An Overview of USTER CLASSIMAT

Last Updated on 26/01/2021

An Overview of USTER CLASSIMAT

Bhavdip Paldiya
Dept. of Textile Technology
Sarvajanik College of Engineering & Technology, Surat, India
Email: bhavdipk9009@gmail.com

USTER created a numeric value to describe the level of yarn unevenness, the so-called U%, deriving from the German word ‘Unregelmässigkeit’, which means irregularity. This was followed by the first USTER standards in 1957, which provided classification of yarn quality into different levels, today referred to as the USTER® STATISTICS percentile levels.

With the introduction in 1960 of the first automatic yarn clearer, the USTER® SPECTOMATIC, spinners had a means of controlling the quality of yarns in the production process.

But spinners were still challenged to find a way of using data gathered in the laboratory to optimize the settings of the in-process quality control capabilities of the yarn clearer. The solution came with the launch of the USTER CLASSIMAT in 1968, which classified yarn defects into classes – the CLASSIMAT® values – with associated USTER® STATISTICS produced the following year. The classification of defects into classes provided the means for spinners to optimize their yarn clearing and the users of yarn to specify the required quality levels.

HISTORY OF USTER® CLASSIMAT:
The introduction of the USTER CLASSIMAT 1 in 1968 revolutionized the checking and determining of yarn quality in production and commerce. The later models CLASSIMAT 2 and CLASSIMAT 3 optimized and extended the application possibilities. The USTER CLASSIMAT QUANTUM offers even more advanced classification possibilities.

The classification of yarn defects according to their size and length into 23 standard classes is used extensively to certify yarn quality, to help control spinning processes and to optimize yarn clearing at the winding stage. In the meantime, quality demands have increased enormously. A class of defects regarded as tolerable in the past is no longer acceptable today, because basic yarn quality has improved significantly over the years.

Fault classification based on the well-proven analysis of thick and thin places remains fundamental, but must now also cover critical parameters such as foreign-matter, count variation, periodic faults, unevenness and hairiness. Consistent quality has risen in importance as much as absolute quality and the monitoring of quality exceptions is crucial to control them.

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USTER CLASSIMAT 5 offers the most technically-advanced sensors and superior hardware to detect and eventually classify all types of defects. The unique USTER® sensor range has all the options covered:

The new capacitive sensor identifies both short and fine neps, as well as troublesome thick and thin places that previously could not be detected until showing up in the final fabric.
The latest foreign fiber sensor, using multiple light sources to locate and classify contamination in yarns, even separating colored fibers and vegetable matter in cottons and blends, to distinguish potentially non-disturbing materials from real defects.
A novel sensor combination, enabling polypropylene content to be detected and classified for the first time.
Unique range of advanced sensors covering every option for yarn defect classification
New capacitive sensor with enhanced detection capabilities
Foreign-matter technology, able to distinguish all colors and non-disturbing materials
Breakthrough in polypropylene detection, based on novel sensor combination
New mounting module, special guides and tension control, ensuring ultimate accuracy.

The appearance of seldom-occurring faults in a grey fabric depends on various items:

The cross-section of the fault compared to the mean value.
The length of the fault.
The count of the yarn.
The yarn density in the fabric.
The type of fabric (weaving or knitting).

The new features of the USTER® QUANTUM 3:

Yarn Body –The “yarn body” represents the nominal yarn with its tolerable, frequent yarn faults. Yarn body is a new yarn characteristic, and we know from the experience so far that the yarn body changes according to the raw material and the spinning process. By analyzing the shape of the yarn bodies out of different raw material varieties and process changes, we can discover pat-terns, and build up references. Based on the references, the operator can identify changes. The yarn body becomes always wider in the direction of the short yarn events, e.g. short faults occur more frequent. On the con-trary, the yarn body becomes smaller in the direction of the long yarn events the yarn body is a great tool to help finding the optimum clearing limits for thick places (NSL), thin places (T), yarn count deviations (C) and (CC).

The yarn body is composed of two parts:

Dark green area representing the real yarn body.
Light green area representing yarn body variations.

Since both dark and light green areas together constitute the yarn body, it is recommended that the clearing limit should not cut into the yarn body. If the clearing limit is laid within these green areas, the cuts will increase significantly and the productivity will be lower.

