Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/16287
Title: PREDICTING CUTTING PARAMETERS BY APPLYING DEVELOPED NEURAL NETWORK AND LINEAR REGRESSION MODELS
Authors: Djordjevic, Aleksandar
Erić, Milan
Stefanovic, Miladin
Mitrovic, Slobodan
Pantić, Marko
Kokić Arsić A.
Dzunic, Dragan
Issue Date: 2019
Abstract: The paper presents the methods for prediction of the cutting parameters. In order to test the workability of the material by process of scraping, from the aspect of the cutting temperature, an natural thermopar was placed just below the cutting edge of the plate. In this way, a simple, reliable, accurate and economical method for determining the workability of material by cutting is obtained. The feasibility study of several semi-finished products by applying the realized experiments was carried out. Different materials in processing with cutting discs with different coatings give different results, which are used to form neural network and linear regression models.
URI: https://scidar.kg.ac.rs/handle/123456789/16287
Type: article
DOI: 10.24874/PES01.01.064
ISSN: 2620-2832
SCOPUS: 2-s2.0-85098125164
Appears in Collections:Faculty of Engineering, Kragujevac

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