Loading…

Multi-objective optimization of alloying elements to enhance the wear resistance and impact strength of HCCI produced by furan sand mold

High Chromium White Cast Iron (HCWCI) plays a major role in manufacturing of wear-resistant components. Due to unique wear resistance property, attribution to the additions of carbide forming elements, they have been used for mill liner applications. By varying the wt% of alloying elements such as C...

Full description

Saved in:
Bibliographic Details
Published in:Proceedings of the Institution of Mechanical Engineers. Part E, Journal of process mechanical engineering Journal of process mechanical engineering, 2022-08, Vol.236 (4), p.1566-1580
Main Authors: Dhayaneethi, S, Anburaj, J, Arivazhagan, S
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:High Chromium White Cast Iron (HCWCI) plays a major role in manufacturing of wear-resistant components. Due to unique wear resistance property, attribution to the additions of carbide forming elements, they have been used for mill liner applications. By varying the wt% of alloying elements such as Cr, Ti, and Mo, the wear resistance and impact strength of High Chromium Cast Iron (HCCI) can be increased. To enhance the wear resistance property according to Central Composite Design (CCD), 16 samples were fabricated by varying the wt% of alloying elements. To fabricate the samples, furan sand molds were prepared and used for the further casting process. The properties of Furan sand mold enhance the mechanical properties and reduce the mold rejection rate, production time, etc. To attain the optimum Wear Rate (WR) and Impact Strength (IS) value without dominance, optimization techniques such as Response Surface Methodological (RSM) and Particle swarm optimization (PSO) are employed to solve the multi-objective problem. The RSM and PSO predicted optimum solutions are compared by using the Weighted Aggregated Sum Product Assessment (WASPAS) ranking method. The WASPAS result revealed that when compared to the RSM result, the PSO predicted optimal wt% of chemical composition (22 wt % Cr, 3 wt % Ti, and 2.99 wt % Mo) gives the optimum WR value (53 mm3/min) and IS value (3.77 J). To validate the PSO result, experiments were carried out for the predicted wt% of alloying elements and tested. The difference between the PSO predicted result and experimental result is less than 5% error which clearly shows that PSO is an effective method to solve the multi-objective problem.
ISSN:0954-4089
2041-3009
DOI:10.1177/09544089211069212