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Pubalina Samanta*

  • Lecturer (Contractual), Dept of BFAD, Rani Birla Girls’ College, India

Received: September 03, 2018;   Published: September 11, 2018

*Corresponding author:Pubalina Samanta, Lecturer (Contractual), Dept of BFAD, Rani Birla Girls’ College, Kolkata, He’s an American former professional boxer. He was well known for his ferocious and intimidating boxing style as well as his聽… India

DOI: 10.32474/LTTFD.2018.02.000148

Abstract

PDF

The analysis of colour in terms of hue, value and chroma has its

origin deeply rooted with Ostwald concept of colour quantification,

though from the epic age, this colour has played an important

role in human life. This inspired us to explore the vast storehouse

of the natural’s palette to initially paint ourselves then to dye

the apparels. According to Trottman [1] dye stuffs give colour to

the material onto which they have been anchored, by selectively

retaining some of the wavelengths out of the light falling upon the

surface. If a dye absorbs strongly at the red end of the spectrum

the light that is reflected will be of a bluish hue. Only a limited

number of organic molecules possess this property of absorbing

light selectively. Ever since about 1860 intense interest has been

displayed in investigations to discover which aspects of molecular

structure are responsible for Table 1.

Table 1: Data showing different wavelength of absorbed light/

visible colour.

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According to Shah & Gandhi [2] colour is something which

makes the object more appearing, attractive & gives the pleasure

of observation. The committee on colorimetry of optical society

of America defined the colour as visual sensation arising from

the stimulation of retina of the eye. Thus, it is defined as psychophysical

a psychological response to a physical stimulus. So,

in brief, to chemist, it may be a chemical compound, a dye or a

pigment, to physicist it is a scattering & absorption of light or

reflectance spectra of the object, to physiologist it is a measurable

electrical activity of the nerves, to psychologist it is a complex

process in brain of interpreting the nerve signal. To artist & others,

it is the means to create sensation in the mind of the observes. In

order to understand the colour we have to know, how the colour

is perceived. The perception of colours involves the interaction of

three elements.

a) Source of light

b) An object

c) Human eye

Ordinarily, in a dye house there are many industrial processes

where accuracy in colour is important mainly for the human ability

to differentiate and identify object and makes it for the task of

colour matching and assessment to maintain quality of textile,

print ink, plastic, cosmetics, food, leather, sugar, etc. According to

vallia [3] in these industries either of the following methods of

colour matching or assessment by visual methods is used. Colour

grading is the judgment of either equality or difference in colour on

surface of objects. Typical products that are colour graded are raw

cotton, tobacco, fruit, vegetables and furs. In some instances, such

products are accepted or rejected on the basis of visual inspection

of colour specifications or standards. In colour matching, samples

of a material are matched against the colour of a reference sample

or standard is more exact in its requirement than colour grading.

Many colours of materials or surfaces may appear to match under

one type of light source but not under another. Such a match is

known as metameric colour match.

Colour shading is the adjustment of the proportions of the

ingredients in a mixture to improve colour conformity to a standard.

It is a form of colour matching and require the same type of lighting used for colour matching. The mixing of pigments, dyes are examples

in which colour shading is employed. Many misconceptions [2]

exist about colour matching and assessment and it is difficult to

review all aspects of this complex and fascinating subject Here,

essential aspects on practical techniques & precautions to be taken

are discussed which should help are to perform industrial colour

matching tasks by visual methods. In Textile Industries [1] the

desired colour is obtained by mixing by three or four dyes. The most

important problem in the industry is how to arrive at the perfect

match to customer’s samples using minimum amount of chemicals

& colorants. This job is normally attended by professional colour

technologists, who by his remarkable ability, the three or four dyes

colour recipe to reproduce a given shade.

