Cross-directional feed rate optimization using tool-path surface

Abstract

With the state-of-the-art technologies, NC tool paths are optimized along the feed direction of the tool path without the consideration of the consistency in the crossing (step-over) direction. As a result, the surface finishing is not fully optimal. In this paper, a method that performs the feed rate scheduling with consistency in crossing direction is proposed. The core of the method involves three steps: cross-directional information reconstruction, tool-path feature curve construction, and nominal feed rate computation. To reconstruct the cross-directional information, the neighbor projections, which are the nearest points on the adjacent pass segments of each GOTO point, are computed. For feature curve construction, feature points of the tool path are identified and then connected into curves along the crossing direction based on the neighbor projection information. The tool path is then divided according to the feature curves into feed rate intervals. The nominal feed rate of each feed rate interval is computed and blended with the nominal feed rates of the crossing neighbors, to achieve the consistency in the crossing direction. Information on the nominal feed rates and feature points is sent to the CNC to compute the final feed rate scheduling that takes advantages of the cross-consistent nominal feed rates. The proposed method is implemented in a lab-developed software program and validated experimentally using a commercial CNC. Experiments and simulations on two workpieces verify the effectiveness of the proposed cross-directional feed rate optimization method.

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References

  1. 1.

    Liu X, Li Y, Ma S, Lee CH (2015) A tool path generation method for freeform surface machining by introducing the tensor property of machining strip width. Comput Aided Des 66:1–13

    Article  Google Scholar 

  2. 2.

    Li X, Zhao H, Zhao X, Ding H (2016) Dual sliding mode contouring control with high accuracy contour error estimation for five-axis CNC machine tools. Int J Mach Tools Manuf 2016:S0890695516300529

    Google Scholar 

  3. 3.

    Liang H, Hong H, Svoboda J (2002) A combined 3D linear and circular interpolation technique for multi-Axis CNC machining. J Manuf Sci Eng 124(2):305–312

    Article  Google Scholar 

  4. 4.

    Sun YW, Zhou JF, Guo DM (2013) Variable feedrate interpolation of NURBS toolpath with geometric and kinematical constraints for five-axis CNC machining. J Syst Sci Complex 26(5):757–776

    Article  Google Scholar 

  5. 5.

    Kim TKT, Sarma SE (2003) Optimal sweeping paths on a 2-manifold: a new class of optimization problems defined by path structures. IEEE Trans Rob Autom 19(4):613–636

    Article  Google Scholar 

  6. 6.

    Li XY, Lee CH, Hu PC, Zhang Y, Yang FZ (2017) Cutter partition-based tool orientation optimization for gouge avoidance in five-axis machining. Int J Adv Manuf Technol 95(5–8):1–17

  7. 7.

    Han L, Gao XS, Li H, Zhang LX (2009) Arbitrary shape reconstruction from NC sectional data and applications in space cutter compensation and interference detection. 11th International Conference on Computer-Aided Design and Computer Graphics, CAD/Graphics 2009, Huangshan, China, August 19–21, 2009. DBLP

  8. 8.

    Jiao XM, Bayyana NR (2008) Identification of C1 and C2 discontinuities for surface meshes in CAD. Comput Aided Des 40(2):160–175

    Article  Google Scholar 

  9. 9.

    Vidal V, Christian W, Florent D (2011) Robust feature line extraction on CAD triangular meshes. International conference on computer graphics theory and applications 106–112

  10. 10.

    Lasemi A, Xue D, Gu P (2010) Recent development in CNC machining of freeform surfaces: a state-of-the-art review. Comput Aided Des 42(7):641–654

    Article  Google Scholar 

  11. 11.

    Bosetti P, Enrico B (2014) Feed-rate and trajectory optimization for CNC machine tools. Robot Comput Integr Manuf 30(6):667–677

    Article  Google Scholar 

  12. 12.

