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Linear motion error evaluation of open-loop cnc milling using a laser interferometer

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The usage of computerised numerical control (CNC) machines requires accuracy verification to ensure the high accuracy of the processed products. This paper introduces an accuracy verification method of an open-loop CNC milling machine using a fringe counting of He–Ne laser interferometry to evaluate the best possible accuracy and functionality. The linear motion accuracy of open-loop CNC milling was evaluated based on the number of pulses from the controller against the actual displacement measured by the He–Ne fringe-counting method. Interval distances between two pulses are also precisely measured using the He–Ne interferometry. The linear motion error and controller error can be simultaneously evaluated in sub-micro accuracy. The linear positioning error due to the micro-stepping driver accuracy of the mini-CNC milling machine was measured with the expanded uncertainty of measurement and was estimated at 240 nm. The experimental results show that linear motion error of the open-loop CNC milling can reach up to 50 μm for 200 mm translation length.
Słowa kluczowe
Rocznik
Strony
124--129
Opis fizyczny
Bibliogr. 27 poz., rys., tab., wykr.
Twórcy
  • Department of Mechanical Engineering, Vocational School, Universitas Gadjah Mada, Jl. Yacaranda Sekip Unit IV, Yogyakarta 55281, Indonesia
  • Department of Mechanical Engineering, Vocational School, Universitas Gadjah Mada, Jl. Yacaranda Sekip Unit IV, Yogyakarta 55281, Indonesia
  • Department of Mechanical Engineering, Vocational School, Universitas Gadjah Mada, Jl. Yacaranda Sekip Unit IV, Yogyakarta 55281, Indonesia
Bibliografia
  • 1. Liu C, Xiang S, Lu C, Wu C, Du Z, Yang J. Dynamic and static error identification and separation method for three-axis CNC machine tools based on feature workpiece cutting. International Journal of Advanced Manufacturing Technology. 2020; 107(5–6): 2227-2238. https://doi.org/10.1007/s00170-020-05103-5
  • 2. Martinov G M, Ljubimov A B, Martinova L I. From classic CNC systems to cloud-based technology and back. Robotics and Computer-Integrated Manufacturing. 2020; 63: 101927 https://doi.org/10.1016/j.rcim.2019.101927
  • 3. Zhao W, Chen M, Xi W, Xi X, Zhao F, Zhang Y. Reconstructing CNC platform for EDM machines towards smart manufacturing. Procedia CIRP. 2020: 95: 161–177 https://doi.org/10.1016/j.procir.2020.03.134
  • 4. Nurhadi H, Tarng Y S. Open-and closed-loop system of computer integrated desktop-scale CNC machine, IFAC Proceedings Volumes. 2010: 42(24):222–226. https://doi.org/10.3182/20091021-3-JP-2009.00041
  • 5. Andersen H V, Pitkänen K. Empowering educators by developing professional practice in digital fabrication and design thinking. International Journal of Child-Computer Interaction. 2019: 21: 1-16. https://doi.org/10.1016/j.ijcci.2019.03.001
  • 6. Ropin H, Pfleger-Landthaler A. Irsa W A. FabLab as integrative part of a learning factory. Procedia Manufacturing. 2020;45: 355–360. https://doi.org/10.1016/j.promfg.2020.04.033
  • 7. Korkut I, Donertas M A. The influence of feed rate and cutting speed on the cutting forces, surface roughness and tool-chip contact length during face milling. Materials and Design. 2007; 28(1): 308-312. https://doi.org/10.1016/j.matdes.2005.06.002
  • 8. Zmarzły P. Technological heredity of the turning process, Tehnicki Vjesnik. 2020; 27(4): 1194–1203.
  • 9. Mori M, Yamazaki K, Fujishima M, Liu J, Furukawa N. A study on development of an open servo system for intelligent control of a CNC machine tool. CIRP Annals - Manufacturing Technology. 2001; 50(1): 247–250. http://dx.doi.org/10.1016/S0007-8506(07)62115-5
  • 10. Zhou Q. Application of PLC in the CNC machine tool control system. Applied Mechanics and Materials. 2012; 182-183: 902–905. https://doi.org/10.4028/www.scientific.net/AMM.182-183.902
  • 11. Xu HH, Dai C. Research on precision detection and error compen-sation technology for 3-axis CNC milling machine, Applied Mechanics and Materials. 2014: 455; 505–510. https://doi.org/10.4028/www.scientific.net/AMM.455.505
  • 12. Ibaraki S, Oyama C, Otsubo H. Construction of an error map of rotary axes on a five-axis machining center by static R-test. International Journal of Machine Tools and Manufacture. 2011; 51(3): 190–200. http://dx.doi.org/10.1016/j.ijmachtools.2010.11.011
  • 13. ISO 230-1. Test code for machine tools — Part 1: Geometric accuracy of machines operating under no-load or quasi-static conditions; 2012.
