More quality in textile finishing: reproducibility of processes in laboratory and production

The fuzzy logic-based approach was applied in studying the influence of a different textile surface structure on colour appearance and similarity. The fuzzy-based approach has been chosen because fuzzy logic provides the computerising of human reasoning. For the analyses, 100% cotton samples with certain characteristics were chosen. First, the computer match prediction was performed to determine the concentrations of dyestuff to be used in the experimental work. A yellow-shaded direct dyestuff suitable for cotton dyeing was used. In the next step, the fuzzy logic system was created based on terms that would define the surface characteristics of the samples. The most important part was a proper definition of the rules and linguistic variables that use words for assigning the values of properties and that influence the experience of an observer (gloss, smoothness, roughness, etc.) and connect input space with output space. Finally, the performances of both systems were compared and analysed. In this work, the approach was based solely on the surface-structural characteristics of textile samples. The main aim was to examine the approach using the fuzzy logic-based technique in order to provide the method that would include surface parameters of textile samples that are of importance in applying colour to different structured textile surfaces. It was confirmed that the fuzzy logic reasoning would have its application in the control of the influence of the surface structure of coloured textiles, especially for lighter shades where the influence of structure parameters on the colour experience of an observer is more emphasised.

Section: Resultsmentioning

confidence: 93%

Research of influences of surface structure of coloured textiles: applying fuzzy logic

Glogar

Parac-Osterman

Grundler

et al. 2011

“…In most practical cases, dye amount variations of ±3% within one batch are commercially tolerable, equivalent to a variation coefficient of 1.5% [17]. The critical unlevelness value of 1.5% is indicated in Figure 1 as a horizontal line.…”

Section: Resultsmentioning

confidence: 99%

Dye demand/supply ratio as a predictor for the unlevelness of disperse‐dyed polyester

Ferus-Comelo¹

2009

The ratio of the demand for dye by the fibre and the supply of dye by the dyebath is a useful indicator to predict unlevelness in the exhaust dyeing of polyester with disperse dyes, provided that dispersion breakage is small. The ratio can be calculated from the dye exhaustion curve, the dye solubility and the flow rate in the machine. The findings suggest that unlevelness can be successfully controlled by ensuring that dye demand never exceeds dye supply at any moment during the dyeing process.

“…Colour reproducibility has always been a key concern in textile dyeing. It is well known that a number of factors can infl uence colour reproducibility, among them the accuracy of dyestuff weighing, substrate and water quality and the consistency of the dye [1][2][3][4][5][6][7]. From the dyehouse standpoint, some of these factors are not controllable, an obvious example being substrate quality in a commission dyehouse.…”

Section: Introductionmentioning

confidence: 99%

Physico‐chemical modelling of the dyeing of cotton with reactive dyes

Ferus-Comelo

Clark

2004

Over the past decades a great deal of research effort has been devoted to understanding the physico‐chemical mechanism of the dyeing of cotton with reactive dyes. However, the use of physico‐chemical models has been almost exclusively restricted to research laboratories due to the simplifying assumptions used. A more practical model has now been developed and is intended to allow dyeing recipes and the process parameters used in bulk production to be optimised. The model is additionally able to quantify the effect of non‐controllable variables on overall dyeing efficiency.