Tools
Tools
Ghalme, S., Mankar, A. and Bhalerao, Y.J. 
ORCID: https://orcid.org/0000-0002-0743-8633
(2017)
Wear performance optimization of silicon nitride using genetic and simulated annealing algorithm.
Journal of Engineering Science and Technology Review, 12 (12).
pp. 3120-3135.
ISSN 1791-9320
Preview |
PDF (Published_Version)
- Published Version
Available under License Other licence. Download (1MB) | Preview |
Abstract
Replacing damaged joint with the suitable alternative material is a prime requirement in a patient who has arthritis. Generation of wear particles in the artificial joint during action or movement is a serious issue and leads to aseptic loosening of joint. Research in the field of bio-tribology is trying to evaluate materials with minimum wear volume loss so as to extend joint life. Silicon nitride (Si3N4) is non-oxide ceramic suggested as a new alternative for hip/knee joint replacement. Hexagonal Boron Nitride (hBN) is recommended as a solid additive lubricant to improve the wear performance of Si3N4. In this paper, an attempt has been made to evaluate the optimum combination of load and % volume of hBN in Si3N4 to minimize wear volume loss (WVL). The experiments were conducted according to Design of Experiments (DoE)–Taguchi method and a mathematical model is developed. Further, this model is processed with Genetic Algorithm (GA) and Simulated Annealing (SA) to find out the optimum percentage of hBN in Si3N4 to minimize wear volume loss against Alumina (Al2O3) counterface. Taguchi method presents 15 N load and 8% volume of hBN to minimize WVL of Si3N4. While GA and SA optimization offer 11.08 N load, 12.115% volume of hBN and 11.0789 N load, 12.128% volume of hBN respectively to minimize WVL in Si3N4.
| Item Type: | Article |
|---|---|
| Faculty \ School: | Faculty of Science > School of Engineering (former - to 2024) |
| UEA Research Groups: | Faculty of Science > Research Groups > Materials, Manufacturing & Process Modelling |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 14 Jan 2020 04:59 |
| Last Modified: | 07 Nov 2024 12:41 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/73610 |
| DOI: |
Downloads
Downloads per month over past year
Actions (login required)
 |
View Item |