Skip to main content

Uster Evenness Tester Report Analysis (USTER TESTER 6)

Spun yarn produced in the conventional spinning processes, even under the best conditions, has a certain minimum irregularity. Because: (i) the number of fibers in the yarn cross-section is not constant, and (ii) in contrast to synthetic staple fibers, natural fibers have variations in their fineness. So, ultimately, yarn thickness varies even when the number of fibers in the cross section remains the same. Uster Evenness Tester is used to determine the index of irregularity of a yarn. Following the capacitive measuring principle, it measures the capacitance of the materials that pass through the capacitor electrodes of the tester. 

Figure 1: Irregularity measuring principle of an evenness tester.

Uster tester mainly determines the mass variation of fiber assembly using the capacitive measuring principle. This mass variation provides a mass diagram that is valuable for the detection of the following faults of a yarn.

  • Random & seldom occurring events
  • Long-term variations
  • Thick and thin places
  • Slow changes in the mean value
  • Periodic mass variation of wavelengths longer than 100 m (can be detected by spectrogram)

Scope of Uster Evenness Tester:

It can measure the irregularity of fiber assembly in 3 different forms,

  • Sliver
  • Roving
  • Yarn

Report Analysis:

Figure 2: Example of Uster Evenness Tester Report

Uster Evenness Tester report provides the following data on a fiber assembly:

i)                U% (Unevenness %)

ii)             CVm% (Coefficient of mass variation) at different cut length

iii)           Imperfection count/km (Thick, thin & neps count) at different sensitivity thresholds (i.e., -30%, -40%, etc. for thin places, +35%, +50%, etc. for thick places and +200% for neps)

iv)            Relative count variation

v)              H, sh (Hairiness)

Before we summarize what these terms/parameters represent and what are the effects of these fiber assembly characterization measurements in further textile processing, let's talk about the statistical evaluation system of these terms/ parameters.

i)             Mean value: The average value found for a specific term.

Calculated by,

ii)          S (Standard deviation): A standard deviation (or σ) is a measure of how dispersed the data is in relation to the mean. Low, or small, standard deviation indicates data are clustered tightly around the mean, and high, or large, standard deviation indicates data are more spread out. Calculated by,


iii)        CV (Co-efficient of variation): Co-efficient of variation, defines the level of dispersion of single test data around the mean value. It is generally expressed as a percentage. Calculated by,

Where s is the standard deviation of the dataset.

iv)     Q95%(Confidence range of the mean): In textile testing, it is generally considered with a statistical significance ‘S’ of 95%. This means that the real mean value of the population will lie within this confidence range with a degree of error of

Α=100% - S =100% - 95% =5%

                    The limit of confidence range can be calculated by,

                                        Q95%= `x ± k.s

Where ‘s’ is the standard deviation & ‘k’ refers to the value (t/√n), where ‘t’ is called the factor of data distribution. The value of ‘k’ depends on the sample size ‘n’ according to the table mentioned below:

Sample size, n

5

10

20

30

50

100

Factor, k

1.24

0.715

0.467

0.373

0.248

0.198

For example, in the 2nd column of Figure 2, the mean of U% is 9.08, and Q95 of U% is 0.15. It can be expressed as, Q95%=9.08±0.15. It indicates that there is a 95% chance that the mean value of U% will lie between 8.93%~9.23%.

v)             Max. & Min.: Shows the maximum and minimum value of the dataset.

vi)        USP™ (Uster Statistics percentile): Uster statistics is the only established benchmark for the worldwide textile industry. It is a comparison of test data with the existing practices throughout the world. USTER® STATISTICS percentile level express how many spinning mills worldwide can produce yarn at that specified level or batter.

Figure 3: USTER Statistics percentile shows the comparison of CVm% of different counts of yarn.

Now let’s discuss about the provided test data by Uster Evenness Tester.

i)                U%(Unevenness%): Measurement of mass unevenness by the help of the irregularity.

