• DocumentCode
    1608181
  • Title

    An abductive network for predicting tool life in drilling

  • Author

    Lee, B.Y. ; Liu, H.S. ; Tarng, Y.S.

  • Author_Institution
    Dept. of Mech. Manuf. Eng., Nat. Yunlin Polytech. Inst., Taiwan
  • fYear
    1995
  • Firstpage
    717
  • Lastpage
    722
  • Abstract
    The paper presents an abductive network for predicting tool life in drilling operations. The abductive network is composed of a number of functional nodes. These functional nodes are well organized to form an optimal network architecture by using a predicted squared error (PSE) criterion. Once the drill diameter, cutting speed, and feedrate are given, the tool life can be predicted based on the developed network. Experimental results have shown that the abductive network can be effectively used to predict drill life under varying cutting conditions and the prediction error of drill life is less than 9%
  • Keywords
    inference mechanisms; machine tools; machining; monitoring; neural nets; prediction theory; process control; uncertainty handling; abductive network; abductive reasoning; cutting speed; drilling; feedrate; functional nodes; predicted squared error; tool life prediction; uncertainty handling; Databases; Drilling; Equations; Intelligent networks; Machine intelligence; Network synthesis; Polynomials; Transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Automation and Control: Emerging Technologies, 1995., International IEEE/IAS Conference on
  • Conference_Location
    Taipei
  • Print_ISBN
    0-7803-2645-8
  • Type

    conf

  • DOI
    10.1109/IACET.1995.527647
  • Filename
    527647