Industry Innovation: Use Fiber Properties To Optimize Product Quality

Since 1957, the famous USTER ? STATISTICS benchmark has always been one of the important sources of textile fiber and yarn quality data. Latest USTER ? STATISTICS 20181 provides the latest data categories, which is expected to further promote quality improvement.

　　USTER ? The value of STATISTICS has been recognized globally, enabling yarn producers and their trading partners to objectively compare their quality levels against global market standards.

At USTER ? Two of the quality characteristics introduced by STATISTICS 2018 for the first time are to deal with the changing market demand by dealing with fiber characteristics 2. According to these results, benchmarking will promote spinning mills to further improve their yarn quality.

　 Fiber elongation

Compared with the fiber length, the elongation of cotton fiber depends more on the cotton type. The fiber elongation and fiber toughness jointly affect the yarn elongation, so the yarn processing performance is usually better when the elongation is higher. Therefore, in the future USTER ? It is obvious that fiber elongation category should be added to STATISTICS.

The analysis of USTER database shows that the correlation coefficient between fiber elongation and yarn elongation of combed cotton ring spun yarn is 85%. Although twist coefficient and yarn production speed also have a great impact on yarn elongation, the high yarn elongation actually comes from the fiber itself.

　　 Difference between seed neps and fiber neps

　　USTER ? The difference between fiber neps and seed neps in STATISTICS 2018 stems from market observations. Previously, only the total number of neps was considered.

The total number of neps is the sum of fiber neps and seed neps. High nep count indicates rough ginning, low maturity, and poor maintenance during mechanical harvesting and ginning. Today's ginners are increasingly focusing on productivity rather than quality. At the same time, ginners have not been upgraded to accommodate the increase in cotton production. This indicates that for spinning mills, cotton should now be evaluated more accurately, which can be achieved by evaluating fiber neps and seed neps separately. This more detailed analysis has the following new benefits.

First, the factory can optimize cotton blending to manage specific neps. It can also optimize specific nep removal efficiency. The spinning mill can also more accurately predict the degree of white spots on the fabric after yarn dyeing. A large number of fiber neps and a high proportion of immature fibers will cause these white spots. By analyzing the degree of fiber neps in the cotton blending stage, the factory can adjust the process flow accordingly, for example, focusing on reducing fiber neps in the carding process.

When using USTER STATISTICS 2018, it is recommended that the spinning mill adjust the settings of the carding machine, compare the sliver data with the fiber nep treatment chart, and benchmark the data of other factories. Combined with maturity monitoring, spinning mills can avoid or reduce white spots. If it is found during processing that the yarn can be used for other purposes, for example, bleached white T-shirts, in this case, immature fiber neps have little impact.

　　 summary

Fiber elongation and neps of fiber and seed chips are just two examples to illustrate the importance of following industry trends. Growing customer demand in a competitive market means that every textile manufacturer should use USTER ? The global quality benchmark provided by STATISTICS maximizes optimization.

　　 About USTER

Through USTER ? STATISTICS global benchmark data, USTER Technologies provides common standards for yarn manufacturers and buyers, so that manufacturers at each stage of the textile chain can be sure that the yarn will fully meet their needs. For yarn producers, USTER ? STATISTICS is a unique indicator of factory processes and yarn quality standards based on recognized international data. Since 2018, USTER ? STATISTICS is available as a mobile application that can be used on personal computers and all mobile devices.

About the author:

David McAlister is the Fiber Test Product Manager at Uster Technologies. He has more than 30 years of experience in the industry, providing services to some major organizations in the industry in leading manufacturing, research and product development fields. Mr. McAlister's experience covers all aspects of greenfield yarn manufacturing start-ups, operation management, fiber quality and yarn production research, as well as the development and launch of new products.