ARTIFICIAL NEURAL NETWORK MODELLING OF CUTTING FORCE COMPONENTS DURING AZ91HP ALLOY MILLING

ARTIFICIAL NEURAL NETWORK MODELLING OF CUTTING FORCE COMPONENTS DURING AZ91HP ALLOY MILLING

The paper presents simulation of the cutting force components for machining of magnesium alloy AZ91HP. The simulation employs the Black Box model. The closest match to (input and output) data obtained from the machining process was determined. The simulation was performed with the use of the Statist...

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Bibliographic Details
Main Authors: Monika KULISZ, Ireneusz ZAGÓRSKI, Aleksandra SEMENIUK
Format: Article
Language:English
Published: Polish Association for Knowledge Promotion 2016-12-01
Series:Applied Computer Science
Subjects:
The paper presents simulation of the cutting force components for machining of magnesium alloy AZ91HP. The simulation employs the Black Box model. The closest match to (input and output) data obtained from the machining process was determined. The simulation was performed with the use of the Statistica programme with the application of neural networks: RBF (Radial Basis Function) and MLP (Multi-Layered Perceptron).
simulation
cutting force
artificial neural networks
magnesium alloys
Online Access:http://acs.pollub.pl/pdf/v12n4/4.pdf
Description
Summary:The paper presents simulation of the cutting force components for machining of magnesium alloy AZ91HP. The simulation employs the Black Box model. The closest match to (input and output) data obtained from the machining process was determined. The simulation was performed with the use of the Statistica programme with the application of neural networks: RBF (Radial Basis Function) and MLP (Multi-Layered Perceptron).
ISSN:1895-3735
2353-6977

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