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Selection of the most appropriate cotton fibre type for yarn manufacturing is often treated as a multi-criteria decision-making (MCDM) problem as the optimal selection decision needs to be taken in presence of several conflicting fibre properties. In this paper, two popular MCDM methods in the form of decision making trial and evaluation laboratory (DEMATEL) and VIse Kriterijumska Optimizacija kompromisno Resenje (VIKOR) are integrated to aid the cotton fibre selection decision. DEMATEL method addresses the interrelationships between various physical properties of cotton fibres while segregating them into cause and effect groups, whereas, VIKOR method helps in ranking all the considered 17 cotton fibres from the best to the worst. The derived ranking of cotton fibre alternatives closely matches with that obtained by the past researchers. This model can assist the spinning industry personnel in the blending process while making accurate fibre selection decision when cotton fibre properties are numerous and interrelated.

Selection of cotton fabrics for providing optimal clothing comfort is often considered as a multi-criteria decision making problem consisting of an array of candidate alternatives to be evaluated based of several conflicting properties. In this paper, design of experiments and technique for order preference by similarity to ideal solution (TOPSIS) are integrated so as to develop regression meta-models for identifying the most suitable cotton fabrics with respect to the computed TOPSIS scores. The applicability of the adopted method is demonstrated using two real time examples. These developed models can also identify the statistically significant fabric properties and their interactions affecting the measured TOPSIS scores and final selection decisions. There exists good degree of congruence between the ranking patterns as derived using these meta-models and the existing methods for cotton fabric ranking and subsequent selection.