The application of principal component analysis and gray relational method in the optimization of the melt spinning process using the cooling air system

Abstract

This study attempted to optimize the manufacturing process of polyethylene terephthalate (PET) and titanium dioxide-containing (TiO₂) composite fibers. The composite fiber is made by the melt spinning processing method, and has the characteristics of the high strength of PET and the sterilization function of TiO₂. To obtain the optimal processing parameters, this study applied the Taguchi method in planning the research experiment, and set one parameter of two levels and seven parameters of three levels using the L₁₈ orthogonal array. The flow equation was used to design a cooling air system for the manufacturing, and the results showed that using one parameter of two levels can give a stable air pressure to cool the fiber to obtain the characteristics of excellent quality. Finally, field emission scanning electron microscope (FE-SEM) was used to observe the distribution of TiO₂ particles in the PET fiber produced in the experiment, in order to verify the experimental effectiveness. This study used principal component analysis combined with the gray relational method to obtain the optimal parameters of the experiment, because the former has the advantage of data simplicity, while the latter can determine the factors influencing power ranking. Confirmation experiments were conducted to test the quality characteristics, and found that the properties of the fiber produced with the optimal parameters showed improvements.

Keywords

Gray relational theory principal component analysis PET Taguchi method

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