Figure 4: Yarn unevenness

The effects of yarn unevenness on subsequent textile processing are as follows:

      • The uneven yarn should have more thin regions than the even one as the result of irregularity since the average linear density is the same. Thus, an irregular yarn will tend to break more easily during spinning, winding, weaving, knitting, or any other process.
      • Fabric knitted from yarn with high unevenness possesses a high chance of getting GSM variation in knit fabric.
      • More regular the yarn, better will be the appearance and aesthetic value of the product. As a result, better sale value can be achieved.
      • When the yarn evenness exceeds certain limits, it will result in a cloudy fabric appearance.
      • Fabric defects and rejections are critically influenced by irregularity of yarns. Defects such as streaks, stripes, barre, or other visual groupings develop in the cloth. Such defects clearly apparent to eye and are usually compounded when the fabric is dyed or finished, as a result of  the twist variation accompanying them.
      • Other fabric properties such as abrasion or pill- resistance, soil retention, drape, absorbency, reflectance, or luster may also be directly influenced by yarn evenness.

ii)   CVm% (Coefficient of mass variation) at different cut length: Measurement of mass unevenness with the help of the coefficient of variation at available cut lengths of 1, 3, 10, 50 and 100 m. This term also represents the unevenness of yarn from the point of view of mass.

Larger cut lengths provide lower mass variation because of normalization.

 

The effects of yarn unevenness of mass on subsequent textile processing are as follows:

          [Same as U% as it is also a measure of yarn unevenness]

Nowadays, CVm% is preferred to U% in modern statistics as the measure of yarn unevenness.

iii)       Imperfection count/km: Counting of thin places, thick places and neps for several sensitivity levels in yarns:

– Thin places: -30%, -40%, -50%, -60%

– Thick place: +35%, +50%, +70%, +100%

– Neps: +140%, +200%, +280%, +400%

– Total imperfections available for standard (ring/air-jet yarn -50%, +50%, +200%, and open-end/rotor yarn -50, +50, +280%)


Effects of yarn imperfection of mass on subsequent textile processing are as follows:

      • Thick and thin mark on knit fabric can be introduced due to imperfection.
      • A higher number of imperfections (thick, thin, and neps) reduces the smoothness of the fabric.

Figure 5: Thick thin mark on fabric

      • Neps can cause undyed or unprinted spots during dyeing or printing. 
      • Higher imperfection in fabric can cause uneven dyeing of fabric. 
      • Sometimes yarn with higher neps contain immature fibres which are usually weaker than normal fibres, which can effect the strength and dye uptake% of a fabric.

iv)        Relative count variation: Percentage count variation of the test material between single tests in a sample, with reference level to selectable material length.

v)        H, sh (Hairiness, Standard deviation of hairiness): H is the measure of yarn hairiness that measure the length of protruding fibers within the measurement field of 1 cm length.

On the other hand, ‘sh’ stands for the measure of hairiness variation of yarn at different cut length of 1, 3, 10, 50 and 100 m.


The effects of yarn hairiness on subsequent textile processing is as follows:

      • Essentially, the hairiness of the yarn is one of the factors that determines the quality of yarn. The higher hairiness of the yarn results in the lower quality of the yarn. The presence of the lint in yarn creates a bad appearance in the fabric. According to the report of the Uster standards, 15% of the faults in fabrics are due to the hairiness of yarns. Creation of unwanted strips in the direction of the wraps and wefts is due to the high hairiness of the yarn or its variation. Periodic changes in the yarn’s hairiness led to the formation of alternating thin and thick bands in fabric.
      • When a yarn with high degree of hairiness is used in fabric wraps, long protruded fibers of yarns cause engagement of the yarns and cling to each other. Such a condition prevents the easy separation of the fabric warps at the creation of sheds, and thus increases the number of tears in the warp threads and adds to the fabric imperfections.
      • The use of yarns with high degree of hairiness in sewing process increases thread breakage.
      • The presence of high-tufted yarns in the fabrics causes printing of the lines and curvatures of the design pattern cannot be accurately applied to the fabrics and lead to an interference of patterns.
      • The higher the yarn’s hairiness, the higher the tendency to the hairiness of the fabric, which causes unseemly appearance in the fabric.
      • Increasing the hairiness of the yarn increased air resistance around the spinning yarn balloon. According to conducted researches, it has been estimated that with increasing the yarn hairiness, the friction coefficient increases. Consequently, the amount of air resistance increases during the revolving of yarn balloon in the circular spinning machines. Studies have shown that by singeing of the excessive hairiness of the yarns, the air resistance reduces up to 26% for cotton yarns and up to 33% for wool yarns. In general, a practical result excessive hairiness of yarns is elevated energy consumption.
      • Higher value of ‘Sh’ indicates higher variation of hairiness is present on the fabric. It can cause uneven dye uptake by fabric.
      • The hairiness of the yarn has a positive effect on the comfort feeling of the fabric texture and its warmness. This fact can be easily realized from the comparison of the produced yarns from filament fibers and discontinuous fibers that have the same size and material.

