The influence of reinforcement, alkali treatment, compression pressure and temperature in fabrication of sisal/coir/epoxy composites: GRA and ANN prediction


In this study, sisal and coir fiber-based epoxy composites were fabricated using compression molding route. Optimization technique using Taguchi and grey relational analysis (GRA) was employed to find the best condition for tensile, flexural and impact properties. Sisal (0–20 wt%), coir fibers (0–20 wt%), NaOH treatment (0–8 wt%), compression pressure (10–16 MPa) and temperature (100–120 °C) are the different factors with various levels. Multi-response optimization using GRA showed significance of both the fibers in enhancing mechanical properties. The response table of GRA concluded that combination of sisal 20%/coir 15%/NaOH treatment 5%/compression pressure 10 MPa and temperature 120 °C has the best mechanical results. SEM images indicated the advancement in adhesion of reinforcement and epoxy resin by hybridization of fibers. The artificial neural network (ANN) prediction states predicted and experimental values for various trials are almost same, and regression graph showed a straight line with R-value 97.321%. These fabricated composites can be used in aerospace and automobile industries for their interior parts.

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The authors are thankful to the Department of Nano Science and Technology, Bharathiar University, Coimbatore, for the support in conducting ‘contact angle’ test. There is no funding for this project.

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Correspondence to K. R. Sumesh.

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Sumesh, K.R., Kanthavel, K. The influence of reinforcement, alkali treatment, compression pressure and temperature in fabrication of sisal/coir/epoxy composites: GRA and ANN prediction. Polym. Bull. 77, 4609–4629 (2020).

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  • Natural fibers
  • Particle reinforcement
  • Optimization
  • Mechanical properties
  • Artificial neural network (ANN) technique