Sample Conditioning for Digital Color Communication

Sample conditioning is a key element for measurement repeatability as variations in temperature and moisture content can contribute to variations in measurement data, but not all fabrics and colors respond in the same way to these environmental variations.  The variety of colors and number of fabric types typically produced and evaluated by textile manufacturers and retailers excludes the possibility of occasional control of relative humidity and temperature for specific colors or fabric types.  Instead, environmental conditions must be specified and continually controlled so as to minimize color variation for all samples to be evaluated.  This is especially significant when samples are measured at various locations globally where environmental conditions may vary dramatically.

 

ASTM guidelines for conditioning of textile samples are detailed in ASTM standard D1776-98 “Standard Practice for Conditioning and Testing Textiles”.  This standard specifies a temperature of 21 +/- 1° C and 65 +/- 2% relative humidity (RH) for the conditioning of textile samples.  A series of experiments was performed using 100% cotton standards to determine the effects of variations in temperature and relative humidity on associated color differences.  The following tables detail the DE CMC (2:1) color differences in D65/10 between selected experimental samples at the stated conditions and the standard conditioned to the ASTM recommended values of 21°C and 65% RH.  The experimental data in Table 4 was generated for variations in relative humidity while holding temperature constant, the experimental data in Table 5 was generated for variations in temperature while holding relative humidity constant, and the experimental data in Table 6 was generated for variations in both temperature and relative humidity.  The last column of Tables 4 and 5 represent the color differences between samples conditioned at the extremes of temperature or relative humidity.

 

Sample  40%  55%  60%  70%  75%  40%-75% 
4 Burgundy  0.24  0.10  0.05  0.06  0.18  0.42 
5 Bright Red  0.23  0.08  0.05  0.04  0.04  0.22 
6 Cherry Red  0.28  0.11  0.08  0.02  0.01  0.29 
11 Dark Orange  0.19  0.09  0.05  0.03  0.11  0.29 
13 Light Orange  0.10  0.04  0.02  0.03  0.06  0.12 
14 Dark Brown  0.11  0.05  0.06  0.05  0.06  0.16 
18 Dark Yellow  0.04  0.03  0.04  0.03  0.05  0.08 
21 Dark Green  0.15  0.09  0.04  0.07  0.14  0.29 
24 Light Green  0.11  0.05  0.04  0.05  0.05  0.16 
25 Jade  0.04  0.03  0.03  0.05  0.07  0.11 
26 Medium Blue  0.06  0.04  0.04  0.05  0.06  0.11 
28 Bright Blue  0.23  0.13  0.05  0.05  0.14  0.36 
29 Dark Navy  0.15  0.07  0.06  0.08  0.13  0.21 
32 Maroon  0.09  0.04  0.05  0.04  0.06  0.15 
33 Purple  0.13  0.07  0.03  0.05  0.08  0.20 
34 Light Violet  0.19  0.07  0.07  0.08  0.06  0.25 
38 Black  0.17  0.04  0.05  0.06  0.08  0.17 
39 Tan  0.05  0.03  0.04  0.05  0.07  0.10 

 

(Table 4.  Constant Temperature of 21°C with Variation in Relative Humidity)

 

Analysis of the data in Table 4 indicates that for the samples tested, variations in relative humidity do not have a significant impact on measured color difference when temperature is held constant until the humidity drops to 40% RH.  This represents a variance of 25% RH when compared to the standard relative humidity of 65%.  The final column, which displays the color differences between the samples measured after conditioning to 40% RH and the samples after conditioning to 75% RH represents a variance of 35% RH, and as expected the color differences continue to increase.  So while minor variations in relative humidity with constant temperature do not contribute significantly to color differences for the samples tested, larger variations in relative humidity contribute significantly to calculated color differences. 


 

Sample  15°C  25°C  30°C  35°C  15-35°C 
4 Burgundy  0.13  0.07  0.13  0.14  0.15 
5 Bright Red  0.09  0.03  0.38  0.36  0.29 
6 Cherry Red  0.08  0.03  0.37  0.36  0.28 
11 Dark Orange  0.05  0.03  0.10  0.14  0.09 
13 Light Orange  0.11  0.05  0.09  0.14  0.06 
14 Dark Brown  0.13  0.09  0.06  0.12  0.08 
18 Dark Yellow  0.23  0.09  0.07  0.18  0.06 
21 Dark Green  0.03  0.04  0.06  0.05  0.03 
24 Light Green  0.15  0.08  0.04  0.05  0.11 
25 Jade  0.16  0.12  0.09  0.07  0.14 
26 Medium Blue  0.11  0.06  0.10  0.03  0.11 
28 Bright Blue  0.04  0.05  0.04  0.03  0.02 
29 Dark Navy  0.11  0.07  0.17  0.13  0.24 
32 Maroon  0.06  0.04  0.05  0.02  0.07 
33 Purple  0.04  0.03  0.04  0.04  0.07 
34 Light Violet  0.04  0.03  0.13  0.17  0.16 
38 Black  0.19  0.15  0.12  0.18  0.10 
39 Tan  0.18  0.10  0.08  0.07  0.15 

