PARAMETRIC RATIO OPTIMIZATION AND STATISTICAL MODELLLNG OF WEAR PERFORMANCE IN DUAL-FILLER PARTICLE REINFORCED EPOXY COMPOSITES

Authors

  • Oluwaseyi A. Ajibade Department of Metallurgical and Materials Engineering, University of Lagos, Lagos, Nigeria
  • Johnson O. Agunsoye Department of Metallurgical and Materials Engineering, University of Lagos, Lagos, Nigeria
  • Sunday A. Oke Department of Mechanical Engineering, University of Lagos, Lagos, Nigeria

DOI:

https://doi.org/10.30572/2018/KJE/100111

Keywords:

Epoxy composites, wear, Taguchi, ANOVA, regression

Abstract

Despite the potentials of dual reinforced particulate polymer composites to produce outstanding composite with enhanced wear properties, scholars have devoted insignificant attention to them. This paper introduces five diverse epoxy composites prepared in dual reinforcement blends. Using a mixed design L16 orthogonal array, Taguchi’s parametric optimization was conducted with some ratios between the wear parameters as a novel way of revealing the influence of their interrelatedness in the optimization process while the statistical modelling of the wear responses was pursued. Analysis of variance was also conducted as well as regression analysis. With experimental tests on the DIN abrasion tester, the (10OPP,15CSP)% composite obtained an optimal parametric setting of A1B2-3C3D1E4. The (10PKSP,15CSP), (10PSp,15ESP), (10OPP,15PSP) and (5PKSP,20ESP)% composites obtained optimal parameter settings of A3B2C3D3E2, A3B1-3,C3D1E4, A3B2C2D1E4 and A3B2C4D3E3, respectively. The correlation plots between the experimental and predicted values of the wear process and determination coefficient indicate a high level of accuracy of the models in predicting the wear behaviour of the composites.

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Published

2021-06-06

How to Cite

Ajibade, Oluwaseyi, et al. “PARAMETRIC RATIO OPTIMIZATION AND STATISTICAL MODELLLNG OF WEAR PERFORMANCE IN DUAL-FILLER PARTICLE REINFORCED EPOXY COMPOSITES”. Kufa Journal of Engineering, vol. 10, no. 1, June 2021, pp. 140-59, doi:10.30572/2018/KJE/100111.

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