Optimization of magnetic field assisted finishing process during nanofinishing of titanium alloy (grade-5) implant using soft computing approaches. (2nd November 2022)

• Record Type: Journal Article
• Authors: Barman, Anwesa; Das, Manas; Pathak, Vimal Kumar
• Is Part Of: International journal of modelling & simulation. Volume 42:Number 6(2022)
• Page Start: 920
• Page End: 935
• Publication Date: 2022-11-02
• Subjects: Nanofinishing -- femoral knee implant -- magnetic field assisted finishing process -- fuzzy logic -- improved salp swarm algorithm; Mathematical models -- Periodicals; Simulation methods -- Periodicals; Mathematical models; Simulation methods; Periodicals; 003.3
• DOI: 10.1080/02286203.2021.2001720
• Languages: English
• ISSNs: 0228-6203

Abstract

ABSTRACT: The present study explores the potential of magnetic field assisted finishing (MFAF) in precise finishing of femoral knee implant made of bio-titanium alloy at the nanometric level. The process parameters, viz. rotational speed of tool, feed rate and carbonyl iron particle (CIP) concentration of MFAF have significant influence on the final surface topography of implants and thus selection of optimal set of their values is a difficult but an important task. In the present work, central composite rotatable design of response surface methodology is considered for nanofinishing of titanium alloy based femoral knee implants. Based on the experimental results, a polynomial regression prediction model for surface roughness is established in terms of MFAF process parameters. The fuzzy logic model with the help of ANOVA analysis is employed to analyze the effect of individual and interaction of parameters on surface roughness of implants. Finally, for further optimizing the final surface roughness of knee implant and determining the best settings of MFAF parameters, an improved salp swarm algorithm (ISSA) is proposed by introducing two important enhancements in basic SSA. The results reveal that SSA and ISSA metaheuristics achieved an improvement in final surface finish of knee implant by 4.04% and 14.24%, respectively, in comparison to default experimental trials during finishing.