WEAR PERFORMANCE ANALYSIS OF NYLON-6/BORON NITRIDE POLYMER COMPOSITES USING TAGUCHI-PARETO AND TAGUCHI-ABC METHODS

Authors

  • Abdulganiyu A. Adekoya Department of Mechanical Engineering, University of Lagos, Lagos, Nigeria
  • Sunday A. Oke Department of Mechanical Engineering, University of Lagos, Lagos, Nigeria https://orcid.org/0000-0002-0914-8146
  • Wasiu O. Adedeji Department of Mechanical Engineering, Osun State University, Osogbo, Nigeria https://orcid.org/0000-0002-0914-8146

DOI:

https://doi.org/10.30572/2018/KJE/140102

Keywords:

Nylon 6, boron nitride, composites, optimisation, prioritisation

Abstract

Despite the industrial popularity of nylon 6 composites, their wear performance portrays a substantial knowledge gap on parametric importance. Consequently, this study optimizes and prioritizes the wear performance parameters of nylon 6/boron nitride composites using the Taguchi-Pareto and Taguchi-ABC methods based on 80-20 Pareto rule and the ABC analysis, using signal-to-noise ratios. From the literature information, the principal parameters considered are the %wt of reinforcement, normal load, sliding speed, and sliding distance, respectively. The results showed that the optimal parametric setting using the Taguchi-Pareto method is 4wt % of boron nitride Nanocomposite, 15 N of normal load, 100 rpm of sliding speed and 500m of sliding distance. The limitation of this study is the difficulty in deducing the most significant delta values or ranks through the parameters. This work drive towards more practically focused wear performance studies by industrial practitioners, showing critical optimization and prioritization procedures in a single study.

Downloads

Download data is not yet available.

Downloads

Published

2023-02-08

How to Cite

Adekoya, Abdulganiyu A., et al. “WEAR PERFORMANCE ANALYSIS OF NYLON-6 BORON NITRIDE POLYMER COMPOSITES USING TAGUCHI-PARETO AND TAGUCHI-ABC METHODS”. Kufa Journal of Engineering, vol. 14, no. 1, Feb. 2023, pp. 13-32, doi:10.30572/2018/KJE/140102.

Similar Articles

1 2 > >> 

You may also start an advanced similarity search for this article.