High-performance five-axis computer numerical control machine tools are widely used in the processing of Aeronautical Structural parts. With the increase of service life, the precision of CNC machine tools equipped by aeronautical manufacturing enterprises is declining day by day, while the new generation of aircraft structural parts are developing towards integration, large-scale, complexity, thin-walled and lightweight. It is very easy to produce dimension overshoot and surface quality defects due to unstable processing technology. The machining accuracy of aircraft structural parts is also affected by complex factors such as cutting load, cutting stability, tool error, workpiece deformation, fixture deformation, etc. Because of the complexity of structure and characteristics of Aeronautical Structural parts, the consistency and stability of cutting process are poor. It is easy to cause machining accuracy problems due to tool wear, breakage and cutting chatter. Relevant scholars have carried out a lot of basic research on NC machining accuracy control and achieved fruitful results, but the research on NC machining accuracy control of Aeronautical structural parts is still less. This paper elaborates from three aspects: error modeling method of NC machine tools, error compensation method, prediction and control of machining accuracy, and combines the characteristics of Aeronautical Structural parts, the development trend and demand of NC machining accuracy control technology are put forward.
References
[1]
Sartori, S. and Zhang, G.X. (1995) Geometric Error Measurement and Compensation of Machines. CIRP Annals, 44, 599-609.
https://doi.org/10.1016/S0007-8506(07)60507-1
[2]
Schwenke, H., Knapp, W., Haitjema, H., et al. (2008) Geometric Error Measurement and Compensation of Machines—An Update. CIRP Annals, 57, 660-675.
https://doi.org/10.1016/j.cirp.2008.09.008
[3]
Wu, S.M. and Ni, J. (1989) Precision Machining without Precise Machinery. CIRP Annals, 38, 533. https://doi.org/10.1016/S0007-8506(07)62762-0
[4]
Rahman, M., Heikkala, J. and Lappalainen, K. (2000) Modeling, Measurement and Error Compensation of Multi-Axis Machine Tools. Part I: Theory. International Journal of Machine Tools and Manufacture, 40, 1535-1546.
https://doi.org/10.1016/S0890-6955(99)00101-7
[5]
Li, S.Y., Dai, Y.F., et al. (2007) Precision and Ultra-Precision Machine Tool Precision Modeling Technology. National Defense University of Science and Technology Press, Changsha.
[6]
Mize, C.D. and Ziegert, J.C. (2000) Neural Network Thermal Error Compensation of a Machining Center. Precision Engineering, 24, 338-346.
https://doi.org/10.1016/S0141-6359(00)00044-1
[7]
Zhang, Y. and Yang, J.G. (2011) Thermal Error Modeling of Machine Tools Based on Grey Neural Network. Journal of Shanghai Jiaotong University, 45, 1581-1586.
[8]
Yang, J.G., Ren, Y.Q. and Zhu, W.B. (2003) Research on Online Correction Method of Thermal Error Compensation Model for NC Machine Tools. Journal of Mechanical Engineering, 39, 81-84.
[9]
Li, Y.X., Tong, H.C. and Cao, H.T. (2006) Modeling and Application of Time Series Analysis Method for Thermal Error of CNC Machine Tools. Journal of Sichuan University (Engineering Science Edition), 38, 74-78.
[10]
Han, Z.J. and Zhou, K. (1986) Improvement of Positioning Accuracy of Rotating Table Microcomputer Control Compensation. Precision Engineering, 4, 115-120.
https://doi.org/10.1007/978-1-349-08114-1_16
[11]
Reshetov, D.N. and Portman, V.T. (1988) Accuracy of Machine Tools. ASME Press, New York.
[12]
Liu, Y.W. and Zhang, D.J. (1991) Multibody Dynamics and Its Application in Machine Tools. Machine Tools, No. 1, 24-26, 49.
