Two approaches to multi-criteria optimisation of steel alloys for crankshafts production
by Petia Koprinkova-Hristova; Nikolay Tontchev; Silviya Popova
International Journal of Reasoning-based Intelligent Systems (IJRIS), Vol. 5, No. 2, 2013

Abstract: The paper presents the application of multi-criteria optimisation to steel alloy composition determination aimed at obtaining improved properties material for crankshafts production. Neural network model of steel mechanical characteristics in dependence on amounts of its alloying elements was used for simulation purpose. Two optimisation approaches were applied to find optimal alloys composition. In the first one, several Pareto optimal solutions were found based on those obtained by simulation numerous compositions in the investigated region of interest. The second one used Taguchi method for robust design. The obtained optimal solutions were compared and decision about further production experiments was taken.

Online publication date: Tue, 22-Oct-2013

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 Reasoning-based Intelligent Systems (IJRIS):
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