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

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.