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Optimization of Injection Molding Parameters for HDPE/TiO₂ Nanocomposites Fabrication with Multiple Performance Characteristics Using the Taguchi Method and Grey Relational Analysis.

ABSTRACT: The current study presents an investigation on the optimization of injection molding parameters of HDPE/TiO₂ nanocomposites using grey relational analysis with the Taguchi method. Four control factors, including filler concentration (i.e., TiO₂), barrel temperature, residence time and holding time, were chosen at three different levels of each. Mechanical properties, such as yield strength, Young's modulus and elongation, were selected as the performance targets. Nine experimental runs were carried out based on the Taguchi L₉ orthogonal array, and the data were processed according to the grey relational steps. The optimal process parameters were found based on the average responses of the grey relational grades, and the ideal operating conditions were found to be a filler concentration of 5 wt % TiO₂, a barrel temperature of 225 °C, a residence time of 30 min and a holding time of 20 s. Moreover, analysis of variance (ANOVA) has also been applied to identify the most significant factor, and the percentage of TiO₂ nanoparticles was found to have the most significant effect on the properties of the HDPE/TiO₂ nanocomposites fabricated through the injection molding process.

SUBMITTER: Pervez H

PROVIDER: S-EPMC5512532 | biostudies-other | 2016 Aug

REPOSITORIES: biostudies-other

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Project description:Halloysite nanotubes-thermoplastic polyurethane (HNTs-TPU) nanocomposites are attractive products due to increasing demands for specialized materials. This study attempts to optimize the parameters for injection just before marketing. The study shows the importance of the preparation of the samples and how well these parameters play their roles in the injection. The control parameters for injection are carefully determined to examine the mechanical properties and the density of the HNTs-TPU nanocomposites. Three types of modified HNTs were used as untreated HNTs (uHNTs), sulfuric acid treated (aHNTs) and a combined treatment of polyvinyl alcohol (PVA)-sodium dodecyl sulfate (SDS)-malonic acid (MA) (treatment (mHNTs)). It was found that mHNTs have the most influential effect of producing HNTs-TPU nanocomposites with the best qualities. One possible reason for this extraordinary result is the effect of SDS as a disperser and MA as a crosslinker between HNTs and PVA. For the highest tensile strength, the control parameters are demonstrated at 150 °C (injection temperature), 8 bar (injection pressure), 30 °C (mold temperature), 8 min (injection time), 2 wt % (HNTs loading) and mHNT (HNTs type). Meanwhile, the optimized combination of the levels for all six control parameters that provide the highest Young's modulus and highest density was found to be 150 °C (injection temperature), 8 bar (injection pressure), 32 °C (mold temperature), 8 min (injection time), 3 wt % (HNTs loading) and mHNT (HNTs type). For the best tensile strain, the six control parameters are found to be 160 °C (injection temperature), 8 bar (injection pressure), 32 °C (mold temperature), 8 min (injection time), 2 wt % (HNTs loading) and mHNT (HNTs type). For the highest hardness, the best parameters are 140 °C (injection temperature), 6 bar (injection pressure), 30 °C (mold temperature), 8 min (injection time), 2 wt % (HNTs loading) and mHNT (HNTs type). The analyses are carried out by coordinating Taguchi and ANOVA approaches. Seemingly, mHNTs has shown its very important role in the resulting product.

Dataset Information

Optimization of Injection Molding Parameters for HDPE/TiO₂ Nanocomposites Fabrication with Multiple Performance Characteristics Using the Taguchi Method and Grey Relational Analysis.

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