Forward and reverse mapping for milling process using artificial neural networks

Rashmi L. Malghan, Karthik Rao M C, Arun Kumar Shettigar, Shrikantha S. Rao, R. J. D'Souza

Research output: Contribution to journalArticle

2 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)114-121
Number of pages8
JournalData in Brief
Volume16
DOIs
Publication statusPublished - 01-02-2018

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Malghan, R. L., M C, K. R., Shettigar, A. K., Rao, S. S., & D'Souza, R. J. (2018). Forward and reverse mapping for milling process using artificial neural networks. Data in Brief, 16, 114-121. https://doi.org/10.1016/j.dib.2017.10.069