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Tytuł artykułu

Enhancing machining accuracy reliability of multi-axis CNC Indexed by: machine tools using an advanced importance sampling method

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The purpose of this paper is to propose a general precision allocation method to improve machining performance of CNC machine tools based on certain design requirements. A comprehensive error model of machine tools is established by using the differential motion relation of coordinate frames. Based on the comprehensive error model, a reliability model is established by updating the primary reliability with an advanced importance sampling method, which is used to predict the machining accuracy reliability of machine tools. Besides, to identify and optimize geometric error parameters which have a great influence on machining accuracy reliability of machine tools, the sensitivity analysis of machining accuracy is carried out by improved first-order second-moment method. Taking a large CNC gantry guide rail grinder as an example, the optimization results show that the method is effective and can realize reliability optimization of machining accuracy.
Rocznik
Strony
559--568
Opis fizyczny
Bibliogr. 23 poz., rys., tab.
Twórcy
autor
  • School of Mechanical and Electronic Engineering, Lanzhou University of Technology, Lanzhou 730050, China
autor
  • School of Mechanical and Electronic Engineering, Lanzhou University of Technology, Lanzhou 730050, China
Bibliografia
  • 1. Antonio CC, Hoffbauer LN. An approach for reliability-based robust design optimisation of angle-piy composite. Composite Structures 2009; 90(1): 53-59, https://doi.org/10.1016/j.compstruct.2009.01.008.
  • 2. Bohez ELJ, Ariyajunya B, Sinlapeecheewa C, Shein TMM, Lap DT, Belforte G. Systematic geometric rigid body error identification of 5-axis milling machines. Computer-Aided Design 2007; 39(4): 229-244, https://doi.org/10.1016/j.cad.2006.11.006.
  • 3. Cai LG, Zhang ZL, Cheng Q, Liu ZF, Gu PH. A geometric accuracy design method of multi-axis NC machine tool for improving machining accuracy reliability. Eksploatacja i Niezawodnosc-Maintenance and Reliability 2015; 17(1): 143-155, https://doi.org/10.17531/ein.2015.1.19.
  • 4. Chen GD, Liang YC, Sun YZ, Chen WQ, Wang B. Volumetric error modeling and sensitivity analysis for designing a five-axis ultra-precision machine too. The International Journal of Advanced Manufacturing Technology 2013; 68(9-12): 2525-2534, https://doi.org/10.1007/s00170-013-4874-4.
  • 5. Cheng Q, Feng QN, Liu ZF, Gu PH, Cai LG. Fluctuation prediction of machining accuracy for multi-axis machine tool based on stochastic process theory. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 2015; 229(14):2534-2550, https://doi.org/10.1177/0954406214562633.
  • 6. Cheng Q, Zhang ZL, Zhang GJ, Gu PH, Cai LG. Geometric accuracy allocation for multi-axis CNC machine tools based on sensitivity analysis and reliability theory. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 2015; 229(6): 1134-1149, https://doi.org/10.1177/0954406214542491.
  • 7. Cheng Q, Zhao HW, Zhang GJ, Gu PH, Cai LG. An analytical approach for crucial geometric errors identification of multi-axis machine tool based on global sensitivity analysis. The International Journal of Advanced Manufacturing Technology 2014; 75(1-4): 107-121, https://doi.org/10.1007/s00170-014-6133-8.
  • 8. Cheng Q, Zhao HW, Zhao YS, Sun BW, Gu PH. Machining accuracy reliability analysis of multi-axis machine tool based on Monte Carlo simulation. Journal of Intelligent Manufacturing 2018; 29(1): 1-19, https://doi.org/10.1007/s10845-015-1101-1.
  • 9. Fu GQ, Fu JZ, Xu YT, Chen ZC, Lai JT. Accuracy enhancement of five-axis machine tool based on differential motion matrix: Geometric error modeling, identification and compensation. International Journal of Machine Tools & Manufacture 2015; 89: 170-181, https://doi.org/10.1016/j.ijmachtools.2014.11.005.