Figure 6: Another example of a Uster Evenness tester report

References

  1. uTESTER6 The Total Testing Center™. (n.d.). Technical data.
  2. Uddin, A. J. (n.d.). Process control of spinning: Part B.
  3. Imtiaz, S. (n.d.). Yarn unevenness and its impact on quality.
  4. Booth, J. E. (n.d.). Principles of textile testing.
  5. Nishi, S. I. (n.d.). Fiber and yarn testing: Part A.


Comments

Post a Comment

Popular posts from this blog

Sustainability in Textile Manufacturing: Deepening Insights into Bangladesh’s RMG Sector

  The Ready-Made Garment (RMG) industry in Bangladesh has charted remarkable export growth—USD 31.5 billion in 2021, accounting for over 80 % of national exports—yet it faces acute resource constraints, environmental hazards, and social equity challenges. The sector’s average water footprint (125–250 L/kg of fabric) and carbon intensity (~1.5 kg CO₂e/kg) underscore the imperative for systemic sustainability interventions that transcend compliance and embed circularity at every stage of production [1], [2], [13]. Bangladesh’s textile clusters lie within some of the world’s most water-stressed basins. Traditional dye houses discharge effluents with biochemical oxygen demand (BOD) upwards of 500 mg/L, far exceeding national standards. Recent pilots deploying digital flow meters and real-time water quality sensors have achieved 35 % reductions in freshwater intake and a 50 % drop in effluent loads by optimizing batch scheduling and implementing closed-loop rinse systems [1], [11]. Sc...
Post a Comment
Read more

Piezoelectric Effect and Piezoelectric Materials

Piezoelectricity is a reversible phenomenon wherein certain materials generate an electric charge under mechanical stress and deform under an electric field. This article explores the core principles of piezoelectricity, commonly used materials, and characterization methods. Emphasis is placed on practical applications ranging from sensors and actuators to biomedical and nanotechnology fields. The discussion integrates both traditional piezoceramics like PZT and emerging nanostructures, underscoring their roles in modern engineering and science. Piezoelectric materials convert mechanical stress into electrical energy and vice versa. This unique property finds use in a wide range of technologies, including oscillators, actuators, and medical sensors. The phenomenon is inherent in certain crystals, ceramics, polymers, and biological materials. Fig. 1: Direct and converse piezoelectric effect Piezoelectric Materials Several materials exhibit strong piezoelectric behavior: Lead Zirconat...
Post a Comment
Read more

USTER AFIS (Advanced Fiber Information System) Report Analysis

The unique measuring system of the USTER® AFIS counts every fiber, neps and trash particle one by one. The fiber individualizer ensures single fiber measurement, with a gentle opening of the test material. The USTER® AFIS is the standard system for nep measurement, recognized worldwide, and used from cotton ginning to yarn manufacturing. It measures various fiber characteristics such as fiber length, maturity, trash, and nep content. Measuring Principle The measuring principle of USTER AFIS is different from that of the USTER TESTER so far as the USTER AFIS is an optical system. (Figure-1) A fiber sample of 500 mg (making into a 30 cm thin sliver form) is inserted into the fiber individualizer unit that separates the specimen into three main components: Lint: Fiber, short fibers, neps, seed coat neps. T rash & dust: Trash, dust, fiber fragments, very large seed coat with little or no attached fibers. Figure 1: Measuring principle of AFIS Report Analysis: Figure 2: An exa...
Post a Comment
Read more