Development of an Intelligent System for Tool Materials Selection in High Speed Machining


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Tool materials play one of the pivotal roles in the machining system. Tool materials must be carefully chosen in relation to the workpiece material to be machined, the tool life, the metal removal rate, the machining cost, and the required accuracy and finish. The advantages and decision-making processes of case-based reasoning (CBR) are described. The CBR system for tool material selection in high speed machining (HSM) is developed. The case expression and organization, searching, matching and constraint-based adaptation rules are presented. With combining the case-based reasoning strategy and constraint-based adaptation, the tool material can be properly selected on the basis of previously successful tool materials used in HSM operations, which is helpful to push the wide applications of HSM.



Materials Science Forum (Volumes 471-472)

Edited by:

Xing Ai, Jianfeng Li and Chuanzhen Huang




Z. Q. Liu et al., "Development of an Intelligent System for Tool Materials Selection in High Speed Machining", Materials Science Forum, Vols. 471-472, pp. 82-86, 2004

Online since:

December 2004




[1] L. Wittgenstein: Philosophical Investigations (Oxford: Basil Blackwell, 1968).

[2] R. Schank: Dynamic Memory: A Theory of Learning in Computers and People (New York: Cambridge University Press, 1982).

[3] J.G. Carbonell, R.S. Michalski and T.M. Mitchell (eds. ): Machine Learning Vol. 2 (1986), p.371.

[4] A. Aamodat and E. Plaza: AI Communications Vol. 7 (1994), p.39.

[5] R.I. King: High Speed Machining Technology (Chapman and Hall, New York 1985).

[6] S. Ashley: Mechanical Engineering Vol. 112 (1995), p.56.