USTER CLASSIMAT 5:
Previous CLASSIMAT® generations used 23 different classes, giving good coverage of all detected faults. However, there has been enormous progress in yarn quality – yarns have become more even, with the result that smaller defects are now viewed as disturbing. These small faults can now be detected and classified by the USTER CLASSIMAT 5, extending the existing classification table to include a total of 45 classes. The USTER CLASSIMAT QUANTUM can be used not only as a tool in order to examine the yarns to be purchased for remaining disturbing thick places, thin places and foreign fibres but also as a sophisticated classifying system which can help the user to determine and set his own yarn quality standards.

Today, the selection of the right yarn for the right product is crucial for economic reasons. A continuous incoming inspection guarantees a constant satisfactory quality of the end product. In this respect, yarn clearing and classifying systems are playing a very important role. At the beginning of electronic yarn clearing, the setting of the clearing curve has been quite difficult and has required specialists.

In 1968, Uster Technologies launched an electronic system by the name of USTER® CLASSIMAT, which was a revolution in yarn clearing at that time. The purpose of the system was the analysis of seldom-occurring or disturbing thick places and the setting of an optimum clearing curve on the winding machine to eliminate the really disturbing yarn faults and to simultaneously keep the efficiency of the winding machine as high as possible.

For this purpose, the yarn was classified into four length and in four thick place classes.

This analyzing system was not only used by spinners. The yarn buyers (traders, weavers, knitters, garment makers, etc.) also detected this system as a tool to separate yarns into first grade, second grade, etc., or to establish minimum conditions for the acceptance of yarns. As already mentioned, the first classifying system was introduced in the market in 1968. Therefore, the year 2008 marks the 40th anniversary of this analyzing tool. Figure 1 also shows that the system has been permanently improved in the past 40 years. Today with the USTER® CLASSIMAT QUANTUM generation, the cleared and uncleared yarn can be checked. The classification of thick and thin places, neps and foreign fibres in the yarn can be fulfilled.

This system also helps the user in determining the optimal limits for yarn clearing, in analysing new material, and supports with experience values, which can be used for benchmarking and evaluation.

Zellweger Uster AG, a textile instrument manufacturer based in Switzerland, has produced generations of evenness testing instrument for rapid measurement of the evenness of various fibre assemblies. The latest is the Uster Evenness Tester 4, although its predecessor (Uster Evenness Tester 3) is still widely used.

Uster Evenness Tester :
It measures mass variations along the length of a fibre assembly. It is based on the capacitance principle. The two capacitors detect the mass variations or weight per unit length variations of the fibre assembly running between them. These variations are transformed into a proportional electrical signal. The signal processing unit will process this signal, as well as other useful information concerning the mass variations.

The key quality attributes listed for these yarns are:

Yarn count variation (between bobbins or packages)
Mass variation (U% and CV%)
Imperfections (thick and thin places, neps)
Uster Hairiness Index
Tensile properties (strength and elongation).

Conclusion
It is well-known that the yarn quality is very important for the quality of the end product. Weak places, for example, mainly affect the productivity (machine stops caused by end breaks) whereas coarse yarn faults in woven or knitted fabrics result in costly rejects. Today, the selection of the right yarn for the right product is crucial for economic reasons. A continuous incoming inspection guarantees a constant satisfactory quality of the end product. In this respect classifying systems are playing a very important role. For example many of the foreign fibre problems are only detected after finishing, and the spinner is finally made responsible for the damage. For this reason, the sooner they are detected, the lower the costs and the better the quality. The costs and claims due to foreign fibres can be prevented by setting up a quality management system to eliminate or minimise the number of foreign fibres in yarns.

Within the scope of a modern quality assurance program it is now possible that test reports, which serve as a quality guarantee for the observance of supplier agreements or certificates, are requested with every yarn delivery. As a result of 40 years of continuous experience in yarn clearing and classification, the USTER CLASSIMAT QUANTUM can be used not only as a tool in order to examine the yarns to be purchased for remaining disturbing thick places, thin places and foreign fibres, but also as a sophisticated classifying system which can help the user to determine and set his own yarn quality standards.

Reference: https://www.uster.com

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Mazharul Islam Kiron

Founder & Editor of Textile Learner. He is a Textile Consultant, Blogger & Entrepreneur. He is working as a textile consultant in several local and international companies. He is also a contributor of Wikipedia.