Abstract
CNC machine tools play an extremely important role in the equipment manufacturing industry. Because a machine tool has multiple geometric errors which are highly coupled, the error identification process is difficult. Most direct and indirect measurement methods do not consider the dynamic errors in the actual cutting process. This study aims to optimize the error identification process of three-axis CNC machine tools, and proposes an efficient identification and separation method for the dynamic error and the quasi-static error based on feature workpiece cutting. In this study, a stepped feature workpiece that can reflect geometric errors is designed, and the mapping relationship between the geometric error components and the features is established. After the feature workpiece is cut, it performs two tests of on-machine measurement and CMM calibration sequentially. It can realize the identification and separation of 7 geometric errors and corresponding dynamic errors based on the two sets of test data. This method takes the actual cutting workpiece as the error source and can identify and separate the dynamic error and the quasi-static error simultaneously. Thus, the measurement efficiency of this method is higher than direct measurements. The geometric error identification result is highly consistent with the laser interferometer measurement, which proves the method in this study is feasible, efficient, and accurate.
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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(9):1235–1256
Yang J, Aslan D, Altintas Y (2018) Identification of workpiece location on rotary tables to minimize tracking errors in five-axis machining. Int J Mach Tools Manuf 125:89–98
Majda P (2012) Modeling of geometric errors of linear guideway and their influence on joint kinematic error in machine tools. Precis Eng 36(3):369–378
Li Y, Zhao W, Lan S, Ni J, Wu W, Lu B (2015) A review on spindle thermal error compensation in machine tools. Int J Mach Tools Manuf 95:20–38
Baek SW, Kim MG, Lee DH, Cho NG (2019) Multi-probe system design for measuring the roundness and rotation error motion of a spindle using an error separation technique. Proc Inst Mech Eng B J Eng Manuf 233(5):1547–1560
ГРАНОВСКИЙ BA (1989) Dynamic measurements. Translated by FU Lietang, BAO Jianzhong. China Metrology Press, Beijing
Andolfatto L, Lavernhe S, Mayer JRR (2011) Evaluation of servo, geometric and dynamic error sources on five-axis high-speed machine tool. Int J Mach Tools Manuf 51(10–11):787–796
Li B, Luo B, Mao X, Cai H, Peng F, Liu H (2013) A new approach to identifying the dynamic behavior of CNC machine tools with respect to different worktable feed speeds. Int J Mach Tools Manuf 72:73–84
Ibaraki S, Knapp W (2012) Indirect measurement of volumetric accuracy for three-axis and five-axis machine tools: a review. Int J Autom Technol 6(2):110–124
Xiang S, Li H, Deng M, Yang J (2018) Geometric error identification and compensation for non-orthogonal five-axis machine tools. Int J Adv Manuf Technol 96(5–8):2915–2929
Yang J, Ding H (2016) A new position independent geometric errors identification model of five-axis serial machine tools based on differential motion matrices. Int J Mach Tools Manuf 104:68–77
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
Hong C, Ibaraki S (2013) Non-contact R-test with laser displacement sensors for error calibration of five-axis machine tools. Precis Eng 37(1):159–171
Ibaraki S, Blaser P, Shimoike M, Takayama N, Nakaminami M, Ido Y (2016) Measurement of thermal influence on a two-dimensional motion trajectory using a tracking interferometer. CIRP Ann 65(1):483–486
Givi M, Mayer JRR (2016) Optimized volumetric error compensation for five-axis machine tools considering relevance and compensability. CIRP J Manuf Sci Technol 12:44–55
Mutilba U, Yagüe-Fabra JA, Gomez-Acedo E, Kortaberria G, Olarra A (2018) Integrated multilateration for machine tool automatic verification. CIRP Ann 67(1):555–558
ISO B S (1998) 10791–7. Test conditions for machining centres-Part, 7
China Chengdu Aircraft Industry (Group) Co. Lt (2010) Processing Accuracy Test Specification for Five-Axis Linkage CNC Milling Machine
Jiang Z, Song B, Zhou X, Tang X, Zheng S (2015) On-machine measurement of location errors on five-axis machine tools by machining tests and a laser displacement sensor. Int J Mach Tools Manuf 95:1–12
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
Ibaraki S, Ota Y (2014) A machining test to calibrate rotary axis error motions of five-axis machine tools and its application to thermal deformation test. Int J Mach Tools Manuf 86:81–88
Ibaraki S, Yoshida I, Asano T (2019) A machining test to identify rotary axis geometric errors on a five-axis machine tool with a swiveling rotary table for turning operations. Precis Eng 55:22–32
Ibaraki S, Sawada M, Matsubara A, Matsushita T (2010) Machining tests to identify kinematic errors on five-axis machine tools. Precis Eng 34(3):387–398
Zaghbani I, Songmene V (2009) Estimation of machine-tool dynamic parameters during machining operation through operational modal analysis. Int J Mach Tool Manu 49(s12–13):947–957
Wang G, Li W (2019) Manufacturing of lens arrays using fast tool servo system based on error correcting algorithm. Optik 178:698–703
Zhang L, Xiang Y (2019) Error separation methods based on absolute testing of non-uniform sampling. Optik 178:986–991
Funding
This research was sponsored by the National Natural Science Foundation of China (51705262, 51975372), Natural Science Foundation of Zhejiang Province (LY20E050005, Q19E050001), Natural Science Foundation of Ningbo (2018A610147), Research Project of State Key Laboratory of Mechanical System and Vibration (MSV201911), and the K. C. Wong Magna Fund in Ningbo University.
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Liu, C., Xiang, S., Lu, C. et al. Dynamic and static error identification and separation method for three-axis CNC machine tools based on feature workpiece cutting. Int J Adv Manuf Technol 107, 2227–2238 (2020). https://doi.org/10.1007/s00170-020-05103-5
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DOI: https://doi.org/10.1007/s00170-020-05103-5