Statistical modelling and optimization of thermophysiological and tactile comfort properties of sports socks.

The thermo-physiological and tactile properties of socks were analysed by using hybrid yarns which were made by Polyethylene (PE) fibre with different fibres in variable ratios, using full-factorial experimental design. Socks samples were designed using hybrid yarns made with three blend ratios of polyethylene filament with cotton (Co), polyester (PET), polypropylene (PP), modal (Mo) and viscose (Vis) spun yarns. Statistical analysis was carried out according to response surface regression analysis (RSM). Among various analytical tools, RSM is adopted for prediction of multiple responses and response optimizer (RO) was used to optimize the thermo-physiological and tactile comfort i.e. softness and smoothness properties of socks by using the desirability function approach. It was inferred that the combination of cotton with polyethylene was most influencing for thermal conductivity and softness properties. Experimental validation confirmed that predicted variables can be used to design knitted socks fabric with desired thermo-physiological and tactile comfort properties.