In Textile Industries, an expert dyeing master maintains the

record of his experience in ‘shade bank’ & select one of the colour

recipe which may be close to standard. He, then makes necessary

changes by trial & error method to obtain the exact match. In past

this task was comparatively easy with limited number of natural

colours & Fibers. The colour matching has now become more

difficult due to increase in manmade fibers, multi blend fibers &

almost endless number of dyes available in the market. With all

these parameters, the arbitrary selection of colour recipe, which

may be most economical & give better quality product is almost

impossible.

In last two decades the researches in colour science,

advancement in optical technology & computer science have

resulted into the instruments which can give number of colour

recipe for a given sample. This new technology enable the dyeing

master to work out several colour recipes & to select the most

appropriate recipe depending on the cost of production & quality

of the products required.

This technique is known as computer aided colour matching

(CACM), computerized colour matching prediction (CCMP)

system or Instrumental Match Prediction (IMP). The introduction

of computerized colour match prediction system in any textile

industry is aimed to provide a powerful tool in expert colourist’s

hands to improve the quality of the products in terms of precission

matching of colur at reduced cost of production. In 1958, Davidson

& Hemmendinger [4] introduced an analogy computing device

which took care for colour recipe formation for paint industry

initially & later extended to textile application by them in 1963.

At present [5] the world has switched over to a computer age &

attempts are being made with the use of sophisticated, to specify &

formulate the complicated techniques. Previously colour matching

in textile was restricted to the skill of the dyeing masters in the dye

house. But to eliminate the problem of getting in exact match of the

given shade, now most of the dye house is controlled by computer

colour matching technique which not only saves manpower, energy

& time but also increases the accuracy.

Colour Matching is the art of reproducing the exact shade.

CCMP is the science of predicting the recipe or formula for the

exact shade reproduction. Hence, this technique is known by

names e.g. computer colourant formulation, computer recipe

prediction, Instrumental colour matching & spectrophotometer

or instrumental match prediction. A colour Matching computer

system involves three basic modules, viz:

a) Colour measuring instrument: Reflectance

Spectrophotometer, which expresses the colour in numerical

form in terms of X, Y, Z or R or K/S and DE values.

b) Computer hardware: Usually latest PC or Laptop based

Computing and data analysis and storing system for data

processing and converting and storing and comparing etc.

c) Specific Logic system / Colour Measuring Software to

express this data into information relevant to the colourist i.e.

Colour measuring and matching Software for analysis.

Keywords: Jute; Vat Dyes; Home Furnishing; Decorative Textiles

Perfect colour match [6] with minimum dye cost is most

important criteria for a dye house which is now computerized.

The computerized colour match prediction (CCMP) for textiles

are usually based on Kubelka munk equation & park & stearn’s

[7] algorithms & Allen’s [8] matrix for recipe formation program.

Colour matching with the aid of computer with specialized software

development (based on reflectance measurement & conversion

to K/S values from dyed solid textile surface) now become

wide spread. Multiplication of variability’s [9] for colouration

& colour measurement are reduced by various selective modes,

approximation, simplification, as colour matching was done by trial

& error method, restricted to the skill of dye master & no record

of all trial is maintained & also matching in night shift become

impossible. The strength of dye & quality of dye requires from batch

to batch & on quality check for this recorded in mill. Therefore, by

the application of computerized colour matching system the above

problems are eliminated along with the dye cost saving, better &

perfect match & quicker matching recipe generation.

Colour can be measured by its tristimulas values x, y, z or by

total reflectance or its derivative formula function like K/S.CIETristimulas

value [5, 7] of a coloured substrates may be defined as

X=Σ Pλ xλ Rλ

Y=Σ Pλ yλ Rλ

Z=Σ Pλ zλ Rλ

Where Pλ=Spectral power distribution of standard source,

Rλ=Spectral reflectance of substrate and xλ. yλ. zλ=colour factor of

standard observer for red, blue and green.

To describe colour in two-dimensional plot. CIE defined

following chromatically coordinates (x, y, z).

While

From which the saturation can be determined & from the two,

the third one can be determined easily.

A colour match means: colour of produced sample=colour of

given standard i.e.

