Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 33087
Milling Simulations with a 3-DOF Flexible Planar Robot
Authors: Hoai Nam Huynh, Edouard Rivière-Lorphèvre, Olivier Verlinden
Abstract:
Manufacturing technologies are becoming continuously more diversified over the years. The increasing use of robots for various applications such as assembling, painting, welding has also affected the field of machining. Machining robots can deal with larger workspaces than conventional machine-tools at a lower cost and thus represent a very promising alternative for machining applications. Furthermore, their inherent structure ensures them a great flexibility of motion to reach any location on the workpiece with the desired orientation. Nevertheless, machining robots suffer from a lack of stiffness at their joints restricting their use to applications involving low cutting forces especially finishing operations. Vibratory instabilities may also happen while machining and deteriorate the precision leading to scrap parts. Some researchers are therefore concerned with the identification of optimal parameters in robotic machining. This paper continues the development of a virtual robotic machining simulator in order to find optimized cutting parameters in terms of depth of cut or feed per tooth for example. The simulation environment combines an in-house milling routine (DyStaMill) achieving the computation of cutting forces and material removal with an in-house multibody library (EasyDyn) which is used to build a dynamic model of a 3-DOF planar robot with flexible links. The position of the robot end-effector submitted to milling forces is controlled through an inverse kinematics scheme while controlling the position of its joints separately. Each joint is actuated through a servomotor for which the transfer function has been computed in order to tune the corresponding controller. The output results feature the evolution of the cutting forces when the robot structure is deformable or not and the tracking errors of the end-effector. Illustrations of the resulting machined surfaces are also presented. The consideration of the links flexibility has highlighted an increase of the cutting forces magnitude. This proof of concept will aim to enrich the database of results in robotic machining for potential improvements in production.Keywords: Control, machining, multibody, robotic, simulation.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1126555
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1366References:
[1] A. Abele, M. Weigold, S. Rothenb¨ucher, “Model and identification of an industrial robot for machining applications,” Annals of CIRP, vol. 56-1, pp. 387–390, 2007.
[2] S. Caro, C. Dumas, S. Garnier, B. Furet, “Workpiece placement optimization for machining operations with a kuka kr270-2 robot,” IEEE International Conference on Robotics and Automation (ICRA), pp. 2921–2926, May, 2013.
[3] C. Dumas, A. Boudelier, S. Caro, S. Garnier, M. Ritou, B. Furet, “D´eveloppement d’une cellule robotis´ee de d´etourage des composites,” M´ecanique et industries, vol. 12, pp. 487–494, 2011.
[4] H. Zhang, J. Wang, G. Zhang, Z. Gan, Z. Pan, H. Cui, Z. Zhu, “Machining with flexible manipulator: Toward improving robotic machining performance,” Proc. IEEE-ASME International Conference on Advanced Intelligent Mechatronics, pp. 1127–1132, USA, July, 2005.
[5] Z. Pan, H. Zhang, Z. Zhu, J. Wang, “Chatter analysis of robotic machining process,” Journal of Material Processing Technology, vol. 173, pp. 301–309, 2006.
[6] J. Tlusty, M. Polacek, “The stability of the machine tool against self-excited vibration in machining,” ASME International Research in Production Engineering, pp. 465–474, 1963.
[7] S. G. Mousavi, V. Gagnol, B.C. Bouzgarou, P. Ray, “Dynamic behaviour model of a machining robot,” ECCOMAS Multibody Dynamics, pp. 771–779, July, 2013.
[8] U. Schneider, M. Drust, A. Puzik, A. Verl, “Compensation of errors in robot machining with a parallel 3d-piezo compensation mechanism,” Procedia CIRP, vol. 7, pp. 305–310, 2013.
[9] N.R. Slavkovic, D.S. Milutinovic, M.M. Glavonjic, “A method for off-line compensation of cutting force-induced errors in robotic machining by tool path modification,” Int J Adv Manuf Technol, Springer, vol. 70, pp. 2083–2096, 2014.
[10] C. Dumas, S. Caro, S. Garnier, B. Furet, “Joint stiffness identification of six-revolute industrial serial robots,” Robotics and Computer-Integrated Manufacturing, vol. 27, pp. 881–888, 2011.
[11] O. Verlinden, G. Kouroussis, C. Conti, “EasyDyn: a framework based on free symbolic and numerical tool for teaching multibody systems,” in Multibody Dynamics 2005, ECCOMAS Thematic Conference, Madrid, Spain, 21-24 June 2005.
[12] O. Verlinden, L. Ben F´ekih and G. Kouroussis, “Symbolic generation of the kinematics of multibody systems in EasyDyn: From MuPAD to Xcas/Giac,” Theoretical and Applied Mechanics Letters, vol. 3, no. 1, pp. 013012, doi: 10.1063/2.13013012, 2013.
[13] H.N. Huynh, E. Rivi`ere, O. Verlinden, “Integration of machining simulation within a multibody framework: application to milling,” IMSD: The 4th Joint International Conference on Multibody System Dynamics, Canada, June, 2016.
[14] S. Mousavi, V. Gagnol, B. C. Bouzgarrou, P. Ray, “Dynamic model and stability prediction in robotic machining,” Int J Adv Manuf Technol (2016), Springer, pp. 1–13, June 2016.
[15] A. Cardona, “Superelements modelling in flexible multibody dynamics,” Multibody System Dynamics, vol. 4, pp. 245–266, 2000.
[16] O. Verlinden, H.N. Huynh, E. Rivi`ere, “Modelling of flexible bodies with minimal coordinates by means of the co-rotational formulation,” The 4th Joint International Conference on Multibody System Dynamics, Canada, June, 2016.
[17] E. Rivi`ere, E. Filippi, P. Dehombreux, “Forces, vibrations and roughness prediction in milling using dynamic simulation,” Proceedings, (Fifth International Conference on High Speed Machining (HSM 2006)), Mars, Metz, France 2006.
[18] E. Rivi`ere, E. Filippi, P. Dehombreux, “Chatter prediction using dynamic simulation,” International Review of Mechanical Engineering (I.RE.M.E.), vol. 1, pp. 78–86, 2007.
[19] G. Peign´e, H. Paris, D. Brissaud, “A model of milled surface generation for time domain simulation of high-speed cutting,” Proceedings of the Institution of Mechanical Engineers, vol. 217, pp. 919–930, 2003.
[20] S. Engin, Y. Altintas, “Mechanics and dynamics of general milling cutters. Part I: helical end mills,” International Journal of Machine Tools and Manufacture, vol. 41, pp. 2195–2212, 2001.
[21] John J. Craig, Introduction to Robotic: Mechanics and Control. Pearson, Prentice Hall, 2005.
[22] C. Renotte, A. VandeWouwer, M. Remy, “A simple frequency domain approach to the tuning of pid control: design of an interactive software tool,” Journal A. Benelux Quaterly Journal on Automatic Control, vol. 42-3, pp. 23–27, 2001.
[23] T. Insperger, B.P. Mann, G. St´ep´an, P.V. Bayly, “Stability of up-milling and down-milling, part I: alternative analytical methods,” International Journal of Machine Tools and Manufacture, vol. 43, pp. 25–34, 2003.
[24] B. Siciliano, L. Sciavicco, L. Villani, G. Oriolo, Robotics: Modelling, Planning and Control. Springer, 2010.
[25] M.H. Raibert, J.J. Craig, “Hybrid position/force control of manipulators,” Journal of Dynamic Systems, Measurement and Control, vol. 103-2, pp. 126–133, 1981.