Advertisement

Performance Evaluation of Parallel Manipulators for Milling Application

  • A. Pashkevich
  • A. Klimchik
  • S. Briot
  • D. Chablat
Conference paper

Abstract

This chapter focuses on the performance evaluation of the parallel manipulators for milling of composite materials. For this application the most significant performance measurements, which denote the ability of the manipulator for the machining are defined. In this case, optimal synthesis task is solved as a multicriterion optimization problem with respect to the geometric, kinematic, kinetostatic, elastostostatic, dynamic properties. It is shown that stiffness is an important performance factor. Previous models operate with links approximation and calculate stiffness matrix in the neighborhood of initial point. This is a reason why a new way for stiffness matrix calculation is proposed. This method is illustrated in a concrete industrial problem.

Keywords

Performance evaluation Kinetostatic modeling Elastic errors Parallel manipulators Milling application 

Notes

Acknowledgments

The work presented in this chapter was partially funded by the Region “Pays de la Loire”, France and by the EU commission (project NEXT).

References

  1. 1.
    Brogardh, T. (2007) Present and future robot control development – An industrial perspective. Annual Reviews in Control, 31/1:69–79.CrossRefGoogle Scholar
  2. 2.
    Chanal, H., Duc, E., Ray, P. (2006) A study of the impact of machine tool structure on machining processes. International Journal of Machine Tools and Manufacture, 46/2:98–106.CrossRefGoogle Scholar
  3. 3.
    Merlet, J.-P. (2000) Parallel Robots. Kluwer, Dordrecht.MATHGoogle Scholar
  4. 4.
    Koseki, Y., Tanikawa, T., Koyachi, N., Arai, T. (2000) Kinematic analysis of translational 3-DOF micro parallel mechanism using matrix method. Proceedings of IROS, W-AIV-7/1:786–792.Google Scholar
  5. 5.
    Alici, G., Shirinzadeh, B. (2005) Enhanced stiffness modeling, identification and characterization for robot manipulators. IEEE Transactions on Robotics, 21/4:554–564.CrossRefGoogle Scholar
  6. 6.
    Pashkevich, A., Chablat, D., Wenger, P. (2009) Stiffness analysis of overconstrained parallel manipulators. Mechanism and Machine Theory, 44:966–982.MATHCrossRefGoogle Scholar
  7. 7.
    Pashkevich, A., Chablat, D., Klimchik, A. (2009) Enhanced stiffness modelling of serial manipulators with passive joints. In: Ernest, H. (Eds.) Advances in Robot Manipulators, InTech Publishing, Vienna, April 2010, ISBN: 978-953-307-070-4.Google Scholar
  8. 8.
    Pashkevich, A., Klimchik, A., Chablat, D., Wenger, P. (2009) Stiffness analysis of multichain parallel robotic systems with loading. Journal of Automation, Mobile Robotics & Intelligent Systems, 3/3:75–82.Google Scholar
  9. 9.
    Merlet, J.-P. (2006) Jacobian, manipulability, condition number, and accuracy of parallel robots. Transaction of the ASME Journal of Mechanical Design, 128/1:199–206.CrossRefGoogle Scholar
  10. 10.
    Briot, S., Pashkevich, A., Chablat, D. (2010) Optimal technology oriented design of parallel robots for high-speed machining applications. IEEE 2010 International Conference on Robotics and Automation, Anchorage, Alaska, May 3–8, 2010, pp. 1155–1161.Google Scholar
  11. 11.
    Merlet, J.-P. (2006) Computing the worst case accuracy of a PKM over a workspace or a trajectory. The 5th Chemnitz Parallel Kinematics Seminar, Chemnitz, Germany, pp. 83–96.Google Scholar
  12. 12.
    El-Khasawneh, B.S., Ferreira, P.M. (1999) Computation of stiffness and stiffness bounds for parallel link manipulators. International Journal of Machine Tools and Manufacture, 39/2:321–342.CrossRefGoogle Scholar
  13. 13.
    Bouzgarrou, B.C., Fauroux, J.C., Gogu, G., Heerah, Y. (2004) Rigidity analysis of T3R1 parallel robot uncoupled kinematics. Proceedings of the 35th International Symposium on Robotics, Paris, March.Google Scholar
  14. 14.
    Deblaise, D., Hernot, X., Maurine, P. (2006) Systematic analytical method for PKM stiffness matrix calculation. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Orlando, FL, May, pp. 4213–4219.Google Scholar
  15. 15.
    Ghali, A., Neville, A.M., Brown, T.G. (2003) Structural Analysis: A Unified Classical and Matrix Approach. Spon Press, New York, NY.Google Scholar
  16. 16.
    Gosselin, C.M., Zhang, D. (2002) Stiffness analysis of parallel mechanisms using a lumped model. International Journal of Robotics and Automation, 17/1:17–27.Google Scholar
  17. 17.
    Majou, F., Gosselin, C.M, Wenger, P., Chablat, D. (2007) Parametric stiffness analysis of the orthoglide. Mechanism and Machine Theory, 42/3:296–311.CrossRefGoogle Scholar
  18. 18.
    Pashkevich, A., Klimchik, A., Chablat, D., Wenger, P. (2009) Accuracy improvement for stiffness modeling of parallel manipulators. Proceedings of 42nd CIRP Conference on Manufacturing Systems, Grenoble, France, June 2009.Google Scholar
  19. 19.
    Akin, J.E. (2005) Finite Element Analysis With Error Estimators: An Introduction to the FEM and Adaptive Error Analysis for Engineering Students. Elsevier, Amsterdam.Google Scholar
  20. 20.
    Chablat, D., Wenger, Ph. (2003) Architecture optimization of a 3-DOF parallel mechanism for machining applications, the orthoglide. IEEE Transactions on Robotics and Automation, 19/3:403–410.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • A. Pashkevich
    • 1
  • A. Klimchik
    • 1
  • S. Briot
    • 2
  • D. Chablat
    • 3
    • 4
  1. 1.Ecole des Mines de Nantes, IRCCyN UMR CNRS 6597Nantes Cedex 3France
  2. 2.Ecole Centrale de Nantes, IRCCyN UMR CNRS 6597Nantes Cedex 3France
  3. 3.Ecole Centrale de Nantes, IRCCyN UMR CNRS 6597Nantes Cedex 3France
  4. 4.Institut de Recherches en Communications et Cybernetique de NantesNantesFrance

Personalised recommendations