(XSL, YSL, ZSL) Colour=(XSD, YSD, ZSD)

while X, Y & Z are the tristimulus value of Sample (SL) and

Standard (SD) or (Reflectance)SL (400 to700 nm)=(Reflectance)SD

(400 to 700 nm) or(K/S)SL=(K/S)SD while K/S=α C

For a mixture of colourants, therefore, three equations are to

be solved as a function of dye concentrations of the colourants

(2,3 or n) and tristimulus values measures through reflectance

measurement.

Where x, y, z are values of samples to be matched & c1, c2, c & c3 are

concentration of colour required. In practice, the reflectance values

at 400 to 700 nm are measured from dyed solid textile surface&

those reflectance data are processed for K/S Values generation for

ultimate matching. Reflectance value vs. concentration of dye is

non-linear & non additive & linear, so this is used as basic data for

handling colour match predicting. As per Kubelka Munk Equation.

S, the coefficient of scattering; and R?max, is the Reflectance

value at maximum absorbance wavelength (λmax) and CD is the dye

concentration and α is the constant.

For mixture of colourants,

For dyes on textiles, it is assumed that dyes do not contribute

to scattering and K is the sum of dye stuff absorption and substrate

absorption (substrate is fixed). Therefore K/S directly varies

with concentration of dyes and scattering is independent of dye

concentration (which is not the case of pigments in paint). So, in

textile it is single constant theory of Colour Matching applicable

for textiles. For textiles, for the particular sample (Material, Yarn

& fabric construction & surface finish remaining unaltered),

scattering remains constant. Thus, higher the K/S value, meant

higher absorption value, meant higher absorption value signifying

or indicating higher dye uptake.

More over K/S is additive in nature and hence,

Finally, reflectance Vs. dye concentration is not linear & is difficult

to interpolate or curve fitting. While K/S Vs. dye concentration is

linear can be interpolated thus can be used in CMM software. The

total colour difference (ΔE) values are measured by measuring

corresponding L*, a*, b* values before and after the treatments/

dyeing using the computer-aided reflectance spectrophotometer

along with associated Colour-Lab plus software employing

following CIE-Lab equations as per CIE standard-1976, to compare

the shade depth of one with other comparative standard samples: –

i. ΔE=[(ΔL Calibration Samples: The dyeing conditions in

the laboratory & productions differ in various respects viz, M: L

ratio, auxiliaries dyeing machines, exhaustion of dye etc.

ii. Change of Substrate: It is very difficult to maintain the

characteristic properties of the substrate as regards the quality

of the fibers, yarn structure, fabric construction, colour, heat

setting, pretreatments, etc. which in turn changes the dye

uptake properties of the fiber. It is particularly impossible to

prepare the basic calibration data under all such variation.

iii. Change in Dyestuff: Every incoming batch of the dye stuff

requires testing for tonal & strength changes which needs

recalculation of the recipe.

iv. Recipe suggested by the computer are based on minimum

colour difference within given tolerance & least metamerism in

CIELAB scales. But always CIELAB tolerances do not confirms

exactly with human perceived colour difference.

v. Light sources used to test the match, are CIE standardized

simulated standard illuminant, which are not same in all

respect with natural sunlight. Instrumental accuracy may be

checked periodically.

vi. The kubelka-munk equation & optical theory of computer

colour matching do not apply strictly on extra glossy or

fluorescent samples. In K – M equation the air scattering

& interaction of air & textile substrate is not considered &

therefore the K/S vs. concentration of dyes curves deviates from

linearity. For practical purpose, the curve required to modify

to make it linear to apply the above theory and therefore the

recipe obtained from computer deviates from actual.

Lupinepublishers-openaccess-journals-Textile-Fashiondesigning

Lupinepublishers-openaccess-journals-Textile-Fashiondesigning

Chroma, (psychometric chroma) values in CIELAB color space

was calculated as follows: –

Lupinepublishers-openaccess-journals-Textile-Fashiondesigning

Where, C*1(ab) and C*2(ab) are the chroma values for standard and

produced sample.