[13]
Kiriden, V. and Ferreira, P.M. (1993) Mapping the Effects of Positioning Errors on the Volumetric Accuracy of 5-Axis CNC Machine Tools. International Journal of Machine Tools and Manufacture, 33, 417-437.
https://doi.org/10.1016/0890-6955(93)90049-Z
[14]
Lin, Y. and Shen, Y. (2003) Modelling of Five-Axis Machine Tool Metrology Models Using the Matrix Summation Approach. The International Journal of Advanced Manufacturing Technology, 21, 243-248. https://doi.org/10.1007/s001700300028
[15]
Lei, W.T. and Hsu, Y.Y. (2003) Accuracy Enhancement of Five-Axis CNC Machines through Real-Time Error Compensation. International Journal of Machine Tools and Manufacture, 43, 871-877. https://doi.org/10.1016/S0890-6955(03)00089-0
[16]
Ibaraki, S. and Knapp, W. (2012) Indirect Measurement of Volumetric Accuracy for Three-Axis and Five-Axis Machine Tools: A Review. International Journal of Automation Technology, 6, 110-124. https://doi.org/10.20965/ijat.2012.p0110
[17]
Tian, W.J., Gao, W.G., Chang, W.F., et al. (2014) Error Modeling and Sensitivity Analysis of a Five-Axis Machine Tool. Mathematical Problems in Engineering, 2014, Article ID: 745250. https://doi.org/10.1155/2014/745250
[18]
Chen, J.S. (1996) A Study of Thermally Induced Machine Tool Errors in Real Cutting Conditions. International Journal of Machine Tools and Manufacture, 36, 1401-1411. https://doi.org/10.1016/0890-6955(95)00096-8
[19]
Yang, S., Yuan, J. and Ni, J. (1996) The Improvement of Thermal Error Modeling and Compensation on Machine Tools by CMAC Neural Network. International Journal of Machine Tools and Manufacture, 36, 527-537.
https://doi.org/10.1016/0890-6955(95)00040-2
[20]
Lee, S.K., Yoo, J.H. and Yang, M.S. (2003) Effect of Thermal Deformation on Machine Tool Slide Guide Motion. Tribology International, 36, 41-47.
https://doi.org/10.1016/S0301-679X(02)00128-7
[21]
Yang, H. and Ni, J. (2005) Adaptive Model Estimation of Machine-Tool Thermal Errors Based on Recursive Dynamic Modeling Strategy. International Journal of Machine Tools and Manufacture, 45, 1-11.
https://doi.org/10.1016/j.ijmachtools.2004.06.023
[22]
Yang, H. and Ni, J. (2005) Dynamic Neural Network Modeling for Nonlinear, Nonstationary Machine Tool Thermally Induced Error. International Journal of Machine Tools and Manufacture, 45, 455-465.
https://doi.org/10.1016/j.ijmachtools.2004.09.004
[23]
Wang, K.C. and Tseng, P.C. (2010) Thermal Error Modeling of a Machine Tool Using Data Mining Scheme. Journal of Advanced Mechanical Design, Systems, and Manufacturing, 4, 516-530. https://doi.org/10.1299/jamdsm.4.516
[24]
Guo, Q., Yang, J. and Wu, H. (2010) Application of ACO-BPN to Thermal Error Modeling of NC Machine Tool. The International Journal of Advanced Manufacturing Technology, 50, 667-675. https://doi.org/10.1007/s00170-010-2520-y
[25]
Yee, K.W. and Gavin, R.J. (1990) Implementing Fast Part Probing and Error Compensation on Machine Tools. https://doi.org/10.6028/NIST.IR.4447
[26]
Choi, J.P., Min, B.K. and Lee, S.J. (2004) Reduction of Machining Errors of a Three-Axis Machine Tool by On-Machine Measurement and Error Compensation System. Journal of Materials Processing Technology, 155, 2056-2064.
https://doi.org/10.1016/j.jmatprotec.2004.04.402
[27]
Yang, J.G., Zhang, H.T., Tong, H.C., Cao, H.T. and Ren, Y.Q. (2005) Application of Real-Time Thermal Error Compensation for CNC Machine Tools. Journal of Shanghai Jiaotong University, 39, 1389-1392.
