Application of Taguchi and grey-fuzzy model to optimise the machining parameters of nanocrystalline structured chips production in high carbon steel
by M. Ilangkumaran; R. Sasikumar; G. Sakthivel
International Journal of Fuzzy Computation and Modelling (IJFCM), Vol. 1, No. 4, 2015

Abstract: Nanocrystalline materials is an area of interest for researchers all over the world due to its superior mechanical properties, however the production cost of nano crystals are higher due to the complexity and cost involved during its production. This paper focuses on the application of Taguchi method with grey-fuzzy model for optimising the machining parameters of nano-crystalline structured chips production in high carbon steel (HCS) through machining. To continuously improve the machining parameters capability Taguchi-based methodologies are proposed under the consideration of multiple responses performance characteristics. An orthogonal array, multi-response performance index, signals to noise ratio, grey fuzzy grade (GFG) and analysis of variance (ANOVA) are used to study the machining process with multi-response performance characteristics. The machining parameters namely rake angle, depth of cut, heat treatment, feed and cutting velocity are optimised with considerations of the multi-response performance characteristics. Using the Taguchi and grey fuzzy method optimum cutting conditions are identified in order to obtain the smallest nanocrystalline structure via machining. Optimising a multi-response problem by the Taguchi method involves the engineer's judgement which tends to increase the degree of uncertainty.

Online publication date: Sat, 30-Apr-2016

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 Fuzzy Computation and Modelling (IJFCM):
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