PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Method for enhanced accuracy in machining free-form surfaces on CNC milling machines

Autorzy
Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The present article describes a method for enhanced accuracy in machining free-form surfaces produced on CNC milling machines. In this method, surface patch machining programs are generated based on their nominal CAD model. After the pretreatment, coordinate control measurements are carried out. The obtained results of the measurements contain information on the values and distribution of observed machining deviations. These data, after appropriate processing, are used to build a corrected CAD model of the surface produced. This model, made using reverse engineering techniques, compensates for the observed machining deviations. After regeneration of machining programs, the object processing and control measurements are repeated. As a result of the conducted procedure, the accuracy of the manufacture of the surface object is increased. This article also proposes the introduction of a simple procedure for the filtration of measurement data. Its purpose is to minimise the effect of random phenomena on the final machining error correction. The final part of the article presents the effects of the proposed method of increasing the accuracy of manufacturing on ‘raw’ and filtered measurement data. In both cases, a significant improvement in the accuracy of the machining process was achieved, with better final results obtained from the filtered measurement data. The method proposed in the article has been verified for three-axis machining with a ball-end cutter.
Rocznik
Strony
103--110
Opis fizyczny
Bibliogr. 25 poz., rys., tab., wykr.
Twórcy
  • Faculty of Mechanical Engineering, Bialystok University of Technology, ul. Wiejska 45C, 15-351 Bialystok, Poland
Bibliografia
  • 1. Ramesh R, Mannan MA, Poo AN. Error compensation in machine tools - a review. Part I: geometric, cutting-force induced and fixture dependent errors. Int J Mach Tool Manu. 2000; 40: 1235–1256.
  • 2. Ramesh R, Mannan MA, Poo AN. Error compensation in machine tools - a review. Part II: thermal errors. Int J Mach Tool Manu. 2000; 40: 1257–1284.
  • 3. Wenjie T, Weiguo G, Dawei Z, et al. A general approach for error modeling of machine tools. Int J Mach Tool Manu. 2014; 79: 17–23.
  • 4. Zuriani U, Ahmed A, Sarhan, Mardi NA, et al. Measuring of position-ing, circularity and static errors of a CNC Vertical Machining Centre for validating the machining accuracy. Measurement. 2015; 61: 39–50.
  • 5. Zhouxiang J, Bao S, Xiangdong Z et al. On-machine measurement of location errors on five-axis machine tools by machining tests and a laser displacement sensor. Int J Mach Tool Manu. 2015; 95: 1–12.
  • 6. Ibaraki S, Sawada M, Matsubara A, et al. Machining tests to identify kinematic errors on five-axis machine tools. Prec Eng. 2010; 34: 387–398.
  • 7. Zhengchun Du, Shujie Zhang, Maisheng H. Development of a multi-step measuring method for motion accuracy of NC machine tools based on cross grid encoder. Int J Mach Tool Manu. 2010; 50: 270–280.
  • 8. Vahebi Nojedeh M, Habibi M, Arezoo B. Tool path accuracy en-hancement through geometrical error compensation. Int J Mach Tool Manu. 2011; 51:471–482.
  • 9. Xiaoyan Z, Beizhi L, Jianguo Y, et al. Integrated geometric error compensation of machining processes on CNC machine tool. Proce-dia CIRP. 2013; 8: 135–140.
  • 10. Lasemi A, Xue D, Gu P. Accurate identification and compensation of geometric errors of 5-axis CNC machine tools using double ball bar. Measurement Science and Technology. 2016; 27 (5): 055004.
  • 11. Zhang X, Zhang J, Zheng X, Pang B, Zhao W. Tool orientation optimization of 5-axis ball-end milling based on an accurate cut-ter/workpiece engagement model. CIRP Journal of Manufacturing Science and Technology. 2017; 19: 106-116.
  • 12. Kim YJ, Elber G, Barton M, Pottmann H. Precise gouging-free tool orientations for 5-axis CNC machining. Computer-Aided Design. 2015; 58: 220-229.
  • 13. Barton M, Bizzarri M, Rist F, Sliusarenko O, Pottmann H. Geometry and tool motion planning for curvature adapted CNC machining. ACM Transactions on Graphics. 2021 Aug; 40 (4): 1–16. https://doi.org/10.1145/3450626.3459837
  • 14. Hansel A, Yamazaki K, Konishi K. Improving CNC machine tool geometric precision using manufacturing process analysis tech-niques. Procedia CIRP. 2014; 14: 263–268.
  • 15. Habibi M, Arezoo B, Vahebi Nojedeh M. Tool deflection and geomet-rical error compensation by tool path modification, Int J Mach Tool Manu. 2011: 51: 439–449.
  • 16. Ryu SH, Chu CN. The form error reduction in side wall machining using successive down and up milling. Int J Mach Tool Manu. 2005; 45: 1523–1530.
  • 17. Yang MY, Choi JG. A tool deflection compensation system for end milling accuracy improvement. J Manuf Sci Eng. 1998; 120: 222–229.
  • 18. Landon Y, Segonds S, Mousseigne M, et al. Correction of milling tool paths by tool positioning defect compensation. Proc Inst Mec. Eng B. 2003; 217: 1063–1073.
  • 19. Myeong-Woo Cho, Tae-il Seo, Hyuk-Dong Kwon. Integrated error compensation method using OMM system for profile milling opera-tions. J Mater Process Techol. 2003; 136: 88–99.
  • 20. Poniatowska M, Werner A. Fitting spatial models of geometric devia-tions of free-form surfaces determined in coordinate measurements. Metrol Meas Syst. 2010; 17: 599–610.
  • 21. Poniatowska M, Werner A. Simulation tests of the method for deter-mining a CAD model of free-form surface deterministic deviations. Metrol Meas Syst. 2012; 19: 151-158.
  • 22. Poniatowska M. Free-form surface machining error compensation applying 3D CAD machining pattern model. Comput Aided Design. 2015; 62: 227–235.
  • 23. Werner A, Skalski K, Piszczatowski S, et al. Reverse engineering of free-form surfaces. J Mater Process Technol. 1998; 76: 128-132.
  • 24. Kawasaki T, Jayaraman PK, Shida K, et al. An image processing approach to feature-preserving B-spline surface fairing. Comput Aided Design. 2018; 99: 1–10.
  • 25. Wang Z, Wang H. Image smoothing with generalized random walks: Algorithm and applications. Appl Soft Comput 2016; 46: 792–804.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-a8c40eca-f4a0-4618-9682-913699654292
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.