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Development of an artificial neural network algorithm for predicting the surface roughness in end milling of inconel 718 alloy

Hossain, Mohammad Ishtiyaq and Amin, A. K. M. Nurul and Patwari, Anayet Ullah (2008) Development of an artificial neural network algorithm for predicting the surface roughness in end milling of inconel 718 alloy. In: International Conference on Computer and Communication Engineering 2008, 13-15 May 2008, Kuala Lumpur.

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In this work, an artificial neural network (ANN) model was developed for the investigation and prediction of the relationship between cutting parameters and surface roughness during high speed end milling of nickel-based Inconel 718 alloy. The input parameters of the ANN model are the cutting parameters: cutting speed, feed, and axial depth of cut. The output parameter of the model was surface roughness. For this interpretation, advantages of statistical experimental design technique, experimental measurements, artificial neural network were exploited in an integrated manner. Cutting experiments are designed based on statistical three-level full factorial experimental design technique. A predictive model for surface roughness was created using a feed-forward back-propagation neural network exploiting experimental data. The network was trained with pairs of inputs/outputs datasets generated when end milling Inconel 718 alloy with single-layer PVD TiAlN coated carbide inserts. A very good predicting performance of the neural network, in terms of concurrence with experimental data was attained. The model can be used for the analysis and prediction for the complex relationship between cutting conditions and the surface roughness in metal-cutting operations and for the optimization of the surface roughness for efficient and economic production.

Item Type: Conference or Workshop Item (Full Paper)
Additional Information: 2872/16512
Subjects: T Technology > TJ Mechanical engineering and machinery
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering > Department of Manufacturing and Materials Engineering
Depositing User: Dr. A.K.M. Nurul Amin
Date Deposited: 10 Apr 2012 14:30
Last Modified: 19 Sep 2012 16:15
URI: http://irep.iium.edu.my/id/eprint/16512

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