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: 167PDF downloads: 13
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
- Michał BIAŁY, Marcin SZLACHETKA, CRANK-PISTON MODEL OF INTERNAL COMBUSTION ENGINE USING CAD/CAM/CAE IN THE MSC ADAMS , Applied Computer Science: Vol. 13 No. 1 (2017)
- Konrad PIETRYKOWSKI, Paweł KARPIŃSKI, SIMULATION STUDY OF HYDRODYNAMIC CAVITATION IN THE ORIFICE FLOW , Applied Computer Science: Vol. 18 No. 3 (2022)
- Shahil SHARMA, Rajnesh LAL, Bimal KUMAR, DEVELOPING MACHINE LEARNING APPLICATION FOR EARLY CARDIOVASCULAR DISEASE (CVD) RISK DETECTION IN FIJI: A DESIGN SCIENCE APPROACH , Applied Computer Science: Vol. 20 No. 3 (2024)
- Łukasz SEMKŁO, Łukasz GIERZ, NUMERICAL AND EXPERIMENTAL ANALYSIS OF A CENTRIFUGAL PUMP WITH DIFFERENT ROTOR GEOMETRIES , Applied Computer Science: Vol. 18 No. 4 (2022)
- Mohammed A. Hussein, Ekhlas H. Karam, Rokaia S. Habeeb, CANCER GROWTH TREATMENT USING IMMUNE LINEAR QUADRATIC REGULATOR BASED ON CROW SEARCH OPTIMIZATION ALGORITHM , Applied Computer Science: Vol. 17 No. 2 (2021)
- Weronika WACH, Kinga CHWALEBA, GAP FILLING ALGORITHM FOR MOTION CAPTURE DATA TO CREATE REALISTIC VEHICLE ANIMATION , Applied Computer Science: Vol. 20 No. 3 (2024)
- Puppala Praneeth, Majety Sathvika, Vivek Kommareddy, Madala Sarath, Saran Mallela, Koneru Suvarna Vani, Prasun Chkrabarti, CLASSIFICATION OF PARKINSON'S DISEASE IN BRAIN MRI IMAGES USING DEEP RESIDUAL CONVOLUTIONAL NEURAL NETWORK , Applied Computer Science: Vol. 19 No. 2 (2023)
- Ziadeddine MAKHLOUF, Abdallah MERAOUMIA , Laimeche LAKHDAR, Mohamed Yassine HAOUAM , ENHANCING MEDICAL DATA SECURITY IN E-HEALTH SYSTEMS USING BIOMETRIC-BASED WATERMARKING , Applied Computer Science: Vol. 20 No. 1 (2024)
- Sławomir KUKLA, Marek SMETANA, A SIMULATION EXPERIMENT AND MULTI-CRITERIA ASSESSMENT OF MANUFACTURING PROCESS FLOW VARIANTS TESTED ON A COMPUTER MODEL , Applied Computer Science: Vol. 13 No. 2 (2017)
- Tomasz SEDERYN, Małgorzata SKAWIŃSKA, COMPUTATIONAL ANALYSIS OF PEM FUEL CELL UNDER DIFFERENT OPERATING CONDITIONS , Applied Computer Science: Vol. 19 No. 4 (2023)
<< < 4 5 6 7 8 9 10 11 12 13 > >>
You may also start an advanced similarity search for this article.