Fuzzy Logic Method for Predicting the Effect of Main Fabric Parameters Influencing Drape Phenomenon

Open access


The main aspect of this research was to predict the drape parameters and describe clearly the drape phenomenon using fuzzy logic method. Forecasting features allow manufacturers to save time and improve their productivity. The bending rigidity, (in warp, weft, and skew direction), shear rigidity, and weight of fabric samples were used as the key input variables for the model, whereas drape coefficient, drape distance ratio, folds depth index, and node number were used as output/response variables. The results show that changing the values of fabric parameters significantly affected the fabric drape and a representative correlation values were found between the experimental values and those calculated by the fuzzy system.

[1] Basu, A., Chellamani, K. P., Ramesh, P. R. (2002). Fabric engineering by means of an artificial neural network. Journal of the Textile Institute, 93(3), 283-296.

[2] Hu, J. L., Chan, Y. F. (1998). Effect of fabric mechanical properties on drape. Textile Research Journal, 68 (1), 57-64.

[3] Tehran, M. A., Maleki, M. (2011). Artificial neural network prosperities in textile applications, Croatia: InTech, Rijeka, pp. 35–64.

[4] Fan, J., Newton, E., Au, R., Chan, S. (2001). Predicting garment drape with fuzzy neural network. Textile Research Journal, 71(7), 605-608.

[5] Guo, Z. X., Wong, W. K., Leung, S. Y. S., Li, M. (2011). Applications of artificial intelligence in the apparel industry. Textile Research Journal, 81(18), 1871-1892.

[6] Guruprasad, R., Behera, B. K. (2010). Soft computing in textiles. Indian Journal of Fibre and Textile Research, 35(1), 75-84.

[7] Vassiliadis, S., Rangoussi, M., Cay, A., Provatidis, C. (2010). Woven fabric engineering: artificial neural networks and their applications in the engineering of fabrics. Croatia: Sciyo, Rijeka, pp. 112-134.

[8] Chattopadhyay, R., Guha, A. (2004). Artificial neural networks: applications to textiles. Textile Progress, 35(1), 1-46.

[9] Breen, D. E., House, D. H., Wozny, M. J. (1994). A particle-based model for simulating the draping behavior of woven cloth. Textile Research Journal, 64(11), 663-685.

[10] Pattanayak, A. K., Ameersing, L., Asimananda, K. (2010). Prediction of drape profile of cotton woven fabrics using artificial neural network and multiple regression method. Textile Research Journal, 81(6), 559-566.

[11] Chu, C. C., Cumming, C. L., Teixeira, N. A. (1950). Mechanic s of elastic performance of textile materials. Textile Research Journal, 20(8), 539-548.

[12] Cusick, G. E. (1965). The dependence of fabric drape on bending and shearing stiffness. Journal of the Textile Institute, 65(5), 596-606.

[13] Mooreka, H., Niwa, M. (1976). Relation between drape coefficient and mechanical properties of fabric. Journal of Textile Institute, 22(3), 63-67.

[14] Ayada, M., Niwa, M. (1991). Relation between the comfort of gathered skirts and fabric mechanical properties. Sen-I Gakkaaishi, 47(6), 291-298.

[15] Bruniaux, P., Vasseur, C. (2001). Modeling and identifying the parameters of a fabric drape model. Textile Research Journal, 71(4), 336-342

[16] Bruniaux,P., Ghith, A., Vasseur, C. (2003). Modelling and parametric study of a fabric drape. Advances in Complex Systems, 6(4), 457-476.

[17] Ghith, A., Hamdi, T., Fayala, F. (2015). Prediction of drape coefficient by artificial neural network. Autex Research Journal, 15(4), 266-274.

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

[19] AFNOR (1984). Essais des étoffes, Détermination de la masse surfacique des tissus et des tricots. Normes Françaises; NF G 07-150.

[20] Hamdi, T., Ghith, A., Fayala, F. (2013). Study of drape parameter using image analysis. International Journal of Engineering Science and Technology, 5(7), 1456-1464.

[21] Jeong, Y.J., Philips, D.G. (1998). A study of fabric-drape behavior with image analysis part I: Measurement, characterization, and instability. Journal of the Textile Institute, 88(1), 59-69.

[22] Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338-353.

[23] Hamdi, T., Ghith, A., Fayala, F. (2017). Characterization of drape profile using Fuzzy-C-mean (FCM) method. Fibers and Polymers Journal, 18(7), 1401-1407.

Autex Research Journal

The Journal of Association of Universities for Textiles (AUTEX)

Journal Information

IMPACT FACTOR 2018: 0.927
5-year IMPACT FACTOR: 1,016

CiteScore 2018: 1.21

SCImago Journal Rank (SJR) 2018: 0.395
Source Normalized Impact per Paper (SNIP) 2018: 1.044


All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 46 46 10
PDF Downloads 35 35 9