Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/8310
Title: Comparative characteristics of ductile iron and austempered ductile iron modeled by neural network
Authors: Savković B.
Kovac P.
Dudic B.
Greguš M.
Rodic D.
Strbac, Branko
Dučić, Nedeljko
Issue Date: 2019
Abstract: © 2019 by the authors. Experimental research of cutting force components during dry face milling operations are presented in the paper. The study was provided when milling of ductile cast iron alloyed with copper and its austempered ductile iron after the proper austempering process. In the study, virtual instrumentation designed for cutting forces components monitoring was used. During the research, orthogonal cutting forces components versus time were monitored and relationship of cutting forces components versus speed, feed and depth of cut were determined by artificial neural network and response surface methodology. An analysis was made regarding the consistency of the measured cutting forces and the values obtained from the model supported by an artificial neural network for the investigated interval of the cutting regime. Based on the results, an analysis of the feasibility of the application of austempered ductile iron in the industrial sector with the aspect of machinability as well as the application of the models based on artificial intelligence, was given. At the end of the presentation, the influence of the aforementioned cutting regimes on cutting force components is presented as well.
URI: https://scidar.kg.ac.rs/handle/123456789/8310
Type: article
DOI: 10.3390/ma12182864
SCOPUS: 2-s2.0-85072563362
Appears in Collections:Faculty of Technical Sciences, Čačak

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