ASTM D 1230 TEST FOR FIRE RESISTANCE OF TEXTILE FABRIC


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SPECIFICATIONS/PROPERTIES REQUIRED FOR THE MEDITECH PRODUCTS AND THEIR TESTING


By: – T.Sureshram
Junior Scientific Officer, Department of Textile Physics,
The South India Textile Research Association, Coimbatore-14

Combination of textile technology and medical sciences has resulted into a new field called medical textiles. Medical textiles are one of the most rapidly expanding sectors in the technical textile market. Textile materials in the medical textile field gradually have taken on more important roles. The wide range of textile products used in the medical industry are classified in to four major segments namely non-implantable materials, implantable materials, extracorporeal devices and healthcare & hygiene products. This paper deals with the specifications/properties required and different types of test methods involved for evaluating the characteristics of the medical textile products.

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Testing Specification

STRUCTURAL, PHYSICAL, AND CHEMICAL CHARACTERIZATION


A number of methods are available for characterization of the structural, physical, and chemical properties of fibers. The major methods available are outlined in this chapter, including a brief description of each method and the nature of characterization that the method provides.

Optical and Electron Microscopy

Optical microscopy (OM) has been used for many years as a reliable method to determine the gross morphology of a fiber in longitudinal, as well as cross-sectional views. Mounting the fiber on a slide wetted with a liquid of appropriate refractive properties has been used to minimize light scattering effects. The presence of gross morphological characteristics such as fiber shape and size and the nature of the surface can be readily detected. Magnifications as high as 1,500X are possible, although less depth of field exists at higher magnifications. Scanning electron microscopy (SEM) can be used to view the morphology of fibers with good depth of field and resolution at magnifications up to 10,000X. In scanning electron microscopy, the fiber must first be coated with a thin film of a conducting metal such as silver or gold. The mounted specimen then is scanned with an electron beam, and back-scattered particles emitted from the fiber surface are detected and analyzed to form an image of the fiber. Transmission electron microscopy (TEM) is more specialized and more difficult to perform than SEM. It measures the net density of electrons passing through the thin cross sections of metal-coated fibers and provides a method to look at their micro-morphologies.

Elemental and End-Group Analysis

The qualitative and quantitative analysis of the chemical elements  and groups in a fiber may aid in identification and characterization of a fiber. Care must be taken in analysis of such data, since the presence of dyes or finishes on the fibers may affect the nature and content of elements and end groups found in a given fiber. Gravimetric and instrumental chemical  methods are available for analysis of specific elements or groups of elements in fibers. Specific chemical analyses of functional groups and end groups in 26 Tufted Carpet
organic polymers that make up fibers may be carried out. For example, analyses of amino acids in protein fibers, amino groups in polyamides and proteins, and acid groups in polyamides and polyesters aid in structure determination, molecular characterization, and identification of fibers.

Infrared Spectroscopy

Infrared spectroscopy is a valuable tool in determination of functional  groups within a fiber. Functional groups in a polymer absorb infrared energy at wavelengths characteristic of the particular group and lead to changes in the vibrational modes within the functional group. As a result of the infrared absorption characteristics of the fiber, specific functional groups can be identified. Infrared spectroscopy of fibers can be carried out on the finely divided fiber segments pressed in a salt pellet, or through the use of reflectance techniques. Functional groups in dyes and finishes also can be detected by this technique.

Ultraviolet-Visible Spectroscopy

The ultraviolet-visible spectra of fibers, dyes, and finishes can provide clues concerning the structure of these materials, as well as show the nature of electronic transitions that occur within the material as light is absorbed at various wavelengths by unsaturated groups giving an electronically- excited molecule. The absorbed energy is either harmlessly dissipated as heat, fluorescence, or phosphorescence, or causes chemical reactions to occur that modify the chemical structure of the fiber. Ultraviolet-visible spectra can be measured for a material either in solution or by reflectance. Reflectance spectra are particularly useful in color measurement and assessment of color differences in dyed and bleached fibers.

Nuclear Magnetic Resonance Spectroscopy

Nuclear magnetic resonance (NMR) spectroscopy measures the relative magnitude and direction (moment) of spin orientation of the nucleus of the individual atoms within a polymer from a fiber in solution in a highintensity magnetic field. The degree of shift of spins within the magnetic field and the signal splitting characteristics of individual atoms such as hydrogen or carbon within the molecule are dependent on the location and nature of  Fiber Identification and Characterization the groups surrounding each atom. In this way, the “average” structure of long polymeric chains can be determined. Line width from NMR spectra also can provide information concerning the relationship of crystalline and amorphous areas within the polymer.

X-Ray Diffraction

X-rays, diffracted from or reflected off crystalline or semicrystalline polymeric materials, give patterns related to the crystalline and amorphous areas within a fiber. The size and shape of individual crystalline and amorphous sites within the fiber are reflected in the geometry and sharpness of the x-ray diffraction pattern and provide an insight into the internal structure of the polymeric chains.

 Thermal Analysis

Physical and chemical changes in fibers may be investigated by measuring changes in selected properties as small samples of fiber are
heated at a steady rate over a given temperature range in an inert atmosphere such as nitrogen. There are four thermal characterization methods.