 

(Table 5.  Constant Relative Humidity of 65% RH with Variation in Temperature)

 

Analysis of data in Table 5 indicates that for the samples tested, variations in temperature have a significant impact on measured color difference for some colors.  Within a normal office temperature range of 20-25°C (68-77°F) with constant humidity, the samples tested showed minimal color variation.  Elevated temperatures of 30-35°C (86-95°F) are more of a concern in a manufacturing environment where samples may be measured after being dried at high temperatures, in which case it is imperative that the samples be allowed to condition prior to measurement.  Higher temperatures are also a concern in manufacturing facilities where the spectrophotometer is not used in a climate-controlled area.  As with extreme variations in relative humidity, extreme variations in the temperatures at which standards and samples are measured will lead to even greater color differences.


 

 

Sample  25°C/35% RH  25°C/75% RH  30°C/35% RH  30°C/75% RH 
  Warm/Dry  Warm/Humid  Hot/Dry  Hot/Humid 
4 Burgundy  0.33  0.16  0.37  0.17 
5 Bright Red  0.20  0.16  0.74  0.27 
6 Cherry Red  0.32  0.13  0.88  0.25 
11 Dark Orange  0.20  0.09  0.39  0.10 
13 Light Orange  0.10  0.07  0.21  0.08 
14 Dark Brown  0.22  0.06  0.22  0.12 
18 Dark Yellow  0.17  0.04  0.17  0.04 
21 Dark Green  0.26  0.12  0.28  0.11 
24 Light Green  0.23  0.06  0.16  0.05 
25 Jade  0.13  0.07  0.05  0.09 
26 Medium Blue  0.13  0.06  0.19  0.08 
28 Bright Blue  0.46  0.13  0.39  0.14 
29 Dark Navy  0.12  0.13  0.21  0.18 
32 Maroon  0.12  0.06  0.18  0.06 
33 Purple  0.19  0.07  0.17  0.07 
34 Light Violet  0.20  0.03  0.46  0.04 
38 Black  0.34  0.08  0.21  0.13 
39 Tan  0.09  0.06  0.07  0.07 

 

(Table 6.  Variations in Both Temperature and Relative Humidity)

 

Analysis of data in Table 6 indicates that for the samples tested, variations in both temperature and humidity relative to recommended conditions of 21 +/- 1° C and 65 +/- 2% RH have a potentially significant effect on color differences.  This is especially true for the “Hot/Dry” conditions of 30°C and 35% RH, which, as stated previously, are typical of samples that have been dried in a manufacturing facility prior to measurement.  Each of the conditions tested are prevalent in different areas of the world during different seasons of the year, and it would not be unusual to have “Warm/Dry” conditions in a retailer’s office and “Hot/Humid” conditions where lab or production samples are being measured, confirming the need for sample conditioning throughout the supply chain in order to minimize these types of errors.


 

The Role of the Human Factor in Digital Color Communication

It is not enough to only control the instrument, the measurement technique, and sample conditioning in order to ensure that the right color is delivered to the customer.  In addition to control of these more mechanical elements, the contribution of the evaluator in terms of data interpretation and specification must be considered.  Even if all of the physical variables are controlled, data can still be interpreted incorrectly due to selection of the wrong standard, the wrong light source, or the wrong color difference formula.  Errors in any of these areas can result in an incorrect pass or fail decision for the sample being evaluated.  So in addition to attention to detail in sample measurement, there is the added responsibility to ensure the proper use of the software tools available to the evaluator and the proper interpretation of the color differences generated from digital color data.  Only then will the right product with the right color get to the consumer at the right time.

 

This is the third post in our Keys to Digital Color Communication series. You can read Ken’s previous posts on the topic,Keys to Reliable Color Communication” and “Sample Measurement Technique in Digital Color Communication”. 

 

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About Ken Butts:

Ken Butts