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Off-line correction method suitable for a machining robotapplication to composite materials

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Abstract

Robotic machining finds its place in a multitude of applications with increasingly restrictive dimensional tolerances. In the machining of left-handed shapes for the production of large composite supports (4-m diameter), the expected shape accuracy is a few hundredths. The industrial robot is not initially compatible with such performance criteria. The literature possesses several ways to improve the accuracy of industrial robots such as stiffness, or stress modeling with dynamic measurement of forces during machining. These methods are difficult to apply in an industrial context because they are too costly in terms of time and investments related to the identification means. This study proposes a new off-line correction based on the mirror correction applied during machining. This method is quickly applicable and required only a 3D vision system. Moreover, it is adapted to any 6-axis serial robot, unlike exiting methods that requires a robot modeling and characterization, which is adapted to a specific robot only. After measuring the position of the tool during a first machining operation, this measurement is compared with the initial program setpoint for identify the robot deviation. A smart and autonomous process is used to re-edit the toolpath to compensate for the deviation. A new machining operation quantifies the correction by producing a part with improved shape tolerances. This article presents the development method, the implementation, and the results obtained following its industrial context. A gain of more than 80% is identified and an analysis of this result is proposed. Future complementary developments are suggested as perspectives.

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Abbreviations

Vc:

Cutting speed in m/min

Fz:

Feed per revolution in mm/tooth

COM method:

Tool material pair method

EtC-track :

Standard deviation of C-track device

Pm:

Measured tool position

Pi:

Desired tool position

D :

Deviation between measured and desired tool position

E :

Error vector

E * :

Correction vector

P :

Measured tool position by C-track device

P* :

Correction tool position

CAM:

Computer-aided manufacturing

CAM_p:

Computer-aided manufacturing desired tool position

MES_p:

Measured tool position by C-track device

RMS:

Root mean square

Xt, Yt:

Effort measurement frame

Ef:

Measured effort

Eini :

Initial measured deviation by ATOS device

Eatos :

Measured deviation after correction by ATOS device

GYZ :

Calculate gain on the Y-Z sample plane

References

  1. Muller C (2019) Welcome to the IFR press conference. Shanghai

  2. Shiakolas PS, Conrad KI, Yih TC (2002) On the accuracy, repeatability, and degree of influence of kinematics parameters for industrial robots. Int J Model Simul 22(4):245–254

    Article  Google Scholar 

  3. Dumas C, Boudelier A, Caro S, Garnier S, Ritou M, Furet B (2011) Development of a robotic cell for trimming composites. Mecanique Ind 12(6):487–494

    Article  Google Scholar 

  4. Olabi A (2011) Improving the accuracy of industrial robots for high-speed machining applications, National higher school of arts and crafts

  5. Belchior J, Guillo M, Courteille E, Maurine P, Leotoing L, Guines D (2013) Off-line compensation of the tool path deviations on robotic machining: application to incremental sheet forming. Robot Comput Integr Manuf 29(4):58–69

    Article  Google Scholar 

  6. Gallot G, Dumas C, Garnier S, Caro S, Furet B (2012) Dynamic path correction for robotic processing, 13rd national conference aip primeca. (France)

  7. Cordes M, Hintze W (2016) Offline simulation of path deviation due to joint compliance and hysteresis for robot machining. Int J Adv Manuf Technol 90:1075–1083. https://doi.org/10.1007/s00170-016-9461-z

    Article  Google Scholar 

  8. Garnier S (2017) Identification and modelling for the development of machining monitoring and production robotics, phd thesis. (France)

  9. Schneider U, Drust M, Ansaloni M, Lehmann C, Pellicciari M, Leali F, Gunnink JW, Verl A (2016) Improving robotic machining accuracy through experimental error investigation and modular compensation. The International Journal of Advanced Manufacturing Technology 85:3–15

    Article  Google Scholar 

  10. Teti R (2002) Machining of composite materials. CIRP Ann-Manuf Technol 51:611–634

    Article  Google Scholar 

  11. Chibane H, Morandeau A, Serra R, Bouchou A, Leroy R (2013) Optimal milling conditions for carbon/epoxy composite material using damage and vibration analysis. Int J Adv Manuf Technol 68:1111–1121. https://doi.org/10.1007/s00170-013-4903-3

    Article  Google Scholar 

  12. Abrão AM, Rubio JCC, Faria PE, Davim JP (2008) The effect of cutting tool geometry on thrust force and delamination when drilling glass fibre reinforced plastic composite. Mater Des 29:508–513. https://doi.org/10.1016/j.matdes.2007.01.016

    Article  Google Scholar 

  13. Voß R, Henerichs M, Kuster F, Wegener K (2014) Chip root analysis after machining carbon fiber reinforced plastics (CFRP) at different fiber orientations. Procedia CIRP 14:217–222. https://doi.org/10.1016/j.procir.2014.03.013

    Article  Google Scholar 

  14. Pierre A (2013) Metrology: precision vs. accuracy, error vs. uncertainty. https://aurelienpierre.com

  15. Siciliano B, Kathib O (2008) Handbook of robotics, springer

  16. Schneider U, Ansaloni M, Drust M, Leali F, Verl A, (2013) Experimental investigation of sources of error in robot machining, International Workshop on Robotics in Smart Manufacturing. Springer, pp. 14–26

