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A practical method of improving hole position accuracy in the robotic drilling process

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Abstract

The industrial robots have the remarkable advantage of flexibility over CNC machine tools in material removal of the large or complex parts, especially in hole drilling. However, the lower stiffness and thus the lower machining accuracy of the robotic drilling hinder its widespread use. Aiming at the enhancement of hole position accuracy, the optimization for stiffness of the robotic drilling system before processing and the compensation for hole position error in processing are proposed. Firstly, the maximum operating stiffness of the robotic drilling system in a certain machining task is obtained by optimizing installation angle of the motorized spindle to the end flange of the robot, which lays the foundation of a high machining accuracy of hole position. And then based on the position of the hole to be drilled, the calculation method of its corresponding compensation value is introduced, which takes both the deformation of the robot’s end under the force on it and the robot absolute positioning error into account. As for a certain robotic drilling system, it is much easier to implement to predict, and then pre-compensate the machining error of hole position for the various parts. The results reveal that the hole position errors reduce sharply at the average rate of 84.45% with compensation in all robotic drilling tests, which proves the proposed method as a practical and effective way to improve the robotic drilling accuracy of hole position.

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References

  1. 1.

    Olsson T, Robertsson A, Johansson R (2007) Flexible force control for accurate low-cost robot drilling. IEEE Int Conf Robot Autom, pp 4770–4775

  2. 2.

    Olsson T, Haage M, Kihlman H, Johansson R, Nilsson, Robertsson A, Brogardh T (2010) Cost-efficient drilling using industrial robots with high-bandwidth force feedback. Robot Comput Integr Manuf 26(1):24–38

  3. 3.

    Roukema JC, Altintas Y (2007) Generalized modeling of drilling vibrations part I: time domain model of drilling kinematics, dynamics and hole formation. Int J Mach Tools Manuf 47(9):1455–1473

  4. 4.

    Roukema JC, Altintas Y (2007) Generalized modeling of drilling vibrations part II: chatter stability in frequency domain. Int J Mach Tools Manuf 47(9):1474–1485

  5. 5.

    Zhang H, Wang J, Zhang G, Gan Z, Pan Z, Cui H, Zhu Z (2005) Machining with flexible manipulator: toward improving robotic machining performance. Proc IEEE/ASME Inter Conf Adv Intell Mechatron, pp 1127–1132

  6. 6.

    Devlieg R (2011) High-accuracy robotic drilling/milling of 737 inboard flaps. SAE Int J Aerosp 4(2):1373–1379

  7. 7.

    Hagino M, Inoue T, Mizoguchi M, Aoki W, Matsumoto F (2016) Dust collection validity and effect of hole shape accuracy of CFRP with developed hollow-type drill and dust collector. Int J Autom Technol 2016:324–333

  8. 8.

    Bi S, Liang J (2011) Robotic drilling system for titanium structures. Int J Adv Manuf Technol 54(5):767–774

  9. 9.

    Dong HY, Cao GS, Qu WW, Ke YL (2013) Processing research of industry robots drilling and countersinking automaticly. J Zhejiang Univ Sci 47(2):201–208

  10. 10.

    Guo Y, Dong H, Wang G, Ke Y (2016) Vibration analysis and suppression in robotic boring process. Int J Mach Tools Manuf 101:102–110

  11. 11.

    P Depince (1998) Parameters identification of flexible robots. Proc 1998 I.E. Inter Conference on Robotics and Automation 2: 1116–1121

  12. 12.

    Tsumugiwa T, Yokogawa R, Hara K (2003) Measurement for compliance of vertical-multi-articulated robot: application to 7-DOF robot PA-10. Proc IEEE Int Conf Robot Autom 2:2741–2746

  13. 13.

    Demester F, van Brussel H (1994) Experimental compliance breakdown of industrial robots. Trans ASME J Mech Des 116:1065–1072

  14. 14.

