Please use this identifier to cite or link to this item:
Title: Forward and reverse mapping for milling process using artificial neural networks
Authors: Malghan R.L.
M C K.R.
Shettigar A.K.
Rao S.S.
D'Souza R.J.
Issue Date: 2018
Citation: Data in Brief, 2018, Vol.16, , pp.114-121
Abstract: The data set presented is related to the milling process of AA6061-4.5%Cu-5%SiCp composite. The data primarily concentrates on predicting values of some machining responses, such as cutting force, surface finish and power utilization utilizing using forward back propagation neural network based approach, i.e. ANN based on three process parameters, such as spindle speed, feed rate and depth of cut.The comparing reverse model is likewise created to prescribe the ideal settings of processing parameters for accomplishing the desired responses as indicated by the necessities of the end clients. These modelling approaches are very proficient to foresee the benefits of machining responses and also process parameter settings in light of the experimental technique. © 2017 The Authors
URI: 10.1016/j.dib.2017.10.069
Appears in Collections:5. Miscellaneous Publications

Files in This Item:
There are no files associated with this item.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.