An investigation of modeling of the machining database in turning operations

Abstract Modeling of the machining database in turning operations has been investigated in this paper. The machining database is constructed based on polynomial networks. The polynomial networks can learn the relationships between cutting parameters (cutting speed, feed rate, and depth of cut) and cutting performance (tool life, surface roughness, and cutting force) through a self-organizing adaptive modeling technique. Experimental results have been shown that the machining database in turning operations can be modeled well through this approach.

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