Optimizing Color Control Through the Supply Chain

David Hinks, Associate Professor, Polymer and Color Chemistry, NCSU
Renzo Shamey, Assistant Professor, Polymer and Color Chemistry, NCSU
Lina Cardenas, M.S. Student, Polymer and Color Chemistry, NCSU
Nancy Cassill, Professor, Textile and Apparel Technology Managment, NCSU

In the textile industry, effective color control and communication between designer, dyer and retailer are critical to obtaining high product quality and cost efficiency. Color control should be carried out throughout the supply chain with the aim to deliver the right color to the customer in a short period of time. Ideally, the color of an object perceived by an observer (e.g. a consumer) is the same as the color specified in the original product design. However, there are a large array of problems in communicating and obtaining the right color in the textile supply chain. For instance, variability in lighting may mean that the color of a product in a store is perceived significantly differently from that originally intended by the designer, despite a high level of color control during the design and production of the product. Also, the background viewing environment may have a significant effect on the perceived color.

Some of the large US retail chain stores have a product development cycle greater than 40 weeks, from concept to consumer. Global sourcing, compounded competition, and increased specification requirements are significant challenges for the industry. In this respect, one of the main problems is the effective communication and control of color.

The National Textile Center is currently funding a project that aims to optimize the control of color throughout the textile supply chain . The goal of the research is to develop an accurate and precise integrated color control system that can be implemented through the US textile manufacturing complex. The research is the result of collaboration between NC State and Clemson University faculty and several US textile manufacturers and retailers.

Any significant advance in color control needs to improve color assessment, color measurements, color difference calculations and lighting control. The control of color is commonly achieved both via visual assessment and color measurement. Visual assessment of color, even when conditions are closely controlled, is open to criticism due to its subjectivity and observer variability. The models that predict color, color difference and color variation as a result of changes in conditions, are also not optimum. In addition, if digital color communication is to be used, the methodology must first be clearly understood. In practical visual assessments it is important to ascertain the variability in observers using highly controlled conditions of observation. Factors that are believed to lead to significant inconsistency include the number, gender, and experience of observers in assessing color, as well as methods of judgment (e.g., geometric gray scale or gray anchor pair) and mode of data analysis.

In the first stage of this study, a number of methods of assessing differences in color between two textile samples has been developed to determine the effect of key variables on observer repeatability. A pilot study involving a set of naïve as well as expert observers (i.e. people that work in color quality control) has been carried out. Results, which will be presented at IS&T's Third European Conference on Colour in Graphics, Imaging, and Vision in Leeds, UK, in June 2006, will determine the statistical significance, if any, of the role of observer training or industrial experiences in the visual assessment process. The data developed in this research will be utilized to quantify the variability in color control and improve the current mathematical models used to correlate visual assessment of color difference with predictive models. The use of digital communication throughout the supply chain is a smart path to reducing time and costs, providing the ability to create a more dynamic interaction between processes and associated personnel.

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Last Site Revision:
February 2, 2006