Journal of Harmonized Research in Engineering

PREDICTION OF MILLING MACHINE PARAMETER TO FORECASTE OUTPUT QUANTITY BY NEURAL NETWORK METHOD

Abstract

Author(s): Amit K. Pandey, Manish Verma, Ashish Kumar Khandelwal, S P Shrivas

The aim of this thesis is to discover the role of these parameters is to prediction in milling operations by using artificial neural networks and Taguchi design of experiment.The study was conducted by using milling machine with fine type carbide tool with twin cutting edge.Experimental data collected from tests were used as input parameters of a neural network to identify the sensitivity among machining operations, MRR and surface roughness. The experimental data is later used to predictoutput data by using artificial neural network. Neural network algorithms are developed for use as a direct modeling method, to predict MRR and surface roughness for end milling operations.