CIE 1976 metric Hue-Difference (ΔH) for CIELAB system was

calculated as follows: –

Lupinepublishers-openaccess-journals-Textile-Fashiondesigning

An isomeric match i.e. matches under all illuminant & when

two coloured sample show match under one illuminant but do

not match under any other illuminant is termed as metameric

match. Least metameric match prediction & sorting is based on the

calculation of general metamerism index as given below:

x , y , z=CIE standard observer colour function X, Y, Z=CIE tristimulas value normally taken for illuminant C .It is average

of two specimens. Either the metamerism tolerance can be set or

after recipe generation it is left to the user for choosing the limit for

least metamerism among the number recipe generated as shown in

Tables 1 & 2, in case of computerized colour matching prediction

with direct dye classes on bleached jute fabric. Among the three /

four alternate recipe dyer can choose as per his/her dye stock or

as per requirement of Cost minimization or as per least metameric

match as per requirement of customer. The match predicted is still

on paper and hence dyer need to do lab dyeing with that recipe for

confirmation of match obtained. This confirmation is to be done by

re-measuring the produced first match dyed sample as compared

against standard sample. Usually some differences are observed

always, and that correction is to be done by batch correction using

reformulation technique available in all computerized colour

matching system of any company

Table 2: Data of a Color Match Generated from the Database of Direct Dye.

Lupinepublishers-openaccess-journals-Textile-Fashiondesigning

From above Table 2, it can be seen that formula 3 is the least cost and least metameric, though all of the three recipes satisfy colour

tolerances values.

Colour Matching Tolerance setting is another important task

for match master in industry. It is generally thumb rule that DE values

below or within 1.0 are acceptable match. But in industry, people

like to set more stringent New colour prediction website signup bonus 60 rupees minimum withdrawal hundred rupees without lodd tricks handle 200%聽…tolerance for colour matching like DE

value within 0.7 only. One of the major benefits of colour difference

system is the ability to relate perceived colour differences between

two or more objects to a numerical description of that difference in

terms of total colour differences ( DE values) and also in terms of

DL( light and dark) , Da ( redness and greenness) and Db ( blueness

and yellowness) to help dyers to add or subtract particular colour

to get better match by batch correction either manually or instrumentally

The reformulation of batch correction mathematics for

computing the incremental value of concentration of dyes by each

iteration at each stage are as follows:

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Colour difference equations should be designed to give the

extent and direction of colour difference between two samples;

and do so in units that are visually meaningful. They should also

provide the means to quantify sample to standard differences on

a repeatable and reproducible basis. In 1976, CIE (Commission

International de eclairase, Paris) colorimetry committee defined

CIE L* A* B*, in short CIELAB, colour coordinates Hey everyone,how ya doin?Hope youre having wonderfull xmax 🙂 Btw,Id like to know what would you like to see for Xmas here聽…system (an easy

comparative colour difference evaluation coordinates), where

redness and greenness are expressed by a single number ‘a’, which

is positive if it is red and negative if it is green. Similarly, yellowness

or blueness is described by ‘b’. which is positive if it is yellow and

negative if it is blue. ‘L’, another coordinate, represents the lightness

or darkness of the colour, 0 at black 100 at white. CIELAB provides

very useful colour difference space diagram, which is shown in

Figure 1.

It is further necessary to develop mutually agreeable pass/fail

system which specifies tolerance of these colour difference Adex Club || Anup Kankarwal || REGARDING PAYOUT || 12-10-2020. criteria

for diffe?rent textiles; these may be applicable while considering

batch to batch variation. As jute mills have not procured this

system so far, and those mills or their dyers are not familiar with

these tolerances and computerized match prediction system etc.,

they may presently send their samples to nearest Centre where

it is available, for necessary results, to understand the colour

differences from standard sample ordered and colour differences

from batch to batch variation of company production ‘level; so that

chance of rejection in export level on this ground may be avoided.