  17. Mustafa S.K, Pey Y.T, Yang G, Chen I (2010) A geometrical approach for online error compensation of industrial manipulator, Proceedings of ieee/asme international conference on advanced intelligent mechatronics, pp. 738–743 (montreal, Canada)

  18. Schneider U, Drust M, Diaz Posada J, Verl A (2013) Position control of an industrial robot using an optical measurement system for machining purposes

  19. Zhang H, Wang J, Zhang G, Gan Z, Pan Z, Cui H, Zhu Z (2005) Machining with flexible manipulator, Improving robotic machining performance. IEEE, pp. 1127–1132

  20. Pan Z, Zhang H, Zhu Z, Wang J (2006) Chatter analysis of robotic machining process. J Mater Process Technol 173(3):301–309

    Article  Google Scholar 

  21. Chen T, Xiang J, Gao F, Liu X, Liu G (2019) Study on cutting performance of diamond-coated rhombic milling cutter in machining carbon fiber composites. Int J Adv Manuf Technol 103(9-12):4731–4737

    Article  Google Scholar 

  22. Tankus K, Tascioglu E, Atay G, Brunken H, Kaynak Y (2020) The effect of cutting parameters and cutting tools on machining performance of carbon graphite material. Mach Sci Technol 24:96–111. https://doi.org/10.1080/10910344.2019.1701020

    Article  Google Scholar 

  23. Henerichs M, Voß R, Kuster F, Wegener K (2015) Machining of carbon fiber reinforced plastics: Influence of tool geometry and fiber orientation on the machining forces. CIRP J Manuf Sci Technol 9:136–145. https://doi.org/10.1016/j.cirpj.2014.11.002

    Article  Google Scholar 

  24. NF E66-520-1 (1997) Operating range of cutting tools - tool-material pair

  25. Creaform brochure. www.creaform3d.com/sites/default/files/assets/brochures/files/fr-vxtrack_feuillet_fr_11122018

  26. Atos brochure. www.cetimsudouest.fr/technologies-moyens/optique

  27. Sheikh-Ahmad JY (2009) Machining of polymer composites. Springer, New York

    Book  Google Scholar 

  28. Gaitonde VN, Karnik SR, Rubio JC, Correia AE, Abrão AM, Davim JP (2008) Analysis of parametric influence on delamination in high-speed drilling of carbon fiber reinforced plastic composites. J Mater Process Technol 203:431–438. https://doi.org/10.1016/j.jmatprotec.2007.10.050

    Article  Google Scholar 

  29. Morandeau A, Leroy R, Bouchou A, Bonhoure D (2011) Usinage des composites renforcés en fibres de carbone: stratégie de surfaçage pour limiter les efforts de coupe, 17th National Composites Days (JNC17). p. 126

  30. Olabi A, Damak M, Bearee R, Gibaru O, Leleu S (2012) Improving the accuracy of industrial robots by offline compensation of joints errors. In: Industrial Technology (ICIT), 2012 IEEE International Conference On. IEEE, pp. 492–497.

  31. Lei WT, Sung MP (2008) Nurbs-based fast geometric error compensation for cnc machine tools. Int J Mach Tools Manuf 48(3-4):307–319

    Article  Google Scholar 

  32. Guiassa R (2012) Methods of compensating for machining errors using measurement on machine tools, Phd thesis, Polytechnique school of Montreal

  33. Shen H, Fu J, He Y, Yao X (2012) On-line asynchronous compensation methods for static/quasi-static error implemented on cnc machine tools. Int J Mach Tools Manuf 60:14–26

    Article  Google Scholar 

  34. Thiery C, Scherrer B (2010) Least-Squares λ Policy Iteration: optimism and bias-variance trade-off for optimal control, 26

  35. Duan H, Zhang R, Yu F, Gao J, Chen Y (2016) Optimal trajectory planning for glass-handing robot based on execution time acceleration and jerk. J Robot 2016:1–9. https://doi.org/10.1155/2016/9329131

    Article  Google Scholar 

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Authors and Affiliations

  1. Laboratoire Génie de Production, Ecole Nationale d’Ingénieurs de Tarbes, Université de Toulouse, Tarbes Cedex, France

    Guillaume Carriere, Mourad Benoussaad, Vincent Wagner & Gilles Dessein

  2. Groupe LAUAK, LAUAK Innovative Solutions, Bagnères de Bigorre, France

    Benjamin Boniface

Authors
  1. Guillaume Carriere
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  2. Mourad Benoussaad
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  3. Vincent Wagner
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  4. Gilles Dessein
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  5. Benjamin Boniface
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Correspondence to Guillaume Carriere.

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Carriere, G., Benoussaad, M., Wagner, V. et al. Off-line correction method suitable for a machining robotapplication to composite materials. Int J Adv Manuf Technol 110, 2361–2375 (2020). https://doi.org/10.1007/s00170-020-05947-x

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  • DOI: https://doi.org/10.1007/s00170-020-05947-x

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