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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Reasoning-based Intelligent Systems
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
