Abstract
Automation of forging processes is important for both safety and efficiency in today's advanced manufacturing operations. This work supports the development of an Intelligent Open Die Forging System which will integrate state-of-the-art modelling techniques, automatic die selection and sequencing, full system dynamic simulation, automatic machine programming and coordination, and sensor-based process control to enable the production of more general and complex workpiece geometries than are achievable using current forging methods. Effective automation of this open die forging system requires the coordination and control of the major system components: press, robot, and furnace. In particular, forces exerted on the robot through its manipulation of the workpiece during forging must be minimized to avoid damage to the manipulator mechanism. In this paper, the application of neural networks for compliance control of the forging robot to minimize these forces is investigated. Effectiveness of the neural network-based compliance control module is evaluated through a full dynamic system simulation, which will later form a central part of the complete Intelligent Forging System. Dynamic simulation of the robot is achieved using an efficient O(N) recursive algorithm, while material flow of the workpiece is modeled with a finite element approach. Simulation and timing results for the complete processing system for a specific open die forging example are presented.
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References
Ang, C. S.: Implementation of the virtual environment force control concept an industrial robot, MS Thesis, Department of Mechanical Engineering, Penn State University, 1994.
Appleton, E., Higginbotham, W. B. and Law, D.: Open die forging with an industrial robot, The Industrial Robot (December 1979), 191–194.
Appleton, E.: Open-die forging operations by industrial robot, Robotic Technology 15 (1983), 160–168.
Asada, H.: Teaching and learning of compliance using neural nets: Representation and generation of nonlinear compliance, in Proc. 1990 IEEE Int. Conf. Robotics and Automation, 1990, pp. 1237–1244.
Brandl, H., Johanni, R. and Otter, M.: A very efficient algorithm for the simulation of robots and similar multibody systems without inversion of the mass matrix, Proc. IFAC/IFIP/IMACS Int. Symp. Theory of Robots, 1986.
Cha, D. H.: Compliance control of telerobot systems using a recurrent neural network, in Proc. Japan-USA Symp. Flexible Automation, Part 1, 1992, pp. 271–274.
Connoly, T. H.: Neural network hybrid position/force control, in Proc. 1993 Int. Conf. Intelligent Robots and Systems, 1993, pp. 240–244.
Featherstone, R.: Robot Dynamics Algorithms, Kluwer, Boston, 1987.
FIA, Open Die Forging Manual, 3rd edn, Forging Industry Association, Cleveland, OH, 1982.
Funahashi, K. I.: On the approximate realization of continuous mappings by neural networks, Neural Networks 2 (1989), 183–192.
Han, C. S., Gandhi, R. V. and Srinivasan, R.: Optimum design of forging die shapes using nonlinear finite element analysis, AIAA J. 31(4) (1993), 774–781.
Her, M. G.: Automated robotic deburring of parts using compliance control, ASME J. Dynamic Systems, Measurement, and Control 113(1) (1991), 60–66.
Kazerooni, H.: Compliance control and stability analysis of cooperating robot manipulators, Robotica 7(3) (1989), 191–198.
Kobayashi, S., Oh, S. and Altan, T.: Metal Forming and the Finite Element Method, Oxford University Press, New York, 1989.
Kwan, C. M.: Robust force/motion control of constrained robots using neural networks, in Proc. IEEE Conf. Decision and Control, Vol. 2, 1994, pp. 1862–1867.
Lee, C. H. and Kobayashi, S.: New solution to rigid plastic deformation problems using a matrix method, ASME Trans. J. Engrg. Industry 95 (1973), 865–873.
Lilly, K. W.: Efficient Dynamic Simulation of Robotic Mechanisms, Kluwer, Boston, 1993.
Lilly K. W. and Jablokow A. G.: Intelligent open die forging, Int. J. Industrial Engrg. 2(3) (1995).
Lilly, K. W. and Melligeri, A. S.: Efficient dynamic simulation of an integrated robot/forge near net-shape processing center, in R. P.Judd and N. A.Kheir (eds), Intelligent Manufacturing Systems, Pergamon, New York, 1992, pp. 347–351.
Lilly, K. W. and Orin, D. E.: Efficient dynamic simulation of a single closed-chain manipulator, in Proc. 1991 IEEE Int. Conf. Robotics and Automation, Vol. 1, 1991, pp. 210–215.
Maekawa, A.: Compliance control of an articulted manipulator, JSME Int. J. Ser. C: Dynamics, Control, Robotics, Design and Manufacturing 37(1) (1994), 155–161.
Melligeri, A. S. and Lilly, K. W.: Application of neural networks in compliance control of an integrated robot/forge processing center, in R.Sodhi (ed.), Advances in Manufacturing Systems: Design, Modeling and Analysis, Elsevier, New York, 1993, pp. 445–450.
Orin, D. E. and McGhee, R. B.: Dynamic computer simulation of robotic mechanisms, Int. J. Robotics Res. 7(5) (1981), 32–47.
Raibert, M. and Craig, J.: Hybrid position/force control of manipulators, ASME J. Dynamic Systems, Measurement, and Control 102(2) (1981), 126–133.
Roberson, R. E. and Schwertassek, R. F., Introduction to the Dynamics of Multibody Systems, Springer, Berlin, 1987.
Rodiguez, G., Jain, A. and Kreutz-Delgado, K.: A spatial operator algebra for manipulator modeling and control, Int. J. Robotics Res. 10 (1991), 371–381.
Rumelhart, D. E. and McClelland, J. L.: Parallel Distributed Processing, MIT Press, 1986.
Venkataraman, S. T., Gulati, S., Barhen, J. and Toomarian, N.: Parameter learning and compliance control using neural networks, in G. A.Bekey and K. Y.Goldberg (eds), Neural Networks in Robotics, Kluwer, Boston, 1993, pp. 193–216.
Vitscheff, V.: A programmable manipulator for closed die forging, Proc. 9th Int. Drop Forging Convention, Kyoto, Japan, 1977.
Waibel, B. J.: Theory and experiments on the stability of robot compliance control, IEEE Trans. Robotics and Automation 7(1) (1991), 95–104.
Walker, M. W. and Orin, D. E.: Efficient dynamic computer simulation of robotic mechanisms, ASME J. Dynamic Systems, Measurement, and Control 104 (1982), 205–211.
Wasserman, P. D., Neural Computing, Van Nostrand/Reinhold, New York, 1989.
Westmeyer, W. B.: Modernization speeds open die operation, Forging, Winter Issue (1991), 30–34.
Wright, J. R.: Investing in Excellence, Forging, Winter Issue (1991), 16–19.
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Lilly, K.W., Melligeri, A.S. Dynamic simulation and neural network compliance control of an intelligent forging center. J Intell Robot Syst 17, 81–99 (1996). https://doi.org/10.1007/BF00435717
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DOI: https://doi.org/10.1007/BF00435717