Abstract
In machining of a microstructure on a free form surface, a five-axis ultra-precision machine tool has a great advantage in its flexibility and efficiency compared to a conventional machine tool. However, rotary axes in the five-axis machine tool are sensitive to position errors due to low rigidity. In addition, micro-tools, which are utilized in micro-machining, have low stiffness. The low rigidity and stiffness of the rotary axes and tool introduce geometric errors in machining. Therefore, the position and orientation errors of the rotary axes and the micro-tool must be identified and compensated. Many components contribute to uncertainty of the measurements which will inevitably reduce the reliability of the results. Therefore, it is necessary to analyze the uncertainty of each component. This paper proposed a method to comprehensively identify position-independent geometric errors (PIGEs) and force-induced errors (FIEs) of a system from the rotary axis on the machine to the micro-tool. A simple and practical error model to represent the tool position with respect to the angle of the rotary axis was built. Uncertainty was analyzed to validate the reliability of the proposed method. Cutting experiments were carried out on an AISI 1018 steel and an Al6061 workpiece, and the results were analyzed to verify the proposed model.
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References
Ramesh R, Mannan MA, Poo AN (2000) Error compensation in machine tools — a review: part I: geometric, cutting-force induced and fixture-dependent errors. Int J Mach Tools Manuf 40:1235–1256. https://doi.org/10.1016/S0890-6955(00)00009-2
Ratchev S, Liu S, Becker AA (2005) Error compensation strategy in milling flexible thin-wall parts. J Mater Process Technol 162–163:673–681. https://doi.org/10.1016/j.jmatprotec.2005.02.192
Fan KG, Yang JG, Yang LY (2013) Orthogonal polynomials-based thermally induced spindle and geometric error modeling and compensation. Int J Adv Manuf Technol 65:1791–1800. https://doi.org/10.1007/s00170-012-4301-2
ISO 230-1 (2012) Test code for machine tools — part 1: geometric accuracy of machines operating under no-load or quasi-static conditions. In: ISO. http://www.iso.org/cms/render/live/en/sites/isoorg/contents/data/standard/04/64/46449.html. Accessed 18 Nov 2019
ISO 230-7 (2015) Test code for machine tools — part 7: geometric accuracy of axes of rotation. In: ISO. https://www.iso.org/cms/render/live/en/sites/isoorg/contents/data/standard/05/66/56624.html. Accessed 24 May 2020
ISO 10791-1 (2015) Test conditions for machining centres — part 1: geometric tests for machines with horizontal spindle (horizontal Z-axis). In: ISO. https://www.iso.org/cms/render/live/en/sites/isoorg/contents/data/standard/05/47/54729.html. Accessed 11 Jun 2020
Lee KI, Yang SH (2013) Measurement and verification of position-independent geometric errors of a five-axis machine tool using a double ball-bar. Int J Mach Tools Manuf 70:45–52. https://doi.org/10.1016/j.ijmachtools.2013.03.010
Huang ND, Bi QZ, Wang YH (2015) Identification of two different geometric error definitions for the rotary axis of the 5-axis machine tools. Int J Mach Tools Manuf 91:109–114. https://doi.org/10.1016/j.ijmachtools.2015.02.003
Ding S, Huang XD, Yu CJ, Liu XY (2016) Identification of different geometric error models and definitions for the rotary axis of five-axis machine tools. Int J Mach Tools Manuf 100:1–6. https://doi.org/10.1016/j.ijmachtools.2015.09.008
Zhang Z, Cai L, Cheng Q, Liu Z, Gu P (2016) A geometric error budget method to improve machining accuracy reliability of multi-axis machine tools. J Intell Manuf 30:1–25. https://doi.org/10.1007/s10845-016-1260-8