  • 14. Blackshaw D M S. Machine tool accuracy and repeatability-a new approach with the revision of ISO 230-2. Transactions on Engineering Sciences. 1997; 16: 91-100. https://doi.org/10.2495/LAMDAMAP970081
  • 15. ISO 10791-4. Test conditions for machining centres-Part 4: Accuracy and repeatability of positioning of linear and rotary axes. 1998
  • 16. ISO 10791-6:2014. Test conditions for machining centres-Part 6: Accuracy of speeds and interpolations. 2014
  • 17. Begović E, Plančić I, Ekinović S, Ekinov E. Laser Interferometry-Measurement and Calibration Method for Machine Tools, Proc 3rd Conference “MAINTENANCE 2014“, 2014; 19–28.
  • 18. Zhang Y, Chu X, Yang S. Research of error detection and compensation of CNC machine tools based on laser interferometer, Proc in 2nd International Conference on Machinery, Materials Engineering, Chemical Engineering and Biotechnology, 2016; 285–289.
  • 19. Lasiyah, S., Development of accuracy measurement for mini Milling CNC with Helium-Neon Laser (in Indonesian). Final Project, Department of Mecahnical Engineering, Vocational College, Gadjah Mada University. 2019
  • 20. Winarno A, Lasiyah S, Prayoga B T, Hendaryanto I A, Sukidjo F X. Development of accuracy evaluation method for open loop educational CNC Milling Machine. Jurnal Rekayasa Mesin. 2021; 12(1): 217-225. https://doi.org/10.21776/ub.jrm.2021.012.01.23
  • 21. Stone J A, Decker J E, Gill P, Juncar P, Lewis A, Rovera G D, Viliesid M. Advice from the CCL on the use of unstabilized lasers as standards of wavelength: The helium-neon laser at 633 nm, Metrologia. 2009; 46(1): 11–18. https://doi.org/10.1088/0026-1394/46/1/002
  • 22. Haitjema H. Calibration of displacement laser interferometer systems for industrial metrology, Sensors. 2019;19(19):1-21. https://dx.doi.org/10.3390%2Fs19194100
  • 23. Ciddor P E, Hill R J. Refractive index of air 2 Group index, Applied Optics. 1999; 38(9): 1663-1667. https://doi.org/10.1364/AO.38.001663
  • 24. Dobosz M, Iwasinska-Kowalska O. A new method of non-contact gauge block calibration using a fringe-counting technique: I. Theoretical basis, Optics and Laser Technology, 2010; 42(1): 141–148. https://doi.org/10.1016/j.optlastec.2009.05.012
  • 25. Iwasinska-Kowalska O, Dobosz M. A new method of noncontact gauge block calibration using the fringe counting technique: II. Experimental verification, Optics and Laser Technology, 2010;42(1):149–155. https://doi.org/10.1016/j.optlastec.2009.05.011
  • 26. Winarno A, Takahashi S, Matsumoto H, Takamasu K. A new measurement method to simultaneously determine group refractive index and thickness of a sample using low-coherence tandem interferometry. Precision Engineering, 2019; 55:254–259. https://doi.org/10.1016/j.precisioneng.2018.09.013
  • 27. Ni Y, Zhou H, Shao C, Li J. Research on the Error Averaging Effect in A Rolling Guide Pair. Chinese Journal of Mechanical Engineering (English Edition). 2019; 32(72). https://doi.org/10.1186/s10033-019-0386-y
Uwagi
This research is funded by Ministry of Education and Culture of the Republic of Indonesia, by Research Grants of Penelitian Terapan Unggulan Perguruan Tinggi (PTUPT) 2020 (No. 1871/UN1/DITLIT/DIT-LIT/PT/2020). The authors are grateful to Sus Lasiyah for the prepare the mini CNC milling
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-a2248223-e640-48af-9649-46a5669a8c61
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