Development of a meta-model for the determination of technological value of cotton fiber using design of experiments and the TOPSIS method

ABSTRACT To meet the requirements of the cotton spinning industry and achieve the best quality of ring-spun yarn, it becomes an imperative task to determine the technological values of cotton fibers. The availability of High Volume Instrument (HIV) data now makes it possible to evaluate the quality of cotton fiber with respect to some of its major physical properties. The fiber quality index (FQI), the spinning consistency index (SCI), and the multiplicative analytic hierarchy process (MAHP) are some of the popular approaches adopted by the spinning industry personnel to determine the quality values of cotton fibers. In this paper, while integrating the design of experiments (DoE) and the technique for order preference by similarity to ideal solution (TOPSIS), a regression meta-model is developed for determining the technological value of cotton fiber with respect to the TOPSIS score. This model identifies the statistically significant fiber properties and their interactions affecting the estimated TOPSIS score while fitting a polynomial to the experimental data in multiple linear regression analysis. It is observed that the uniformity index has no importance in quality value evaluation of the cotton fiber, although its interactions with other properties are statistically significant. A validation analysis shows an excellent degree of congruence of this meta-model with the existing models for cotton fiber quality determination.