    Yin BU, Wenhe L, Wei T, Zhang L, Dawei L (2017) Modeling and experimental investigation of Cartesian compliance characterization for drilling robot. Int J Adv Manuf Technol 2017:1–12

  15. 15.

    Abele E, Weigold M, Rothenbücher S (2007) Modeling and identification of an industrial robot for machining applications. CIRP Ann Manuf Technol 56(1):387–390

  16. 16.

    Dumas C, Caro S, Garnier S, Furet B (2011) Joint stiffness identification of six-revolute industrial serial robots. Robot Comput Integr Manuf 27(4):881–888

  17. 17.

    Pan Z, Zhang H, Zhu Z, Wang J (2006) Chatter analysis of robotic machining process. J Mater Process Technol 173:301–309

  18. 18.

    Vosniakos GC, Matsas E (2010) Improving feasibility of robotic milling through robot placement optimization. Robot Comput Integr Manuf 26:517–525

  19. 19.

    Chen Y, Dong F (2013) Robot machining: recent development and future research issues. Int J Adv Manuf Technol 2013:1–9

  20. 20.

    Santolaria J, Conte J, Ginés M (2013) Laser tracker-based kinematic parameter calibration of industrial robots by improved CPA method and active retroreflector. Int J Adv Manuf Technol 2013:1–20

  21. 21.

    Zeng Y, Tian W, Li D, He X, Liao W (2017) An error-similarity-based robot positional accuracy improvement method for a robotic drilling and riveting system. Int J Adv Manuf Technol 88(9–12):2745–2755

  22. 22.

    Wang D, Bai Y, Zhao J (2012) Robot manipulator calibration using neural network and a camera-based measurement system. Trans Inst Meas Control 32(4):105–121

  23. 23.

    Bai Y (2007) On the comparison of model-based and modeless robotic calibration based on a fuzzy interpolation method. Int J Adv Manuf Technol 31(11):1243–1250

  24. 24.

    Li J, Li B, Shen NY, Qian H, Guo ZM (2017) Effect of the cutter path and the workpiece clamping position on the stability of the robotic milling system. Int J Adv Manuf Technol 89(9–12):2919–2933

  25. 25.

    Guo Y, Dong H, Ke Y (2015) Stiffness-oriented posture optimization in robotic machining applications. Robot Comput Integr Manuf 35:69–76

  26. 26.

    Schneider U, Drust M, Ansaloni M, Lehmann C, Pellicciari M, Leali F, Verl A (2016) Improving robotic machining accuracy through experimental error investigation and modular compensation. Int J Adv Manuf Technol 85(1–4):3–15

  27. 27.

    Kaymakci M, Kilic ZM, Altintas Y (2012) Unified cutting force model for turning, boring, drilling and milling operations. Int J Mach Tools Manuf 54:34–45

  28. 28.

    Hamade RF, Seif CY, Ismail F (2017) Extracting cutting force coefficients from drilling experiments. Int J Mach Tools Manuf 46(3):387–396

  29. 29.

    Guo Y, Yin S, Ren Y, Zhu J, Yang S, Ye S (2015) A multilevel calibration technique for an industrial robot with parallelogram mechanism. Precis Eng 40:261–272

  30. 30.

    Dacunha-Castelle D, Duflo M (2012) Probability and statistics. Springer Science & Business Media, pp 230–235

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Acknowledgments

This work has been sponsored by the BaoShan District Committee of Science and Technology (bkw2015126), and the Shanghai Municipal Commission of Economy and Informatization (CXY-2016-007). Thanks to SHANGHAI-FANUC Robotics CO. LTD for its technical support.

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Correspondence to Jing Li.

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Shen, N., Guo, Z., Li, J. et al. A practical method of improving hole position accuracy in the robotic drilling process. Int J Adv Manuf Technol 96, 2973–2987 (2018). https://doi.org/10.1007/s00170-018-1776-5

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Keywords

  • Robotic drilling
  • Position error compensation
  • Robot stiffness
  • Deformation of the robot’s end
  • Absolute positioning error