  • 10. Guo SJ, Mei XS, Jiang GD. Geometric accuracy enhancement of five-axis machine tool based on error analysis. The International Journal of Advanced Manufacturing Technology 2019; 105(1-4): 137-153, https://doi.org/10.1007/s00170-019-04030-4.
  • 11. Huang B. Reliability theory of engineering structure and its application. Wuhan: Wuhan University of Technology Press 2019.
  • 12. Lee ES, Suh SH, Shon JW. A comprehensive method for calibration of volumetric positioning accuracy of CNC-machines. The International Journal of Advanced Manufacturing Technology 1998; 14(1): 43-49, https://doi.org/10.1007/BF01179416.
  • 13. Lee RS, Lin YH. Applying bidirectional kinematics to assembly error analysis for five-axis machine tools with general orthogonal configuration. The International Journal of Advanced Manufacturing Technology 2012; 62(9-12): 1261-1272, https://doi.org/10.1007/s00170-011-3860-y.
  • 14. Niu P, Cheng Q, Chang WF, Song XM, Li YS. Sensitivity analysis of machining accuracy reliability considering partial correlation of geometric errors for Horizontal Machining Center. Proceedings of the Institution of Mechanical Engineers, part B 2021; 235(3): 455-465, https://doi.org/10.1177/0954405420958843.
  • 15. Niu P, Cheng Q, Liu ZF, Chu HY. A machining accuracy improvement approach for a horizontal machining center based on analysis of geometric error characteristics. The International Journal of Advanced Manufacturing Technology 2021; 112: 2873-2887, https://doi.org/10.1007/s00170-020-06565-3.
  • 16. Qi J, Yang W. Differential change construction based geometric error compensation for machine tools. Transactions of the Chinese Society for Agricultural Machinery 2016; 47(9): 398-405.
  • 17. Wu HR, Zheng HL, Li XX, Wang WK, Xiang XP, Meng XP. A geometric accuracy analysis and tolerance robust design approach for a vertical machining center based on the reliability theory. Measurement 2020; 161: 107809, https://doi.org/10.1016/j.measurement.2020.107809.
  • 18. Yu ZM, Liu ZJ, Ai YD, Xiong M. Geometric error model and precision distribution based on reliability theory for large CNC gantry guideway grinder. Journal of Mechanical Engineering 2013; 49(17): 142-151, https://doi.org/10.3901/JME.2013.17.142.
  • 19. Zhang C. Geometric error inversion and optimization of multi axis CNC machine tools based on robust design. Beijing: Beijing University of Technology 2014.
  • 20. Zhang ZL, Cai LG, Cheng Q, Liu ZF, Gu PH. A geometric error budget method to improve machining accuracy reliability of multi-axis machine tools. Journal of Intelligent Manufacturing 2019; 30(2): 495-519, https://doi.org/10.1007/s10845-016-1260-8.
  • 21. Zhang ZL, Liu ZF, Cai LG, Cheng Q, Qi Y. An accuracy design approach for a multi-axis NC machine tool based on reliability theory. The International Journal of Advanced Manufacturing Technology 2016; 91(5-8): 1-20, https://doi.org/10.1007/s00170-016-9824-5.
  • 22. Zhang ZL, Liu ZF, Cheng Q, Qi Y, Cai LG. An approach of comprehensive error modeling and accuracy allocation for the improvement of reliability and optimization of cost of a multi-axis NC machine tool. The International Journal of Advanced Manufacturing Technology 2016; 89(1-4): 1-19, https://doi.org/10.1007/s00170-016-8981-x.
  • 23. Zhao CB. Application of SCM and PLC technology in CNC machine tool. Applied Mechanics and Materials 2014; 687-691: 22-25, https://doi.org/10.4028/www.scientific.net/AMM.687-691.22.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-67e38046-7f6b-489e-88bc-24f6aa65823d
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