Neural network modelling and multi objective optimisation of electrical discharge diamond cut-off grinding (EDDCG)
by Sanjeev Kumar Singh Yadav; Vinod Yadava
International Journal of Abrasive Technology (IJAT), Vol. 4, No. 4, 2011

Abstract: This paper presents the development of neural network model and parameter optimisation of electrical discharge diamond cut-off grinding (EDDCG) during machining of cemented carbides for material removal rate (MRR) and average surface roughness (Ra). The experiments were carried out on a self developed electrical discharge diamond cut-off grinding (EDDCG) attachment on conventional EDM machine. The numbers of experiments were selected based on full factorial design of experimental procedure. After experimentation the data set were divided into a training set and testing set for ANN modelling. The ANN back propagation algorithm with four inputs (current, pulse on-time, duty factor, wheel RPM) two outputs (MRR, Ra) and one hidden layer with 15 neurons is proposed to establish the process model. The model after proper training was found to be capable of predicting the response parameters. The predicted results from ANN model are discussed to get the insight of the process. Further, multi-objective optimisation of EDDCG is done using GRA coupled with entropy measurement method.

Online publication date: Tue, 30-Sep-2014

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Abrasive Technology (IJAT):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com