Journal
JOURNAL OF MATERIALS PROCESSING TECHNOLOGY
Volume 190, Issue 1-3, Pages 305-311Publisher
ELSEVIER SCIENCE SA
DOI: 10.1016/j.jmatprotec.2007.02.031
Keywords
neural networks; response surface methodology; machinability models
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In this paper, empirical models for tool life, surface roughness and cutting force are developed for turning operations. Process parameters (cutting speed, feed rate, depth of cut and tool nose radius) are used as inputs to the developed machinability models. Two important data mining techniques are used; they are response surface methodology and neural networks. Data of 28 experiments when turning austenitic AISI 302 have been used to generate, compare and evaluate the proposed models of tool life, cutting force and surface roughness for the considered material. (c) 2007 Elsevier B.V. All rights reserved.
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