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
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;
Conference_Titel :
Industrial Automation and Control: Emerging Technologies, 1995., International IEEE/IAS Conference on
Conference_Location :
Taipei
Print_ISBN :
0-7803-2645-8
DOI :
10.1109/IACET.1995.527647
