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Use of Artificial Neural Networks for Modelling the Drape Behaviour of Woollen Fabrics Treated with Dry Finishing Processes

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Abstract:

The relationship between fabric drape, low stress mechanical properties and finishing processes is relatively complex. This paper demonstrates the possibility of using artificial neural networks to identify the fabric drape of woollen fabrics treated with different dry finishing processes (stenter, decatising, superfinish, formula, KADE strong/weak - autoclave decatizing). The mechanical and surface properties of woollen fabrics were measured by both the KES-FB and FAST systems, and then the results obtained were applied to artiicial neural network (ANN) modelling. ANN models were compared by verifying the Mean Square Error (MSE) and Correlation coefficient (R-value). The results indicated that each model is capable of making quantitatively accurate drape behaviour predictions for wool fabrics (Rmin = 0.92, MSEmin = 0).

Tags:

artificial neural network, fabric drape, KES, FAST, wool fabrics, finishing processes.

Citation:

Kursun Bahadir S, Kalaoglu F, Jevsnik S, Hanife Eryuruk S, Saricam C. Use of Artificial Neural Networks for Modelling the Drape Behaviour of Woollen Fabrics Treated with Dry Finishing Processes. FIBRES & TEXTILES in Eastern Europe 2015; 23, 2(110): 90-99.

Published in issue no 2 (110) / 2015, pages 90–99.

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