From Structure to Feel: Statistical Modeling Using Spss to Perform Some Textile Compositions of Flame Retardant Fabrics

Abstract

Studying the performance of fabric compositions of flame-retardant-treated fabrics is gaining increasing scientific and practical importance, especially in the fields of safety and personal protection. This research focuses on analyzing the mechanical and sensory properties of flame-retardant-treated (2/1, 3/1) and warp-stretch (2/2) fabrics, and correlating these properties using SPSS statistical analysis to understand the relationship between the structural variables of the fabric composition and the functional performance of the treated fabric. The research aims to present a quantitative predictive model that helps improve the design of protective fabrics
while evaluating the changes in properties after treatment based on objective sensory analysis. The results showed that the warp-stretch fabrics (2/2) generally showed greater flame resistance and were the best among the composites in tensile, stiffness, and tear properties (mechanically), while the filbert fabrics showed lower flame resistance, especially the filbert (1/3) with improved crease resistance after treatment (physical), while air permeability was not significantly affected by treatment. The sensory analysis results also showed variations in some sensory properties of the treated samples, especially those measured using fingertips (warmth, thickness, and drape), while the averages of the remaining properties were relatively common to all treated samples. Statistical correlation using SPSS also showed that mechanical properties can be predicted based on sensory analysis, as a strong significant correlation was observed for the test properties: stiffness, wrinkling, tensile strength, and friction resistance, with 14 sensory properties measured based on human hand sensation, with a (Pearson >0.92) and a statistical significance level of (P≤0.1* ʻP≤0.05**). The study successfully predicted some physical and mechanical properties of fabrics, while also shortening the testing step on measuring devices by determining the corresponding sensory properties according to the fabric texture based on tactile sensation.