Negri, E., Fumagallia, L., Macchia, M., A review of the roles of digital twin in cps-based production systems. Procedia Manufacturing, 11, 2017, 939–948.
Grieves, M., Digital Twin: Manufacturing Excellence through Virtual Factory Replication, Digital Twin White Paper. 2015.
Armendia, M., Ghassempouri, M., Ozturk, E., Peysson, F., Twin-Control project. Twin-Control, Springer, 2018.
Kim, S.H., Nam, E., Ha, T.I., Hwang, S.H., Loo, J.H., Park, S.H., Min, B.K., Robotic Machining: A Review of Recent Progress, International Journal of Precision Engineering and Manufacturing. 2019.
Iglesias, I., Sebastian, M.A., Ares, J.E., Overview of the state of robotic machining: Current situation and future potential. Procedia Engineering 132 (2015), pp.911–917.
Ji, W., Wang, L., Industrial Robotic Machining: A Review, International Journal of Advanced Manufacturing Technology. 2019, 10.1007/s00170-019-03403-z.
Verl, A., Valente, A., Melkote, S., Brecher, C., Ozturk, E., Tunc, L.T., Robots in machining, CIRP Annals - Manufacturing Technology. 2019.
Zhang, H., Wang, J., Zhang, G., Gan, Z., Pan, Z., Cui, H., Zhu, Z., Machining with flexible manipulator: Toward improving robotic machining performance. Proc. IEEE-ASME International Conference on Advanced Intelligent Mechatronics, USA, July, 2005, 1127–1132.
Tavares, P., Silva, J.A., Costa, P., Veiga, G., Moreira, A.P., Flexible work cell simulator using digital twin methodology for highly complex systems in industry 4.0. Iberian Robotics conference, 2017, 541–552.
S. Makris, G. Michalos, G. Chryssolouris, Virtual Commissioning of an Assembly Cell with Cooperating Robots, Advances in Decision Sciences. 2012, Hindawi.
Aivaliotis, P., Georgoulias, K., Arkouli, Z., Makris, S., Methodology for enabling digital twin using advanced physics-based modelling in predictive maintenance. Procedia CIRP, 81, 2019, 417–422.
Altintas, Y., Weck, M., Chatter stability in metal cutting and grinding. Annals of CIRP 53 (2004), 619–642.
Klimchik, A., Ambiehl, A., Garnier, S., Furet, B., Pashkevich, A., Efficiency evaluation of robots in machining applications using industrial performance measure, Robotics and Computer Integrated Manufacturing. 2017.
Huynh, H.N., Rivière-Lorphèvre, E., Verlinden, O., Multibody modelling of a flexible 6-axis robot dedicated to robotic machining, IMSD: Proceedings of the 5th Joint International Conference on Multibody System Dynamics. Portugal, June, 2018.
Swevers, J., Ganseman, C., Tükel, D.B., De Schutter, J., Van Brussel, H., Optimal Robot Excitation and Identification, IEEE Transactions on robotics and automation. 13, 1997, 730–740.
Mousavi, S., Gagnol, V., Bouzgarrou, B.C., Ray, P., Stability optimization in robotic milling through the control of functional redundancies, Robotics and Computer Integrated Manufacturing. 2018.
Verlinden, O., Huynh, H.N., Kouroussis, G., Rivière-Lorphèvre, E., Modelling flexible bodies with minimal coordinates by means of the corotational formulation, Multibody System Dynamics. 42(4), 2018, 495–514, 10.1007/s11044-017-9609-0.
Cordes, M., Hintze, W., Offline simulation of path deviation due to joint compliance and hysteresis for robot machining, International Journal of Advanced Manufacturing Technology. 90, 2016, 1075–1083.
Mejri, S., Gagnol, V., Le, Thien-Phu, Sabourin, L., Ray, P., Paultre, P., Dynamic characterization of machining robot and stability analysis, International Journal Advanced Manufacturing Technology. 2015, 10.1007/s00170-015-7336-3.
Li, J., Li, B., Shen, N.Y., Qian, H., Guo, Z.M., Effect of the cutter path and the workpiece clamping position on the stability of the robotic milling system, International Journal of Advanced Manufacturing Technology. 2017, 10.1007/s00170-016-9759-x.
