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29.04.2024

Home Page Styczeń 2021 Application of multi-sensor measurement system for machining process monitoring – a case study for sequential turning and burnishing processes

Application of multi-sensor measurement system for machining process monitoring – a case study for sequential turning and burnishing processes

Zastosowanie wielosensorowego systemu pomiarowego do monitorowania procesu skrawania – przypadek sekwencyjnych procesów toczenia i nagniatania *

Author: Marian Bartoszuk, Wit Grzesik, Roman Chudy

Mechanik nr 01/2021 - Obróbka skrawaniem

ABSTRACT: In this paper, the structure and operational functions of a measurement system, which was installed on a 3-axis CNC lathe for monitoring and optimization of the cutting process are presented. In general, the system records signals of the components of the resultant cutting force, acceleration signals (cutting vibrations) and EFM force signals generated for various machining conditions employed. As a result, the total power consumed was determined. The generated data were archived in the expert system which supports the optimization of the cutting process in terms of various optimization criteria including power/energy consumption.

KEYWORDS: machining process, measurement system, signal processing, monitoring, process optimization

STRESZCZENIE: W artykule przedstawiono budowę i funkcje eksploatacyjne układu pomiarowego, który został zainstalowany na 3-osiowej tokarce CNC w celu monitorowania i optymalizacji procesu skrawania. System rejestruje sygnały składowych wypadkowej siły skrawania, sygnały przyspieszenia (drgania skrawania) oraz sygnały siły EFM generowane dla różnych zastosowanych warunków obróbki. W rezultacie określono całkowitą pobieraną moc. Wygenerowane dane zostały zarchiwizowane w systemie ekspertowym, który wspiera optymalizację procesu cięcia pod kątem różnych kryteriów optymalizacji, w tym poboru mocy / energii.

SŁOWA KLUCZOWE: proces obróbki, system pomiarowy, przetwarzanie sygnałów, monitoring, optymalizacja procesów

BIBLIOGRAFIA / BIBLIOGRAPHY:

[1] Grzesik W. “Advanced Machining Processes of Metallic Materials”. 2nd ed. Elsevier (2018), https://www.sciencedirect.com/book/9780080445342/advanced-machining-processes-of-metallic-materials.

[2] Davim J.P. “Machining: Fundamentals and Recent Advances”. Springer (2008), https://scholar.google.pl/scholar?q=Machining:+Fundamentals+and+Recent+Advances+google+scholar&hl=pl&as_sdt=0&as_vis=1&oi=scholart.

[3] Davim J.P. “Machining: Operations, Technology and Management (Materials and Manufacturing Technology)”. Nova Science Pub Inc. (2013).

[4] Jędrzejewski J., Kwaśny W. “Development of machine tool design and operational properties”. Int. Journal of Advanced Manufacturing Technology. 93 (2017): 1051–1068, https://doi.org/10.1007/s00170-017-0560-2.

[5] “Integrated digitalization solutions”. DMG MORI Technology Excellence Magazine 01-2018, en.dmgmori.com.

[6] Kozłowski E., Mazurkiewicz D., Żabiński T., Prucnal S., Sęp J. “Assessment model of cutting tool condition for real-time supervision system”. Maintenance and Reliability. 21 (2019): 679–685, http://dx.doi.org/10.17531/ein.2019.4.18.

[7] Skoczyński W. „Sensory w obrabiarkach CNC (Sensors in CNC Machine Tools). Warszawa: PWN (2018).

[8] Toenshoff H.K., Inasaki I. “Sensors in Manufacturing”. Weinheim – New York – Chichester – Brisbane – Singapore – Toronto: Wiley-VCH Verlag (2001).

[9] Sokołowski A. “Selected concepts and practical applications of artificial intelligence in diagnostics of machine tools and machining process (Wybrane koncepcje i praktyczne zastosowania sztucznej inteligencji w diagnostyce obrabiarek i procesu skrawania)”. Inżynieria Maszyn. 23 (2018): 97–110, file:///C:/Users/Anna/AppData/Local/Temp/Sokolowski_Wybrane_1_2018.pdf.

[10] Teti R., Jemielniak K., O’Donnell G., Dornfeld D. “Advanced monitoring of machining operations”. Annals of the CIRP, 59, 2 (2010): 717–739, https://doi.org/10.1016/j.cirp.2010.05.010.

[11] Jemielniak K. “Contemporary challenges in tool condition monitoring”. Journal of Machine Engineering. 19, 1 (2019): 48–61, https://doi.org/10.5604/01.3001.0013.0448.

[12] Altintas Y., Kersting P., Biermann D., Budak E., Denkena B., Lazoglu I. “Virtual process systems for part machining operations”. CIRP Annals-Manufacturing Technology. 63, 2 (2014): 585–605, https://doi.org/10.1016/j.cirp.2014.05.007.

[13] Grzesik W. “Energy consumption optimization in machining processes”. In: Davim J.P. (ed.), Metal Cutting Technologies. Progress and Current Trends, De Gruyter (2016), https://scholar.google.com/scholar?hl=pl&as_sdt=0%2C5&q=Metal+Cutting+Technologies.+Progress+and+Current+Trends&btnG=.

[14] Melkote S., Grzesik W., Ouiteiro J., Rech J., Schulze V., Attia H., Arrazola P., M’Saoubi R., Saldana CH. “Advances in material and friction data for modelling of metal machining”. CIRP Annals-Manufacturing Technology. 66, 2 (2017): 731–754, https://doi.org/10.1016/j.cirp.2017.05.002.

[15] Bartoszuk M., Nowak A. “Monitoring of cutting temperature (Monitorowanie temperatury skrawania)”. Pomiary Automatyka Kontrola. 60, 1 (2014): 16–19, file:///C:/Users/Anna/AppData/Local/Temp/Bartoszuk_monitorowanie_PAK_1_2014.pdf.

[16] Grzesik W. “An integrated approach to evaluating the tribo-contact for coated cutting inserts”. Wear. 240 (2000): 9–18, https://doi.org/10.1016/S0043-1648(00)00324-0.

[17] Chudy R. “Investigation of power consumption of machining processes of machine parts (Badanie energochłonności procesów obróbki części maszyn)”, PhD Thesis, Faculty of Mechanical Engineering, Opole University of Technology (2019).

DOI: https://doi.org/10.17814/mechanik.2021.1.1

 

* Artykuł recenzowany

 

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Marian Bartoszuk, Wit Grzesik, Roman Chudy: Application of multi-sensor measurement system for machining process monitoring – a case study for sequential turning and burnishing processes (Zastosowanie wielosensorowego systemu pomiarowego do monitorowania procesu skrawania – przypadek sekwencyjnych procesów toczenia i nagniatania) (PDF, ~1,4 MB)

Home Page Styczeń 2021 Application of multi-sensor measurement system for machining process monitoring – a case study for sequential turning and burnishing processes

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