Colour mixing modelling and simulation: optimization of colour recipe for carded fibres

Colour matching between carded and finished fibres is an important challenge for textile industry. The straightforward approach for mixing together some differently coloured fibres in order to obtain a blend of a desired colour is to perform a trial and error approach starting from a given colour recipe and optimizing it with several attempts. Unfortunately, dyeing process so as the carding procedure may result in a carded fibre whose colour is different from the desired one. As a consequence textile companies have to modify the original recipe in order to reduce the gap between the colour of the final product and the desired one. The present work describes a model able to simulate the colour mixing of fibres in order to assess the best recipe. The model consists in two modules: a "prediction module" predicts the colour of a blend obtained by mixing together several fibres; an "optimization module" is used to optimize the final recipe. The devised system has been tested for optimizing the recipe of a set of 200 blends. The mean error in predicting the blend colour is about 15% with a variance of 0.165. The time for optimizing the recipe is reduced by 92%.

[1]  D. Mery,et al.  Color measurement in L ¿ a ¿ b ¿ units from RGB digital images , 2006 .

[2]  W. Marsden I and J , 2012 .

[3]  D. E. Goldberg,et al.  Genetic Algorithms in Search , 1989 .

[4]  Stephen Westland,et al.  Kubelka-Munk or neural networks for computer colorant formulation? , 2002, Other Conferences.

[5]  George L. Hodge,et al.  On-line color monitoring in continuous textile dyeing , 1996 .

[6]  M. Carfagni,et al.  The colorimetric measurement of mélange woollen yarns: a new optical tool , 2011 .

[7]  P. S. Sastry,et al.  Analysis of the back-propagation algorithm with momentum , 1994, IEEE Trans. Neural Networks.

[8]  H. Mangine,et al.  A preliminary comparison of CIE color differences to textile color acceptability using average observers , 2005 .

[9]  S. H. Amirshahi,et al.  An Algorithm for Optimizing Color Prediction in Blends , 1995 .

[10]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[11]  D. Dupont,et al.  Formulation of colored fiber blends from Friele's theoretical model , 2002 .

[12]  Xianyi Zeng,et al.  Colour change as a result of textile transformations , 2008 .

[13]  D. A. Burlone,et al.  Effect of Fiber Translucency on the Color of Blends of Precolored Fibers , 1990 .

[14]  R H Wardman,et al.  A comparison of the colour differences computed using the CIE94, CMC(l:c) and BFD(l:c) formulae , 2008 .

[15]  Stephen Westland,et al.  Application of neural networks to computer recipe prediction , 1991 .

[16]  L. Rong,et al.  Tristimulus algorithm of colour matching for precoloured fibre blends based on the Stearns–Noechel model , 2006 .

[17]  Yong-Keun Lee,et al.  Comparison of the metrics between the CIELAB and the DIN99 uniform color spaces using dental resin composite material values , 2006 .