Optimization of the water-based polyurethane with acrylate terminal process in nylon fabrics application using the Taguchi-based gray relational analysis method

Abstract

This study synthesized the water-permeable and hydrophobic property of water-based polyurethane (WPU) and applied it to nylon fiber-based functional textiles. Specifically, poly-stearyl acrylate (PSA) homopolymers with different molecular weights were used as end-capping agents in the WPU to form water-based polyurethane with acrylate terminal (WPUA). In the WPUA process, dimethylacetamide was adopted as a neutralizing agent to form a stable WPUA emulsion. The effects of the design parameters, such as the hydrophilic ionic group dimethylol propionic acid (DMPA), the PSA molecular weight and content, were set as the control factors and are analyzed by the Taguchi method and gray relational analysis (GRA). The water-repellent characteristic, water vapor permeability (WVP) and fabric flexural rigidity were considered as performance parameters as multi-qualities. The Taguchi method was based on the analysis of variance and implemented orthogonal arrays for experimental design. Each performance parameter was optimized independently. Then, the performance parameters were optimized together with GRA. According to the experimental results, the most important factor for the water-repellent characteristic, WVP and fabric flexural rigidity is the DMPA content, followed by the PSA molecular weight and content. The corresponding results showed that in the optimal parameter combination, the content of DMPA was 30.8 phm (parts per hundred monomer by weight), the PSA molecular weight was 3000 g/mol and the PSA content was 4 phm. After WPUA padding, the water contact angle of the water-repellent nylon was 135.3°, the WVP was 2271.7 g/m2/day and the flexural rigidity was 2.7 cm.

Functional dyeable polypropylene fabric development and process parameter optimization. Part II: Development of graphene thermal insulation dyeable polypropylene fabric with process parameter optimization

“…The analysis of variance (ANOVA) 27,28 is used to evaluate the experimental error and confirm the influence of each factor on the significant factors in the product process. The control factors of the melt-spinning process include nanographene content, mold temperature, metering pump speed, melting temperature, hot roll speed and take-up speed.…”

“…The Taguchi method [23][24][25][26][27][28] used an orthogonal array to design experiments to study the influence of the control factors. The signal-to-noise (S/N) ratio is employed to analyze the experimental data to find the optimum parameter for each quality.…”

“…The factor with a greater degree of significance means that changing the process parameters can effectively achieve process benefits. The ANOVA table in this study 27 for five control factors (A-F) is shown in Table 1.…”

“…The L18 orthogonal array [25][26][27] was used for the design of the experiments. The yarn count of the fiber was tested according to the ASTM D1577 standard.…”

Effects of boron nitride nanotube content on waterborne polyurethane–acrylate composite coating materials

“…WPUA exhibits the advantages of both constituent polymers, and many studies have investigated optimizing the properties of WPUA as a coating material. 11,12 For example, Deng et al demonstrated the effect of the polyurethane/polyacrylate ratio on the properties of WPUA hybrid emulsions and films. 13 Although WPUA shows considerably enhanced performance in flexible and hard coatings, for applications under harsh conditions, other properties such as acid resistance, thermal stability, and electric insulation need to be further developed.…”