Yang JX, Mayer JRR, Altintas Y (2015) A position independent geometric errors identification and correction method for five-axis serial machines based on screw theory. Int J Mach Tools Manuf 95:52–66. https://doi.org/10.1016/j.ijmachtools.2015.04.011
Xiang ST, Altintas Y (2016) Modeling and compensation of volumetric errors for five-axis machine tools. Int J Mach Tools Manuf 101:65–78. https://doi.org/10.1016/j.ijmachtools.2015.11.006
López de Lacalle LN, Lamikiz A (2009) Machine tools for high performance machining. London. https://doi.org/10.1007/978-1-84800-380-4
López de Lacalle LN, Lamikiz A, Sánchez JA, Salgado MA (2004) Effects of tool deflection in the high-speed milling of inclined surfaces. Int J Adv Manuf Technol 24:621–631. https://doi.org/10.1007/s00170-003-1723-x
López de Lacalle LN, Lamikiz A, Sánchez JA, Salgado MA (2007) Toolpath selection based on the minimum deflection cutting forces in the programming of complex surfaces milling. Int J Mach Tools Manuf 47:388–400. https://doi.org/10.1016/j.ijmachtools.2006.03.010
Sang YC, Yao CL, Lv YQ, He GY (2020) An improved feedrate scheduling method for NURBS interpolation in five-axis machining. Precis Eng 64:70–90. https://doi.org/10.1016/j.precisioneng.2020.03.012
Bohez ELJ (2002) Five-axis milling machine tool kinematic chain design and analysis. Int J Mach Tools Manuf 42:505–520. https://doi.org/10.1016/S0890-6955(01)00134-1
Shi XL, Liu HL, Li H, Liu C, Tan G (2016) Comprehensive error measurement and compensation method for equivalent cutting forces. Int J Adv Manuf Technol 85:149–156. https://doi.org/10.1007/s00170-015-7789-4
Suh SH, Cho JH, Hascoet JY (1996) Incorporation of tool deflection in tool path computation: simulation and analysis. J Manuf Syst 15:190–199. https://doi.org/10.1016/0278-6125(96)89571-9
Armarego EJA, Deshpande NP (1991) Computerized end-milling force predictions with cutting models allowing for eccentricity and cutter deflections. CIRP Ann 40:25–29. https://doi.org/10.1016/S0007-8506(07)61926-X
Salgado MA, López de Lacalle LN, Lamikiz A, Muñoa J, Sánchez JA (2005) Evaluation of the stiffness chain on the deflection of end-mills under cutting forces. Int J Mach Tools Manuf 45:727–739. https://doi.org/10.1016/j.ijmachtools.2004.08.023
Uriarte L, Herrero A, Zatarain M, Santiso G, Lopéz de Lacalle LN, Lamikiz A, Albizuri J (2007) Error budget and stiffness chain assessment in a micromilling machine equipped with tools less than 0.3mm in diameter. Precis Eng 31:1–12. https://doi.org/10.1016/j.precisioneng.2005.11.010
Du ZC, Zhang D, Hou HF, Liang SY (2017) Peripheral milling force induced error compensation using analytical force model and APDL deformation calculation. Int J Adv Manuf Technol 88:3405–3417. https://doi.org/10.1007/s00170-016-9052-z
Ma WK, He GY, Zhu LM, Guo LZ (2016) Tool deflection error compensation in five-axis ball-end milling of sculptured surface. Int J Adv Manuf Technol 84:1421–1430. https://doi.org/10.1007/s00170-015-7793-8
Raksiri C, Parnichkun M (2004) Geometric and force errors compensation in a 3-axis CNC milling machine. Int J Mach Tools Manuf 44:1283–1291. https://doi.org/10.1016/j.ijmachtools.2004.04.016
Ding TC, Zhang S, Wang YW, Zhu XL (2010) Empirical models and optimal cutting parameters for cutting forces and surface roughness in hard milling of AISI H13 steel. Int J Adv Manuf Technol 51:45–55. https://doi.org/10.1007/s00170-010-2598-2
Turyagyenda G, Wu H, Yang JG (2008) Progressive development of an absolute sensorless compensation system for cutting force-induced error. Int J Adv Manuf Technol 39:454–461. https://doi.org/10.1007/s00170-007-1239-x
Yue CX, Liu XL, Ding YP, Liang SY (2018) Off-line error compensation in corner milling process. Proc Inst Mech Eng Part B J Eng Manuf 232:1172–1181. https://doi.org/10.1177/0954405416666901
Soori M, Arezoo B, Habibi M (2017) Accuracy analysis of tool deflection error modeling in prediction of milled surfaces by a virtual machining system. Int J Comput Appl Technol 55:308. https://doi.org/10.1504/ijcat.2017.086015
