APPLICATION OF A COMPUTER TOOL MONITORING SYSTEM IN CNC MACHINING CENTRES
Damian KOLNY
dkolny@ath.bielsko.plUniversity 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 optimizationReferences
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
Authors
Damian KOLNYdkolny@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 ZIOBROZPT Industry | Automation | Research & Development | Innovations Poland
Authors
Martin KRAJČOVIČUniversity of Zilina, Industrial Engineering Department, 010 26 Žilina, Univerzitná 1, Slovakia
Statistics
Abstract views: 141PDF downloads: 11
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.
Most read articles by the same author(s)
- Damian KOLNY, Dawid KURCZYK, Józef MATUSZEK, COMPUTER SUPPORT OF ERGONOMIC ANALYSIS OF WORKING CONDITIONS AT WORKSTATIONS , Applied Computer Science: Vol. 15 No. 1 (2019)
- Martin KRAJČOVIČ, Patrik GRZNÁR, UTILISATION OF EVOLUTION ALGORITHM IN PRODUCTION LAYOUT DESIGN , Applied Computer Science: Vol. 13 No. 3 (2017)
- Dariusz PLINTA, Martin KRAJČOVIČ, APPLICATION OF THE AUGMENTED REALITY IN PRODUCTION PRACTICE , Applied Computer Science: Vol. 13 No. 2 (2017)
Similar Articles
- Damian GIEBAS, Rafał WOJSZCZYK, GRAPHICAL REPRESENTATIONS OF MULTITHREADED APPLICATIONS , Applied Computer Science: Vol. 14 No. 2 (2018)
- Grzegorz SUCHANEK, Roman FILIPEK, COMPUTATIONAL FLUID DYNAMICS (CFD) AIDED DESIGN OF A MULTI-ROTOR FLYING ROBOT FOR LOCATING SOURCES OF PARTICULATE MATTER POLLUTION , Applied Computer Science: Vol. 18 No. 3 (2022)
- Agnieszka ZACHCIAŁ, Andrzej JARDZIOCH, APPLICATION OF SIMULATION RESEARCH TO ANALYSE THE PRODUCTION PROCESS IN TERMS OF SUSTAINABLE DEVELOPMENT , Applied Computer Science: Vol. 18 No. 3 (2022)
- Donatien Koulla Moulla, Ernest Mnkandla, Alain Abran, SYSTEMATIC LITERATURE REVIEW OF IOT METRICS , Applied Computer Science: Vol. 19 No. 1 (2023)
- Isaac FLORES-HERNÁNDEZ, Edmundo BONILLA-HUERTA, Perfecto MALAQUIAS QUINTERO-FLORES, Oscar Atriano PONCE, José Crispín HERNÁNDEZ-HERNÁNDEZ, APPLYING INTELLIGENT TECHNIQUES FOR TALENT RECRUITMENT , Applied Computer Science: Vol. 15 No. 2 (2019)
- Maria TOMASIKOVA, Frantisek BRUMERČÍK, Aleksander NIEOCZYM, DESIGN AND DYNAMICS MODELING FOR ELECTRIC VEHICLE , Applied Computer Science: Vol. 13 No. 3 (2017)
- Marcin TOMCZYK, Barbara BOROWIK, Bohdan BOROWIK, IDENTIFICATION OF THE MASS INERTIA MOMENT IN AN ELECTROMECHANICAL SYSTEM BASED ON WAVELET–NEURAL METHOD , Applied Computer Science: Vol. 14 No. 2 (2018)
- Mohanad ABDULHAMID, Deng PETER, REMOTE HEALTH MONITORING: FALL DETECTION , Applied Computer Science: Vol. 16 No. 1 (2020)
- Marcin TOMCZYK, Anna PLICHTA, Mariusz MIKULSKI, APPLICATION OF IMAGE ANALYSIS TO THE IDENTIFICATION OF MASS INERTIA MOMENTUM IN ELECTROMECHANICAL SYSTEM WITH CHANGEABLE BACKLASH ZONE , Applied Computer Science: Vol. 15 No. 3 (2019)
- Manikandan SRIDHARAN, Delphin Carolina RANI ARULANANDAM, Rajeswari K CHINNASAMY, Suma THIMMANNA, Sivabalaselvamani DHANDAPANI, RECOGNITION OF FONT AND TAMIL LETTER IN IMAGES USING DEEP LEARNING , Applied Computer Science: Vol. 17 No. 2 (2021)
<< < 1 2 3 4 5 6 7 8 9 10 > >>
You may also start an advanced similarity search for this article.
