• DocumentCode
    2615171
  • Title

    A neural network-based model for the prediction of cutting force in milling process. A progress study on a real case

  • Author

    Alique, Angel ; Haber, Rodolfo E. ; Haber, Rodolfo H. ; Ros, Salvador ; Gonzalez, Carlos

  • Author_Institution
    Inst. de Automatica Ind., CSIC, Madrid, Spain
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    121
  • Lastpage
    125
  • Abstract
    In spite of recent developments focusing on milling process optimization through an effective cutting force control, there is a need for the analysis of the transient response of these systems because undesirable oscillations in cutting force can be harmful to the quality of the finishing surface and tools. The main goal of this work is to develop a versatile neural network model which can online predict the mean cutting force under commonly encountered conditions. Using this model, easily obtained from a straightforward machining test, developments of complex adaptive controllers and monitoring systems can be carried out. As a result, a good model for predicting the cutting process was obtained
  • Keywords
    adaptive control; condition monitoring; cutting; force control; machining; multilayer perceptrons; neurocontrollers; optimisation; predictive control; transient response; adaptive control; cutting force; force control; machining; milling; monitoring; multilayer perceptron; neural network; process optimization; transient response; Force control; Machining; Milling; Neural networks; Predictive models; Programmable control; Surface finishing; System testing; Transient analysis; Transient response;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control, 2000. Proceedings of the 2000 IEEE International Symposium on
  • Conference_Location
    Rio Patras
  • ISSN
    2158-9860
  • Print_ISBN
    0-7803-6491-0
  • Type

    conf

  • DOI
    10.1109/ISIC.2000.882910
  • Filename
    882910