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Title:Tool cutting force modeling in ball-end milling using multilevel perceptron
Authors:ID Župerl, Uroš (Author)
ID Čuš, Franc (Author)
Files:URL http://dx.doi.org/10.1016/j.jmatprotec.2004.04.309
 
Language:English
Work type:Unknown
Typology:1.01 - Original Scientific Article
Organization:FS - Faculty of Mechanical Engineering
Abstract:This paper uses the artificial neural networks (ANNs) approach to evolve an efficient model for estimation of cutting forces, based on a set of input cutting conditions. A neural network algorithms are developed for use as a direct modeling method, to predict forces for ball-end milling operation. Supervised neural networks are used to successfully estimate the cutting forces developed during end milling process. The training of the networks is preformed with experimental machining data. The predictive capability of using analytical and neural network approaches are compared using statistics, which showed that neural network predictions for three cutting force components were for 4% closer to the experimental measurements, compared to 11% using analytical method. Exhaustive experimentation is conduced to develop the model and to validate it. The milling experiments prove that this model can predict accurately the cutting forces in three Cartesian directions.The force model can be used for simulation purposes and for defining threshold values in cutting tool condition monitoring system.
Keywords:ball end milling, cutting forces, modelling, artificial intelligence, neural networks
Year of publishing:2004
PID:20.500.12556/DKUM-27514 New window
UDC:621.914:004.89
ISSN on article:0924-0136
COBISS.SI-ID:8791062 New window
NUK URN:URN:SI:UM:DK:YJ0GFDEG
Publication date in DKUM:01.06.2012
Views:2527
Downloads:119
Metadata:XML DC-XML DC-RDF
Categories:Misc.
:
ŽUPERL, Uroš and ČUŠ, Franc, 2004, Tool cutting force modeling in ball-end milling using multilevel perceptron. Journal of materials processing technology [online]. 2004. [Accessed 21 January 2025]. Retrieved from: http://dx.doi.org/10.1016/j.jmatprotec.2004.04.309
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Record is a part of a journal

Title:Journal of materials processing technology
Shortened title:J. mater. process. technol.
Publisher:Elsevier
ISSN:0924-0136
COBISS.SI-ID:30105600 New window

Secondary language

Language:English
Keywords:čelno frezanje, krogelno oblikovno frezalo, rezalne sile, modeliranje, nevronske mreže, umetna inteligenca


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