[28]
Cui, G.W., Lu, Y., Gao, D. and Yao, Y. (2012) A Novel Error Compensation Implementing Strategy and Realizing on Siemens 840D CNC Systems. The International Journal of Advanced Manufacturing Technology, 61, 595-608.
https://doi.org/10.1007/s00170-011-3747-y
[29]
Shen, H., Fu, J., He, Y., et al. (2012) On-Line Asynchronous Compensation Methods for Static/Quasi-Static Error Implemented on CNC Machine Tools. International Journal of Machine Tools & Manufacture, 60, 14-26.
https://doi.org/10.1016/j.ijmachtools.2012.04.003
[30]
Yang, T.Y. (2013) Real-Time Error Compensation and Application Based on Bottom Communication of CNC System. China Mechanical Engineering, 24, 2903-2908.
[31]
Zhang, H., Zhou, Y.F., Tang, X.Q. and Chen, J.H. (2002) Error G Code Compensation Technology for CNC Machining Center. Journal of Huazhong University of Science and Technology, 30, 13-16.
[32]
Eskandari, S., Arezoo, B. and Abdullah, A. (2013) Positional, Geometrical, and Thermal Errors Compensation by Tool Path Modification Using Three Methods of Regression, Neural Networks, and Fuzzy Logic. The International Journal of Advanced Manufacturing Technology, 65, 1635-1649.
https://doi.org/10.1007/s00170-012-4285-y
[33]
Zhu, S.W., Ding, G.F. and Jiang, L. (2010) Machining Accuracy Improvement of Five-Axis Machine Tools by Geometric Error Compensation. International Conference on Advanced Technology of Design and Manufacture, Beijing, 23-25 November 2010, 348-352.
[34]
Zhu, S.W., Ding, G.F., Ma, S.W., et al. (2013) Workpiece Locating Error Prediction and Compensation in Fixtures. The International Journal of Advanced Manufacturing Technology, 67, 1423-1432. https://doi.org/10.1007/s00170-012-4578-1
[35]
Wu, C.J., Fan, J.W., Wang, Q.H., et al. (2018) Prediction and Compensation of Geometric Error for Translational Axes in Multi-Axis Machine Tools. The International Journal of Advanced Manufacturing Technology, 95, 3413-3435.
https://doi.org/10.1007/s00170-017-1385-8
[36]
Xiang, S.T., Li, H.M., Deng, M., et al. (2018) Geometric Error Analysis and Compensation for Multi-Axis Spiral Bevel Gears Milling Machine. Mechanism and Machine Theory, 121, 59-74. https://doi.org/10.1016/j.mechmachtheory.2017.10.014
[37]
Lu, B.H., Ge, Y.J., Wang, Q.Y., et al. (2002) Prediction of Virtual NC Turning Accuracy. Journal of Mechanical Engineering, 38, 82-85.
[38]
Dang, J.W., Zhang, W.H., Wanmin, et al. (2011) New Prediction Model of Machining Error in Milling Process. Journal of Mechanical Engineering, 47, 150-155.
[39]
Fan, K.C., Chen, H.M. and Kuo, T.H. (2012) Prediction of Machining Accuracy Degradation of Machine Tools. Precision Engineering, 36, 288-298.
https://doi.org/10.1016/j.precisioneng.2011.11.002
[40]
Holub, M., Michalicek, M. and Vetiska, J. (2014) Prediction of Machining Accuracy for Vertical Lathes. Springer International Publishing, Berlin.
https://doi.org/10.1007/978-3-319-02294-9_6
[41]
Ding, G.F., Zhu, S.W., Yahya, E., et al. (2014) Prediction of Machining Accuracy Based on a Geometric Error Model in Five-Axis Peripheral Milling Process. Journal of Engineering Manufacture, 228, 1226-1236.
[42]
Archenti, A. (2014) Prediction of Machined Part Accuracy from Machining System Capability. CIRP Annals—Manufacturing Technology, 63, 505-508.
https://doi.org/10.1016/j.cirp.2014.03.040
