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 (TiO 2 ) 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 TiO 2 . 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 L 18 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 TiO 2 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.

Integration of multivariate control charts and decision tree classifier to determine the faults of the quality characteristic(s) of a melt spinning machine used in polypropylene as-spun fiber manufacturing Part I: The application of the Taguchi method and principal component analysis in the processing parameter optimization of the melt spinning process

“…The experiment was performed using the single quality optimum processing parameters given in Table 11. The experimental result was converted using equation (1) to the smaller-the-better characteristic. The S/N ratio of fineness was À46.88, and the difference from the prediction value was 4.03%.…”

“…Melt spinning is the most economical spinning process and has been extensively used in the textile industry for various polymers and applications. [1][2][3] Polypropylene (PP) is a remarkable textile fiber. It has several advantages such as good abrasion resistance, flexibility, high strength resistance, it is light weight, has good antistatic character, good chemical resistance, and is low cost.…”

Development of multifunctional warming fabric part II: Multi-quality process parameter optimization of hygroscopic heating and antistatic function yarn

“…The result shows that GRA optimization had the minimum mean error percentage. Kuo et al 26 applied the Taguchi method in planning a research experiment using the orthogonal array combined with the GRA to obtain the optimal parameters of the melt spinning process. It can be observed that GRA can sequence the effects of factors on quality with a grey relational coefficient.…”

Property modification and process parameter optimization design of polylactic acid composite materials Part II: application of response surface methodology and multi-objective particle swarm optimization in the processing of polylactic acid composite fiber

“…The most influential factor for the modulus of resilience is spinning temperature. Kuo et al 6 found that a cooling air system could effectively enhance the various quality characteristics of PET fibers, and the optimization theory of principal component analysis (PCA) and gray relational analysis could enhance the yield strength and ultimate strength by 5.6% and 7.2%, respectively. As shown in the references mentioned above, the characteristics were affected by the factors of melt temperature, spinneret speed and coiling roller speed.…”