    Huan Z, Zhu LM, Ding H (2013) A real-time look-ahead interpolation methodology with curvature-continuous B-spline transition scheme for CNC machining of short line segments. Int J Machine Tools Manuf 65:88–98

  13. 13.

    Fan W, Lee CH, Chen JH (2015) A realtime curvature-smooth interpolation scheme and motion planning for CNC machining of short line segments. Int J Mach Tool Manu 96(96):27–46

    Article  Google Scholar 

  14. 14.

    Fan W, Gao XS, Yan W, Yuan CM (2012) Interpolation of parametric CNC machining path under confined jounce. Int J Adv Manuf Technol 62(5):719–739

    Article  Google Scholar 

  15. 15.

    Sencer B, Ishizaki K, Shamoto E (2015) A curvature optimal sharp corner smoothing algorithm for high-speed feed motion generation of NC systems along linear tool paths. Int J Adv Manuf Technol 76(9–12):1977–1992

    Article  Google Scholar 

  16. 16.

    Ye P, Shi C, Yang K, Lv Q (2008) Interpolation of continuous micro line segment trajectories based on look-ahead algorithm in high-speed machining. Int J Adv Manuf Technol 37(9–10):881–897

    Article  Google Scholar 

  17. 17.

    Dong JC, Wang TY, Li B, Ding YY (2014) Smooth feedrate planning for continuous short line tool path with contour error constraint. Int J Mach Tool Manu 76:1–12

    Article  Google Scholar 

  18. 18.

    Liu XH, Peng JQ, Si L, Wang ZB (2017) A novel approach for NURBS interpolation through the integration of acc-jerk-continuous-based control method and look-ahead algorithm. Int J Adv Manuf Technol 88:961–969

  19. 19.

    Su ZW, Zhou HC, Hu PC, Fan W (2018) Three-axis CNC machining feedrate scheduling based on the feedrate restricted interval identification with sliding arc tube. Int J Adv Manuf Technol 99:1047–1058

  20. 20.

    Quan W, Meng W, Zhang X (2014) The extraction of feature lines on 3D models: a survey. International Conference on Virtual Reality and Visualization (ICVRV). IEEE, 2014

  21. 21.

    Tamás V, Facello MA, Zsolt T (2007) Automatic extraction of surface structures in digital shape reconstruction. Comput Aided Des 39(5):379–388

    Article  Google Scholar 

  22. 22.

    Ke YL, Fan SQ, Zhu WD, Li A, Liu FS, Shi XQ (2006) Feature-based reverse modeling strategies. Comput Aided Des 38(5):485–506

    Article  Google Scholar 

  23. 23.

    Zhang H (2016) Triangular mesh reconstruction of tool path surface for lateral optimization. Dissertation, Huazhong University of Science & Technology

  24. 24.

    Zhou HC, Lang ML, Hu PC, Su ZW, Chen JH (2018) The modeling, analysis, and application of the in-process machining data for CNC machining. Int J Adv Manuf Technol

  25. 25.

    Functions of the TNC 640. HEIDENHAIN, 2016

  26. 26.

    Yan CY, Lee CH, Yang JZ (2012) Three-axis tool-path B-spline fitting based on preprocessing, least square approximation and energy minimization and its quality evaluation. Modern Machinery (MM) Science Journal 2012(4):351–357

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Acknowledgments

The authors acknowledge the help of Chenglei Zhang and Zhiwei Su.

Funding

This study received support from the National Natural Science Foundation of China (51575386).

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Correspondence to Fangzhao Yang.

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Lee, C., Yang, F., Zhou, H. et al. Cross-directional feed rate optimization using tool-path surface. Int J Adv Manuf Technol 108, 2645–2660 (2020). https://doi.org/10.1007/s00170-020-05336-4

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Keywords

  • CNC machining
  • Tool-path surface
  • Feature curve identification
  • Feed rate scheduling
  • Cross-directional optimization