Multicriteria Decision-Making in Complex Quality Evaluation of Ladies Dress Material

Srabani Misra 1 , Jana Salacova 1  and Jiri Militky 1
  • 1 Department of Material Engineering, Faculty of Textile Engineering, 46117


Quality is the essence of any product for consumer satisfaction. However, different people have different perception of quality. Eventually the definition of quality varies from product to product and thus it is much more complex in textile clothing material evaluation. The end use application of a specific clothing material determines what should be the parameters of quality evaluation. Thus, the evaluation based on subjective assessment becomes unpredictable and unquantifiable. Quality for dress materials is not simply a physical parameter but something called as psycho-physical parameter. In recent times, many objective evaluation systems have been developed to evaluate the apparel grade textile materials with regard to their quality parameters. However, the evaluation does not involve enough statistical treatment of data so as to obtain a parametric weighted characterization of complex quality. The current work deals with parametric approach to complex quality evaluation based on multicriteria decision-making approach for ladies dress materials. The ladies dress materials are of numerous varieties and choices across the globe. The selection and marketing of these kinds of textile materials need to be given proper emphasis as it depends not only on physical parameters but also on climate, geography, ethnic group, market trend, age group, gender, and many such complex parameters, which are not quantifiable in absolute terms. In this study, woven fabrics used for ladies dress materials are collected from the market and they were evaluated for the consumer-oriented property parameters. A parametric approach is adopted to quantify the overall quality of these dress materials. Various objective techniques were used to evaluate the comfort and esthetic parameters. A complex quality index (CQI) was estimated with weighted combination of all the contributing parameters and total quality index was calculated. Selected consumers with different education level, age, and gender were interviewed to get a statistic of their opinion about quality parameters preferred by them. This complex quality index/degree of satisfaction shows very high correlation with subjective judgment. A CQI can be evaluated for each kind of clothing material looking into their applications.

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  • [1] Murofushi, T. (1992). A technique for reading fuzzy measures (I): the Shapley value with respect to a fuzzy measure. In 2nd Fuzzy Workshop, Nagaoka, Japan, October, 39-48.

  • [2] Abdelaziz, F. B., Olfa, M. (2015). Unstable interaction in multiple criteria decision problems. Journal of Multi-Criteria Decision Analysis, 22, 167-174.

  • [3] Allmendinger, R., Emmerich, M. T. M., Hakanen, J., Jin, Y., Rigoni, E. (2017). Surrogate-assisted multicriteria optimization: complexities, prospective solutions, and business case. Journal of Multi-Criteria Decision Analysis, 24, 5-24.

  • [4] Lolli, F., Ishizaka, A., Gamberini, R., Rimini, B. (2017). A multicriteria framework for inventory classification and control with application to intermittent demand. Journal of Multi-criteria Decision Analysis, 24, 275-285.

  • [5] Wakker, P. P. (1989). Additive representations of preferences: a new foundation of decision analysis, Vol. 4. Springer (Netherlands).

  • [6] Weber, M. (1985). A method of multi-attribute decision making with incomplete information. Management Science, 31(11), 1365-1371.

  • [7] Meloun, M., Militky, J. (2011). Statistical data analysis (Meloun, M., Militky, J. ed.). Woodhead Publishing India Pvt. Ltd. (New Delhi).

  • [8] Behera, B. K., Mishra, R. (2007). Comfort properties of nonconventional light weight worsted suiting fabrics. Indian Journal of Fiber and Textile Research, 32(1), 72-79.

  • [9] Kothari, V. K., Bal, K. (2005). Development of an instrument to study thermal resistance of fabrics. Indian Journal of Fiber & Textile Research, 30, 357-362.

  • [10] Hes, L. (2008). Non-destructive determination of comfort parameters during marketing of functional garments and clothing. Indian Journal of Fiber and Textile Research, 33, 239-245.

  • [11] Kawabata, S., Niwa, M. (1991). Objective measurement of fabric mechanical property and quality: its application to textile and clothing manufacturing. International Journal of Clothing Science and Technology, 3(1), 7-18.

  • [12] Behera, B. K., Mishra, R. (2008). Measurement of fabric wrinkle using digital image processing. Indian Journal of Fiber and Textile Research, 31(1), 30-36.

  • [13] Ghith, A., Hamdi, T., Fayala, F. (2015). Prediction of drape coefficient by artificial neural network. Autex Research Journal, 18(4), 266-274.

  • [14] Hamdi, T., Ghith, A., Fayala, F. (2014). A principal component analysis (PCA) method for predicting the correlation between some fabric parameters and the drape. Autex Research Journal, 14(1), 22-27.

  • [15] Behera, B. K., Mishra, R. (2007). Effect of crease behaviour, drape and formability on appearance of light weight worsted suiting fabrics. Indian Journal of Fiber and Textile Research, 32(3), 319-325.


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