On-Line Identification and Suppression of Time Varying Machining Chatter in Turning Via Dynamic Data System (DDS) Methodology

  • Shing-Yuan Tsai
  • Shien-Ming Wu


The time varying stability of the machining process necessitates a technique of on-line chatter identification and control. The Dynamic Data System (DDS) methodology which has been applied in the field of manufacturing and proved itself as a powerful tool to identify the machining process under working conditions is implemented for this purpose.

Mathematical models of the machining process with an inherent stochastic nature were developed as discrete ARMA (n,n-1) models. Based on off-line analysis, the peak of power spectral density corresponding to the dynamic mode of workpiece fundamental natural frequency served as a simple and reliable index of stability for on-line chatter identification. Using this criterion, the influence of speed and feed on stability were studied and the strategy of changing speed and feed incremently to find stable cutting conditions without sacrificing productivity was proposed. Due to the current capability of microcomputer, a simple and fast adaptive modeling technique was adopted for the on-line machining process identification. A forecasting control of chatter scheme was implemented to predict the generation of chatter. In addition, the vibration signal was purified from the results of the dynamic analysis of the chuck-workpiece-tailstock system, and a self-learning scheme was established to determine the threshold level of stability in each cutting process.

A chatter suppression controller was designed and interfaced to the PT15 CNC lathe. Cutting tests demonstrated the successful use of the theoretical and technical development by the DDS approach.


Machine Tool Power Spectral Density Machine Process Control Chart Vibration Signal 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. [1]
    H. E. Merrit, “Theory of self-excited machine tool chatter,” J. Eng. Industry, Trans. ASME, Vol. 87, No. 4, pp. 447–454, 1965.CrossRefGoogle Scholar
  2. [2]
    S. A. Tobias, Machine Tool Vibration, John Wiley, 1965.Google Scholar
  3. [3]
    F. Koenigsberger and J. Tlusty, “Machine Tool Structures,” Vol. 1, Pergamon Press, 1968.Google Scholar
  4. [4]
    T. R. Comstock, F. S. Tse, and J. R. Lemon, “Application of controlled mechanical impedance for reducing machine tool vibration,” J. Eng. Industry, Trans. ASME, Series B, Vol. 91, 1969.Google Scholar
  5. [5]
    C. L. Nachitigal and N. H. Cook, “Active control of machine tool chatter,” J. Basic Eng., Trans. ASME, Series D, Vol. 92, No. 2, pp. 238–244, June 1970.CrossRefGoogle Scholar
  6. [6]
    E. E. Metchell, “Design of a hardware observer for active machine tool control,” J. Dynamic System, Measurement, and Control, Trans. ASME, Series G, Vol. 99, No. 4, 1977.Google Scholar
  7. [7]
    F. A. Barney, S. M. Pandit, and S. M. Wu, “A new approach to the analysis of machine tool system stability under working conditions,” J. Eng. Industry, Trans. ASME, Series B, Vol. 99, No. 3, pp. 585–590, August 1977.CrossRefGoogle Scholar
  8. [8]
    F. A. Barney, S. M. Pandit, and S. M. Wu, “A stochastic approach to characterization of machine tool system dynamics under actual working conditions,” J. Eng. Industry, Trans. ASME, Series B, Vol. 98, No. 4, pp. 614–619, November 1976.CrossRefGoogle Scholar
  9. [9]
    T. L. Subramanian, M. F. DeVries, and S. M. Wu, “An investigation of computer control of machining chatter,” J. Eng. Industry, Trans. ASME, Series B, Vol. 98, No. 4, pp. 1209–1214, 1976.CrossRefGoogle Scholar
  10. [10]
    K. F. Eman and S. M. Wu, “A feasibility study of on-line identification of chatter in turning operations,” J. Eng. Industry, Trans. Vol. 102, 1980.Google Scholar
  11. [11]
    K. F. Eman, “Machine tool system identification and forecasting control of chatter,” Ph.D. Thesis, University of Wisconsin-Madison, 1979.Google Scholar
  12. [12]
    S. Y. Tsai, K. F. Eman, and S. M. Wu, “Chatter suppression in turning,” Eleventh NAMRC Proceedings, May 1983.Google Scholar
  13. [13]
    S. Y. Tsai, “On-line identification and control of machining chatter in turning through dynamic data system methodology,” Ph.D. Thesis, University of Wisconsin-Madison, August 1983.Google Scholar
  14. [14]
    S. M. Wu, “Dynamic data system: A, new modeling approach,” J. Eng. Industry, Trans. ASME, Series B, Vol. 99, No. 3, pp. 708–714, August 1977.CrossRefGoogle Scholar
  15. [15]
    S. M. Pandit and S. M. Wu, “Time Series and System Analysis with Application,” Wiley, 1983.Google Scholar
  16. [16]
    W. Q. Yang, S. H. Hsieh, and S. M. Wu, “Adaptive modeling and characterization for control of chatter,” 103rd Winter Annual Meeting, ASME, Nov. 14–19, 1982.Google Scholar
  17. [17]
    A. A. Serig, “Optimum design of mechanical elements and system,” Course Handouts, University of Wisconsin-Madison, 1984.Google Scholar
  18. [18]
    J. Tlusty, “Measurement of the dynamic cutting force coefficient,” NAMRC Conference, 1974.Google Scholar
  19. [19]
    M. M. Nigm and M. M. Sadek, “Experimental investigation of the characteristic of dynamic cutting process,” J. Eng. Industry, ASME, 1977.Google Scholar
  20. [20]
    J. Peters and P. Vanherck, “Machine tool stability test and the incremental stiffness,” Annals of CIRP, Vol. XVII, pp. 225–232, 1969.Google Scholar

Copyright information

© Plenum Press, New York 1985

Authors and Affiliations

  • Shing-Yuan Tsai
    • 1
    • 2
  • Shien-Ming Wu
    • 1
    • 2
  1. 1.MIRL, ITRITaiwan, R.O.C.
  2. 2.University of WisconsinMadisonUSA

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