Computer-aided hybrid ANN-GA approach for modelling and optimisation of EDDG process
by Ashish Srivastava; Avanish Kumar Dubey; Pankaj Kumar Shrivastava
International Journal of Abrasive Technology (IJAT), Vol. 5, No. 3, 2012

Abstract: Artificial intelligence techniques have proven to be the better tool for modelling and optimisation of processes having complex nature and non-linear behaviour. It has been found that the hybrid approach of two individual tools may even perform more efficiently. The present paper proposes a computer aided hybrid approach of neural network and genetic algorithm for modelling and optimisation of different quality characteristics in a manufacturing process. The results of the developed software computer-aided-hybrid-neural-GA (CAHNG) has been compared with that of published literature and found suitable. Further, this software has been applied for modelling and optimisation of material removal rate and average temperature in electric discharge diamond grinding of high speed steel. The results show the considerable improvements in both the characteristics.

Online publication date: Wed, 30-Jul-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