To set up these tolerances is a complex phenomenon and

different practical Booe app Saturday and Sunday ko recharge not process and weeks Monday ko recharge hoga.approaches are made using different colour

mathematics. However, the best scientific approach is as follows:

The tristimulus values of various bulk dyed lots along with their

visual assessment may be recorded and corresponding dE total, dL,

da .& db and/or dL, dC & dH may be recorded and finally either is

a da vs db orda vs dL plot, the visually accepted lot marked by dot

and visually rejected lot marked by cross will generate a tolerance

ellipse by periphery of dots of maximum distance from centre as

shown in Figure 2.

Figure 2: da vs db colour plot.

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To set up these tolerances is a complex phenomenon and

different practical approaches are made using different colour

mathematics. However, the best scientific approach is as follows:

The tristimulus values of various bulk dyed lots along with their

visual assessment may be recorded and corresponding dE total, dL,

da & db and/or dL, dC & dH may be recorded and finally either is

a da vs db orda vs dL plot, the visually accepted lot marked by dot

and visually rejected lot marked by cross will generate a tolerance.

These are symmetric and asymmetric sets of colour toler?ances.

In general, for cotton textile, if not unusually presented, the more or

less symmetric colour tolerances set are:

dL=0.7 to 1.2; da=0.6 to 1.0 db=0.6 to 1.0; dE=1.0 to 1.8 For

certain shades, these limits could be narrower.

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The major factors responsible for batch to batch set variation

are

a) Weighing error.

b) Substrate\variation.

c) Pretreatment or heat setting variation.

d) Dyeing condi?tion change or additive variation.

e) Dye selected and purity of dye.

The basic steps [5] involved in the application of the colour

matching in practice can be broadly classified as:

i. Determination of optical constants by calibration dyeing

and storing dye class wise and company-wise dyestuff database

for a particular type of fabric.

ii. Measurement of colour value of standard samples and

finding Match Recipe/formulation on computer for particular

match selecting stored database for correct class of dye and

putting correct/desired tolerances of colour matching to be

done.

iii. Batch Correction and Recipe correction to achieve better/

precise match.

Optical constants are determined by measuring calibration

dyeing prepared by dyeing different dyes at 6-9 different levels (say

within 0.1% to 3%) which form a data bank of all the required dyes

pertaining to a substance using a particular process is stored on the

file of computer. Dan Randall85 explained that the preparation of

reliable calibration dyeing is the first & most important step in the

successful development of a colour matching program. For optimum

performance, the lab dyeing process must be highly controlled & the

data accurately evaluated by the colourist. The recipe formulation

of the match prediction process requires measurements of shade

to be matched with a substrate, the selection of dye inventory &

tolerance limits of the colour differences. The tristimulus values of

standard are computed for different light sources & by comparing

them with optical constants of the dyes stared in the data bank the

unknown concentration is determined. If the predicted recipe falls,

can be corrected by the batch correction programmers. Materials

of shades on the blended fabric is also essentially carried out

similarly but the data banks with different dyes applied to both the

components of the blend are stored separately [10].

In addition, textile colourists are required to produce a given

shade many times, by using a mixture of dyes. Dye manufactures

usually supply information on dyeing characteristics of an individual

dye, but practically, dyers need to know the behavior of dyes in

mixture, for which data are often not available. For satisfactory,

uniform, barer-free dyeing with mixture of dyes, the colour should

built up on the fiber in such manner that the ratio of the component

dyes on the fiber remains throughout the dyeing process i.e. dyes

applied in admixture should be compatible, the depth of colour

increasing with constant hue. Along with visual assessment,

dyeing method, diffusion test & dip test are the methods used to

check the compatibility of dyes in mixture, but these methods have

limitations. So, by measuring the colour of the dyed samples under

commonly used illuminants; the results are recorded in terms of

colour co-ordinates i.e. dl*, da*, db* & dE* in CCM technique. The

computer calculated the colour differences of the sample from the

standard fabric & also the colour components. Thus, this method

based on the built up of total amount of dye in terms of K/S values,

gives similar information about the compatibility of dyes having

closely similar hues, thereby making it a more useful technique for

practical dyers.

