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. Huwei Inst. of Technol., Yunlin, Taiwan
Abstract :
This 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 criterion. Once the drill diameter, cutting speed and feedrate are given, 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 10%
Keywords :
cutting; inference mechanisms; machine tools; machining; abductive network; cutting conditions; cutting speed; drill diameter; drill tool life prediction; drilling; feedrate; functional nodes; optimal network architecture; predicted squared error criterion; prediction error; Cutting tools; Drilling; Industrial control; Intelligent networks; Neural networks; Performance analysis; Polynomials; Predictive models; Process planning; Temperature;
Journal_Title :
Industry Applications, IEEE Transactions on
