs-2017-25

Authors

Damian KOLNY 
dkolny@ath.bielsko.pl
University of Bielsko-Biala, Faculty of Mechanical Engineering and Computer Science, 43-309 Bielsko-Biała, Willowa 2 Poland

Authors

Dorota WIĘCEK 

 University of Bielsko-Biala, Faculty of Mechanical Engineering and Computer Science, 43-309 Bielsko-Biała, Willowa 2 Poland

Authors

Paweł ZIOBRO 

ZPT Industry | Automation | Research & Development | Innovations Poland

Authors

Martin KRAJČOVIČ 

University of Zilina, Industrial Engineering Department, 010 26 Žilina, Univerzitná 1, Slovakia

Statistics

Abstract views: 104
PDF downloads: 6


License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

All articles published in Applied Computer Science are open-access and distributed under the terms of the Creative Commons Attribution 4.0 International License.