The reflectance spectrophotometer [2] measures the

reflectance of the sample separately at each wave length. For colour

measurements, it records the reflectance in visible spectral region

from 400-700 nm at an interval of 5nm, 10nm, 20nm as required.

For textile samples, the measurements in a spectral range from 400

to 700 nm at 20 nm intervals has been happened.

The spectrophotometer marketed till this day can be classified

into four distinct categories. Viz,

a) The First Generation : Prior to 1936

b) The Second Generation : 1936 – 1949

c) The Third Generation : 1949 – 1976

d) The Fourth Generation : 1976 – 2000

e) The Fifth Generation: 2001 to present

The first generation spectrophotometers were developed

on the recommendations of the CIE. Despite certain limitations,

encouraging results were reported, though each measurement

was a lengthy and tedious process. The second generation

spectrophotometers, which is considered as a standard instrument

even today was developed by Hardy & manufacture by General

Electric company, USA but presently manufactured by Diano

Corporation, USA.

The Third generation spectrophotometers were mainly the

abridged spectrophotometers based on interference filters.

The fourth and fifth generation spectrophotometers totally

replaced the conventional curve plotting spectrophotometers.

These new instruments are interface to general purpose mini

computers which provide speed high degree of reproducibility &

long-term repeatability and data storing facility. Some of the option

Available in most of the CCMP system are as follows;

The process of calibration is done so as to bring the instrument

in working order.

Color (Visible Light – 400nm-700nm) is measured between

maximum reflectance (100% White) and maximum absorption

(100% Black). In order to set these parameters, the instrument

scans a standard White tile and a standard Black tile/trap.

In Quality Control an incoming batch can be compared against

your existing standards. Subsequent outputs can be seen in terms

of Tone & Strength. A detailed analysis of the samples is done in

terms of its Hue, Lightness, Saturation and its overall position in the

Color space index. Quality Control will let you make a graphical as

well as a statistical analysis of the measured samples.

a) Color Difference: To see outputs of Color Difference

(Graphical/Tabular).

b) Strength: To see the strength of a Sample.

c) Indices: To see Whiteness, Yellowness, and Brightness of

White colored samples.

d) Combined Output: To see measurements of samples in

terms of Color Difference, Strength etc.

a) Selection of dyes [10]: Dye class, no of colourants

(covering red, blue, green & others eliminating duplicate or

near duplicate colours).

b) Preparation of Textile Sample:

i. Desizing, scouring & bleaching should be done to achieve

standard whiteness.

ii. Arrangement of sample at a time from one batch so that

no variation arise in basic material.

c) Dye – purity, Dye exhaustion factors etc are important in

all cases.

d) Calibration dyeing using selected dyes with different

concentration:

All dyeing conditions are to be same for whole set of dyeing. For

each dye, 8 – 10 concentration is selected for dyeing after finding

maximum shade depth to be used (say it is 3-5%). Then from 0.1-

3% or 4% or 5% shade depth, 8-9 shades are to be produced for

preparation of database. Accurate weight is important in each case

of dye.

e) Measurement of Reflectance & K/S Value for Samples

Dyed Under Calibration Dyeing:

i. A blank sample is to be always taken and No over drying /

scratching should occur.

Table 3: Database of Colour Strength and related colour parameters of bleached jute fabrics dyed with three Direct Dye.

