Based on the silk fabric specifications database, the paper proposes two technological parameters of selvage tightness coefficient and selvage warp density coefficient, and realizes the quantitative relationship of corresponding parameters between selvage and fabric. By making use of thousands data of silk products in the silk fabric specifications database, corresponding programs are wrote to achieve the automated numeration of various selvage parameters .Then the paper discusses three typical silk fabrics which contains eleven subclasses and analyses the distribution of the two parameters, with the comparison of selvage parameters in sub-categories of the same categories. The conclusion can provide a theoretical basis for the silk fabric design and production.
Based on the current color fastness standard of textiles at home and abroad, this paper gives a comparative analysis of the testing standard of related indicators, discuss the major color fastness of textiles including color fastness to water, to perspiration, to rubbing, to laundering. The quantified data of the sample test results show that there are some differences among the test methods, the equivalent of quantitative values and the requirements of indicator in GB, ISO, AATCC.
On the basis of silk fabric product specifications, making use of programming software to deal with product information, complete the complicated process calculation, realize the connection and running of products information database with the front desk inquiry calculation software. The system can achieve the number of all kinds of machines by automatic accounting according to the requirements of the design, and realize variables to be automatically selected such as the spindle number, efficiency, working hours and linear velocity. Automatically plot and analyze the variation trend of mechanical number in different fabric situation when the number of loom or annual output equality variation. The system contribute to production manager configure the process equipment rapidly and estimate the production ability.
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