Shi YG, Zhao XY, Zhang HJ, Nie Y, Zhang D (2016) A new top-down design method for the stiffness of precision machine tools. Int J Adv Manuf Technol 83:1887–1904. https://doi.org/10.1007/s00170-015-7705-y
Maeng S, Min S (2020) Simultaneous geometric error identification of rotary axis and tool setting in an ultra-precision 5-axis machine tool using on-machine measurement. Precis Eng 63:94–104. https://doi.org/10.1016/j.precisioneng.2020.01.007
Lee K-I, Yang S-H (2013) Robust measurement method and uncertainty analysis for position-independent geometric errors of a rotary axis using a double ball-bar. Int J Precis Eng Manuf 14:231–239. https://doi.org/10.1007/s12541-013-0032-z
Tsutsumi M, Tone S, Kato N, Sato R (2013) Enhancement of geometric accuracy of five-axis machining centers based on identification and compensation of geometric deviations. Int J Mach Tools Manuf 68:11–20. https://doi.org/10.1016/j.ijmachtools.2012.12.008
Jiang XG, Cripps RJ (2015) A method of testing position independent geometric errors in rotary axes of a five-axis machine tool using a double ball bar. Int J Mach Tools Manuf 89:151–158. https://doi.org/10.1016/j.ijmachtools.2014.10.010
Bi QZ, Huang ND, Sun C, Wang Y, Zhu L, Ding H (2015) Identification and compensation of geometric errors of rotary axes on five-axis machine by on-machine measurement. Int J Mach Tools Manuf 89:182–191. https://doi.org/10.1016/j.ijmachtools.2014.11.008
Givi M, Mayer JRR (2014) Validation of volumetric error compensation for a five-axis machine using surface mismatch producing tests and on-machine touch probing. Int J Mach Tools Manuf 87:89–95. https://doi.org/10.1016/j.ijmachtools.2014.08.001
Ibaraki S, Nagai Y, Otsubo H, Sakai Y, Morimoto S, Miyazaki Y, Department of Micro Engineering, Kyoto University, Otsubo Engineering Research Center, Fukuyama, Japan, Fukuda Corporation, Tokyo, Japan (2015) R-test analysis software for error calibration of five-Axis machine tools – application to a five-axis machine tool with two rotary axes on the tool side. Int J Autom Technol 9:387–395. https://doi.org/10.20965/ijat.2015.p0387
Ibaraki S, Iritani T, Matsushita T (2012) Calibration of location errors of rotary axes on five-axis machine tools by on-the-machine measurement using a touch-trigger probe. Int J Mach Tools Manuf 58:44–53. https://doi.org/10.1016/j.ijmachtools.2012.03.002
Angle E, Shreiner D (2011) Interactive computer graphics: a top-down approach with shader-based opengl. 6th ed. Addison-Wesley Publishing Company, USA. https://dl.acm.org/doi/book/10.5555/2018863
ISO 230-2 (2014) Test code for machine tools — part 2: determination of accuracy and repeatability of positioning of numerically controlled axes. In: ISO. http://www.iso.org/cms/render/live/en/sites/isoorg/contents/data/standard/05/52/55295.html. Accessed 18 Nov 2019
ISO/TR 230–9 (2005) Test code for machine tools — part 9: estimation of measurement uncertainty for machine tool tests according to series ISO 230, basic equations. In: ISO. http://www.iso.org/cms/render/live/en/sites/isoorg/contents/data/standard/03/91/39165.html. Accessed 18 Nov 2019
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The authors gratefully acknowledge the financial support and the donation of the ROBONANO α-0iB to MIN LAB at UW-Madison from the FANUC Corporation, Japan.
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Chen, Q., Maeng, S., Li, W. et al. Geometric- and force-induced errors compensation and uncertainty analysis of rotary axis in 5-axis ultra-precision machine tool. Int J Adv Manuf Technol 109, 841–856 (2020). https://doi.org/10.1007/s00170-020-05670-7
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DOI: https://doi.org/10.1007/s00170-020-05670-7