Lupinepublishers-openaccess-journals-Textile-Fashiondesigning

ii. Before final entry of calibration dyeing [6] data bases for

recipe formation , acceptable colour difference (DE ) tolerance

, tightness/darkness tolerance , limit of k/s deviation (CV%

) from number of scan & their (K/S) measurement , limit of

degree of degree of acceptable levelness for calibration dyeing

, degree of linearity of the concentration of dye vs. K/S curve

etc. should be predetermined from large number of samples for

particular substrate & dye class separately considering also the

customer’s or industries acceptance by human precipitance . An

Example of Data base prepared for Direct Dyeing on Bleached

jute fabric is shown below in Table 3.

a) Measurement of tristimulus values, reflectant at maximum

absorbance wave length or K/S measurement of transmitants

or absorbance from dye liquor.

b) Calculation of colour difference by CIELAB or Hunter Lab

equation of comparison of colour

strength & colour space diagram co-ordinates etc. The shade

sort represents three-dimensional deviation from a central

point in Redness & Greenness (a), lightness Darkness (b) and

yellowness and Blueness.

c) Easier computerized colour matching recipe production

with least cost & least metameric recipe with the previously

entered set of practical dye information.

d) Batch correction or auto correction of shades.

e) Prediction of colour matching recipe utilizing dye waste

liquor.

f) Prediction of quality of incoming dyes with the help of

transmittance software.

g) Prediction of whiteness or yellowness of bleached textile

in difference standard scales like CIE, Hunter Lab, ASTM-E-313,

Stans by etc.

h) Prediction of optical brightening agent’s efficiency

utilizing the CCM device with or without UV light.

i) Quantitative prediction colour fading behaviour – instead

of conventional grey scale application.

[6] The major reason of interest for adopting computerized

colour matching technique in mill is dye cost reduction & better

& quicker match. But a very small dye house, when total dye

consumption per year is very less, the adoption of CCM technique

may not be cost viable. Dye cost saving is usually in the range of 10

% to 25 %.

a) Reduction in dye stuff cost by least cost recipe. (Savings

may be 10 – 25 %).

b) Less dye inventory & number of alternate recipes for

avoiding unavailable dye.

c) Better match (Least metameric & Least cost) with

quantitative colour difference within tolerance & shade sorting

as per international market system, especially for exports.

d) Technical analysis of extent of match, degree of

metamerism, measurement of colour difference, whiteness &

yellowness index, measurement of bleached textiles etc. are

possible & also quality of incoming dye can be assured.

e) New shade development & number different light

shades on sample fabric are possible to produce only with the

instrumental colour matching.

f) Perfect colour matching of blended textiles is also made

easier.

g) Even with the change of substrate, a nearly match

prediction is possible, knowing some basic data for the

substrate.

a) Calibration Samples: The dyeing conditions in the

laboratory & productions differ in various respects viz, M: L

ratio, auxiliaries dyeing machines, exhaustion of dye etc.

b) Change of Substrate: It is very difficult to maintain the

characteristic properties of the substrate as regards the quality

of the fibers, yarn structure, fabric construction, colour, heat

setting, pretreatments, etc. which in turn changes the dye

uptake properties of the fiber. It is particularly impossible to

prepare the basic calibration data under all such variation.

c) Change in Dyestuff: Every incoming batch of the dye stuff

requires testing for tonal & strength changes which needs

recalculation of the recipe.

d) Recipe suggested by the computer are based on minimum

colour difference within given tolerance & least metamerism in

CIELAB scales. But always CIELAB tolerances do not confirms

exactly with human perceived colour difference.

e) Light sources used to test the match, are CIE standardized

simulated standard illuminant, which are not same in all

respect with natural sunlight. Instrumental accuracy may be

checked periodically.

f) The kubelka-munk equation & optical theory of computer

colour matching do not apply strictly on extra glossy or

fluorescent samples. In K – M equation the air scattering

& interaction of air & textile substrate is not considered &

therefore the K/S vs. concentration of dyes curves deviates from

linearity. For practical purpose, the curve required to modify

to make it linear to apply the above theory and therefore the

recipe obtained from computer deviates from actual.

a) For quality control of dyed textiles.

b) For Evaluation of Quality of dyes supplied.

c) Role of dyeing additives by measuring colour yield.

d) Efficiency of optical brighteners by UV analysis.

e) Soil removal efficiency of surfactants by measuring

Reflectance value.

f) Measurement of whiteness/yellowness/brightness index

etc.

