A study of optimum processing parameters and abnormal parameter identification of the twin-screw co-rotating extruder mixing process based on the distribution and dispersion properties for SiO₂/low-density polyethylene nano-composites

Abstract

This study took nano-silica particles mixed in low-density polyethylene to implement the optimum processing parameters and make abnormal parameter identification for the twin-screw co-rotating extruder used in the manufacturing process. The mixing quality was divided into distribution and dispersion, where distribution was tested by an energy dispersive spectrometer and evaluated using the coefficient of variation. Dispersion was assessed by the surface effect and specific surface equations, as based on the spectrum of scanning electron microscopy. By using the Taguchi method in planning the experiment coupled with an analysis of variance, we conducted the single-quality characteristic analysis of the experimental results of the two quality characteristics, namely the distribution and dispersion. Then, by using the hierarchical architecture of analytic level process, we can obtain the optimized parameter factors and levels and the calculation of the total weighting of various parameter levels, as well as the ranking of the parameter levels. According to the confirmation experimental results, the signal-to-noise ratios of distribution and dispersion fell within 95% confidence intervals, indicating that the experiment can be represented and reliable. The optimum parameters combination is SiO2 addition level 1%, screw speed 60 rpm, mixing time 5 min, temperature (upper) 150℃, temperature (middle), 175℃ and temperature (lower) 190℃. After that, by using the optimal parameters and operation processing parameters for support vector machine classification, the abnormality of the processing parameters can be identified for 100%. The good quality of the production can be guaranteed during the extrusion.

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“…The Taguchi quality method [34][35][36][37] uses orthogonal arrays to carry out experiments and employs signal-to-noise (S/N) ratios to analyze the corresponding experiment data.…”

“…The S/N ratio obtained from the Taguchi experimental design is used to demonstrate the impact of factors on the overall experiments. The ANOVA [32][33][34][35] is described as follows:…”

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“…MEA was used to describe the effect of changes in specific factor levels on the observed values, and a response graph were used to observe the corresponding factor values to determine the most influential variation factor of the entire experiment. [30][31][32] When the main factor effect was higher, this factor would have a greater impact on the experiment. Conversely, when the main factor effect was lower, this factor would have a smaller impact on the experiment.…”

“…An analysis of variance (ANOVA) was used to separate the variation to determine how much the control factor affected the overall experiment in the Taguchi experiment. 33,34 The factor with greater significance and contribution would be more effective for the overall experimental benefits to change the parameter. The other factors with insufficient significance were classified as the combined error, which was used to judge whether the experiment design was reasonable and provide the influence of each factor in the process.…”

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“…The combination of these two features allows for better dispersion of the filler in the polymer matrix, but a limitation of the process is the fact that the shear forces cause an increase in temperature due to friction [5,6]. It is difficult to describe this process mathematically because there are many variables here that are specific both for the polymers themselves and even for polymer-filler systems [7][8][9][10]. Often, as modelling is conducted, a single section or even a single-screw element of an extruder is referred.…”