Dumas, C., Boudelier, A., Caro, S., Garnier, S., Ritou, M., Furet, B., Développement d'une cellule robotisée de détourage des composites. Mécanique et industries 12 (2011), 487–494.
Hardeman, T., Modeling and Identification of Industrial Robots Including Drive and Joint Flexibilities, 2008, University of Twente Ph.D. thesis.
Wang, J., Zhang, H., Fuhlbrigge, T., Improving Machining Accuracy with Robot Deformation Compensation, IEEE/RSJ International Conference on Intelligent Robots and Systems. 2011.
Hage, H., Identication et simulation physique d'un robot Staubli TX90 pour le fraisage a grande vitesse, 2012, Universite Pierre et Marie Curie - Paris VI Ph.D. thesis.
Lehmann, C., Olofsson, B., Nilsson, K., Halbauer, M., Haage, M., Robertsson, A., Sörnmo, O., Berger, U., Robot Joint Modeling and Parameter Identification Using the Clamping Method, 7th IFAC Conference on Manufacturing Modelling, Management, and Control. 2013.
G. Mercère, M. Lovera, E. Laroche, Identification of a flexible robot manipulator using a linear parameter-varying descriptor state-space structure, 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC), 2011, http://folk.ntnu.no/skoge/prost/proceedings/cdc-ecc-2011/data/papers/0921.pdf.
Karim, A., Hitzer, J., Lechler, A., Verl, A., Analysis of the Dynamic Behaviour of a Six-Axis Industrial Robot within the Entire Workspace in Respect of Machining Tasks, IEEE International Conference on Advanced Intelligent Mechatronics. 2017.
Zaeh, M.F., Roesch, O., Improvement of the machining accuracy of milling robots, Production Engineering - Research and Development. 2014.
Rafieian, F., Liu, Z., Hazel, B., Dynamic model and modal testing for vibration analysis of robotic grinding process with a 6dof flexible-joint manipulator. Proceedings of IEEE, 2009.
Huynh, H.N., Kouroussis, G., Verlinden, O., Rivière-Lorphèvre, E., Modal updating of a 6-axis robot for milling application, Proceeding of the 25th International Congress on Sound and Vibration. July 2018.
Zollo, L., Lopez, E., Spedaliere, L., Aracil, N.G., Guglielmelli, E., Identification of dynamic parameters for robots with elastic joints, Advances in Mechanical Engineering. 2014, 10.1155/2014/843186.
Klimchik, A., Bondarenko, D., Pashkevich, A., Briot, S., Furet, B., Compliance error compensation in robotic-based milling, Lectures Notes in Electrical Engineering. 2014.
Reinl, C., Friedmann, M., Bauer, J., Pischan, M., Abele, E., Von Stryk, O., Model-based Off-line Compensation of Path Deviation for Industrial Robots in Milling Applications, IEEE/ASME International Conference on Advanced Intelligent Mechatronics. 2011.
Huynh, H.N., Assadi, H., Rivière-Lorphèvre, E., Verlinden, O., Ahmadi, K., Modelling the dynamics of industrial robots for milling operations, Robotics and Computer-Integrated Manufacturing. 61, 2019.
Neubauer, M., Gattringer, H., Müller, A., Steinhauser, A., Höbarth, W., A two-stage calibration method for industrial robots with joint and drive flexibilities. Mechanical sciences 6 (2015), 191–201.
Lagarias, J.C., Reeds, J.A., Wright, M.H., Wright, P.E., Convergence Properties of the Nelder-Mead Simplex Method in Low Dimensions, SIAM Journal of Optimization. 9, 1998, 112–147.
Eiben, A.E., Smit, S.K., Evolutionary Algorithm Parameters and Methods to Tune Them, Autonomous Search. 2012, Springer, Berlin, Heidelberg, 15–36 https://link.springer.com/chapter/10.1007/978-3-642-21434-9_2.
Huynh, H.N., Development and validation of a numerical model of robotic milling to optimise the cutting parameters, Ph.D. Thesis, University of Mons (Belgium). 2019.
Cordes, M., Hintze, W., Altintas, Y., Chatter stability in robotic milling, Robotics and Computer Integrated Manufacturing. 55, 2019, 11–18, 10.1016/j.rcim.2018.07.004.
Wernholt, E., Moberg, S., Frequency-Domain Gray-Box Identification of Industrial Robots. Proceedings of the 17th World Congress The International Federation of Automatic Control, 2008.