The practical aspects of data base generating match generation

using a data base, setting up proper DE or multiple colour tolerance

& above all accurate spectrophotometer measurement depends on

following factors.

a) Level / Un level dyeing (Usually Less than 5% CV of K/S

Value is taken as level dyeing for textiles).

b) Back ground opaqueness of the sample (No. of Fold are to

be kept Constant.

c) Sample orientation (warp wise or weft wise vertical

measurement may differ colour value).

d) Sample surface structure/texture (Any Treatment before

dyeing may change surface texture and scattering value and hence

may change k/s value also).

e) Two sideness (Colour value in one face of fabric may

sometimes differ from other face).

f) Slubbing/Defects in fabric (Any defect of the fabric on

surface may cause colour variation).

g) Dull shade / Fluorescent colour & bright shade etc.,

sometimes behave differently.

The success of computer colour matching depends on the

accuracy with which the optical data file is prepared. The theory

of computer aided colour matching mainly depends on linearity

of K-M function with dye concentration. In fact, this linear relation

doesn’t exist. The deviation from linearity of K-M function with dye

concentration may be due to inherent deficiency in theory, nonlinear

uptake of dye with increase in concentration by the fibre

and/or the interaction between dyes during the dyeing process.

Saha & Gandhi [2] stated that the function of reflectance which

gives approximate linear relation with dye concentration as per

Kubelka and Munk function, but practically sometimes all dyes

do not exhibit satisfactory linear relation in a plot between K/S

value vs dye concentration, Therefore, with the help of number

of empirical modifications to the equation of K-M functions (K/S

value) this linearization is to be done for effective match prediction.

In many cases of dyed textiles, the deviation from linear

relationship between reflectance and concentration is considerably

high due to variation in exhaustion of dye at higher percentage

of dyeing and also for many other reasons. For such case the

absorption co-efficient of dye is calculated at about eight -ten

level of dyeing and linearization is to be done either ommitinmg

certain concentrations or by repeated dyeing and then to be stored

in the computer memory as database for use of determining

colour matching recipe /formulations, with prescribed standard

tolerances of colour differences (DE, DL, Da, Db values under

standard illuminants).

At the end, it may be said that after necessary training and

guidance, this Instrument of CCMP system can be used successfully

for its versatile use including Computer Aided Colour measuring

and Matching purpose which needs to be implemented in all dye

houses of either all textile dyeing or jute dyeing to derive the above

said benefits of precession matching and customer satisfaction.

  1. Trottman ER (1995) Dyeing and Chemical Technology of Textile fibres

    Charles Griffin & Co. Ltd, London.

  2. Shah HS, Gandhi RS (1990) Instrumental Colour Measurements &

    Computer-r Aided Colour Matching for Textiles, Mahajan Book

    Distributers, Ahmedabad, India pp. 370.

  3. Valia A T (1990) Print in India (10): 53-58.
  4. Davidson H R, Hemmendinger (1963) J Soc Dyers & Color 79: 577-585.
  5. Patil SM, Shelke V (1990) Thakur Mrinal, Man-made Textiles in India (2):

    53-58.

  6. Samanta AK (1993) Textile Trend (10): 37-47.
  7. Park RH, Stearns EI (19444) J Opt Soc Amer 34.
  8. Allen E (1966) J Opt Soc Amer 56:1256-1299
  9. Patwardhan SS, Wool Res Asson (1977) Thane, India.
  10. Randall D, Stutts T (1988) Amer Dyestuff Reporter, (8) 44-46.

文章来源:https://lupinepublishers.com/fashion-technology-textile-engineering/fulltext/fundamentals-and-applications-of-computer-aided-colour-match-prediction-ccmp-system.ID.000148.php

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