Investigation of process parameters effect on wood-bioplastic nanocomposites behavior using Taguchi method

• Published in: Polymer bulletin (Berlin, Germany) Vol. 80; no. 3; pp. 2959 - 2984
• Main Authors: Karami, S., Khamedi, R., Azizi, H.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2023; Springer Nature B.V
• Subjects: Bioplastics; Characterization and Evaluation of Materials; Chemistry; Chemistry and Materials Science; Complex Fluids and Microfluidics; Composite materials; Data analysis; Environmental impact; Fossil fuels; Graphene; Impact strength; Lignocellulose; Maleic anhydride; Mathematical models; Mechanical properties; Nanocomposites; Nanoparticles; Optimization; Organic Chemistry; Original Paper; Phase composition; Physical Chemistry; Polylactic acid; Polymer Sciences; Polymers; Process parameters; Scanning electron microscopy; Signal to noise ratio; Soft and Granular Matter; Software; Statistical analysis; Taguchi methods; Tensile strength; Tensile tests; Titanium dioxide; Variance analysis; Wood-bioplastic nanocomposite; Digimat software; Optimization; Tensile strength; Taguchi method
• ISSN: 0170-0839; 1436-2449
• DOI: 10.1007/s00289-022-04177-3

This article presents the results of a study on the effect of process parameters on predicting the mechanical properties of wood bioplastic nanocomposites. The primary purpose was to obtain the optimal values of the representative volume element (RVE) parameters to predict the mechanical behavior of the wood-plastic composite accurately. For each sample, a specific combination of the RVE parameters was defined in the Digimat simulation software, and the corresponding mechanical properties was obtained. A tensile test were performed on composite specimens according to the ASTM D638 standard. The results from the Digimat software were compared with the experimental results. This model was eventually applied to Taguchi’s optimization analysis to achieve an optimal set of RVE parameters that minimize the discrepancy between the predicted and experimental models. This study aimed to use Taguchi statistical analysis considering a test design for a signal-to-noise ratio (S/N) and perform a data analysis using Minitab software. The input parameters of these compounds play an important role in determining their quality and strength. In this article, different weight percentages of these compounds were simulated and optimized using the Taguchi method. The study input variables were weight percentages of wood flour, polylactic acid, corn starch, maleic anhydride, and two types of nanoparticles TiO 2 and graphene. The Taguchi method optimized the process parameters in the target direction by obtaining experimental results to correlate the input and output parameters. In this article, optimization objectives include increasing tensile strength. The microstructure and phase composition of the produced materials was examined with scanning electron microscope (SEM), and x-ray energy-dispersive spectroscopy (EDS). SEM images and EDS analysis showed the excellent performance of the proposed techniques in the optimization of mechanical properties.