1. Differential thermal analysis (DTA)
2. Differential scanning calorimetry (DSC)
3. Thermal gravimetric analysis (TGA)
4. Thermal mechanical analysis (TMA)

In DTA, small changes in temperature (ΔT) in the fiber sample compared to a reference are detected and recorded as the sample is heated. The changes in temperature (ΔT) are directly related to physical and chemical events occurring within the fiber as it is heated. These events include changes in crystallinity and crystal structure, loss of water, solvents and volatile materials, and melting and decomposition of the fiber. Differential scanning calorimetry is similar to DTA, but measures changes in heat content (ΔH) rather than temperature (ΔT) as the fiber is heated; it provides quantitative data on the thermodynamic processes involved. In an inert gas such as nitrogen, most processes are endothermic (heat absorbing). If DTA or DSC is carried out in air with oxygen, data may be obtained related to the combustion characteristics of the fiber, and fiber decomposition becomes exothermic (heat generating). Thermal  radiometric analysis measures changes in mass (ΔΜ) of a sample as the temperature is raised at a uniform rate. It provides information concerning loss of volatile materials, the rate and mode of decomposition of the fiber, and the effect of finishes on fiber
decomposition. Thermal mechanical analysis measures changes in a specific mechanical property as the temperature of the fiber is raised at a uniform rate. A number of specialized mechanical devices have been developed to measure mechanical changes in fibers, including hardness and flow under stress.

Molecular Weight Determination

Molecular weight determination methods provide information concerning the average size and distribution of individual polymer molecules making up a fiber. Molecular weights enable one to calculate the length of the average repeating unit within the polymer chain, better known as the DP. The distribution of polymer chain lengths within the fiber provides information concerning selected polymer properties.
The major molecular weight determination methods include number average molecular weights (M¯ n), determined by end-group analysis, osmometry, cryoscopy, and ebullioscopy; weight average molecular weights (M¯ w), determined by light scattering and ultracentrifugation; and viscosity molecular weights (M¯ v), determined by the flow rate of polymer solutions. Since each method measures the average molecular weight of the polymer differently, the molecular weight values obtained will differ depending on the overall number and distribution of polymer chains of varying lengths present in the fiber. The differences in value between M¯ n and M¯ w provide measures of the breadth of distribution of polymers within the fiber. By definition the distribution of molecular weights for a given polymer will always be M¯ w > M¯ v > M¯ n.

Mechanical and Tensile Property Measurements

Mechanical and tensile measurements for fibers include tenacity or tensile strength, elongation at break, recovery from limited elongation, stiffness (relative force required to bend the fiber), and recovery from bending. The tensile properties of individual fibers or yarns are usually measured on a tensile testing machine such as an Instron®, which subjects  fibers or yarns of a given length to a constant rate of force or loading. The force necessary to break the fiber or yarn, or tenacity, is commonly given in grams per denier (g/d) or grams per tex (g/tex), or as kilometer breaking length in the SI system. The elongation to break of a fiber is a measure of the ultimate degree of extension that a fiber can withstand before breaking. The degree of recovery of a fiber from a given elongation is a measure of the resiliency of the fiber to small deformation forces. The stiffness or bendability of a fiber is related to the overall chemical structure of the macromolecules making up the fiber, the forces between adjacent polymer chains, and the degree of crystallinity of the fiber. Mechanical and tensile property measurements can provide valuable insights into the structure of a fiber and its projected performance in end use.

Specific Gravity

The specific gravity of a fiber is a measure of its density in relation to the density of the same volume of water, and provides a method to relate the mass per unit volume of a given fiber to that of other fibers. The specific gravity relates in some degree to the nature of molecular packing, crystallinity, and molecular alignment in the fiber. Specific gravity of a fiber will give an idea of the relative weight of fabrics of identical fabric structure, but of differing fiber content. End-use properties such as hand (feel or touch), drapability, and appearance are affected by fiber density.

Environmental Properties

Environmental properties include those physical properties which relate to the environment in which a fiber is found. Moisture regain, solvent solubility, heat conductivity, the physical effect of heat, and electrical properties depend on the environmental conditions surrounding the fiber. The uptake of moisture by a dry fiber at equilibrium will depend on the temperature and relative humidity of the environment. Solvent solubilities of fibers will depend on the solubility parameters of the solvent in relation to fiber structure and crystallinity. Heat conductivity, the physical effect of heating such as melting, softening, and other thermal transitions, and the electrical properties of a fiber depend on the inherent structure of the fiber and the manner in which heat or electrical energy is acted upon by the macromolecules within the fiber. Environmental properties are measured by subjecting the fiber to the appropriate environmental conditions and measuring the property desired under such conditions.

Chemical Properties

The chemical properties of fibers include the effects of chemical agents like acids, bases, oxidizing agents, reducing agents, and biological agents such as molds and mildews on the fiber, and light- and heat-induced chemical changes within the fiber. Acids and bases cause hydrolytic attack of molecular chains within a fiber, whereas oxidizing and reducing agents cause chemical attack of functional groups through oxidation (removal of electrons) or reduction (addition of electrons). Such chemical attack can change the fiber’s structure and possibly cleave the molecular chains within the fiber. Biological agents such as moths on wool or mildew on cellulose use the fiber as a nutrient for biological growth and, subsequently, cause damage to the fiber structure. Sunlight contains ultraviolet, visible, and infrared light energy. This energy can be absorbed at discrete wavelength ranges by fibers depending on their molecular structure. Ultraviolet and visible light absorbed by a fiber will cause excitation of electrons within the structure, raising them to higher energy states. Shorter ultraviolet wavelengths are the most highly energetic and give the most highly excited states. Visible light usually has little effect on the fiber, although its absorption and reflectance of unabsorbed light will determine the color and reflectance characteristics of the fiber. Infrared energy absorbed will increase the vibration of molecules within the fiber andwill cause heating. The excited species within the fiber can return to their original (ground) state, through dissipation of the energy as molecular vibrations or heat, without significantly affecting the fiber. Ultraviolet and some visible light absorbed by the fiber, however, can lead to molecular scission within the fiber and cause adverse free radical reactions, which will lead to fiber deterioration.

Heating a fiber to progressively higher temperatures in air will lead to physical as well as chemical changes within the fiber. At sufficiently high temperatures, molecular scission, oxidation, and other complex chemical reactions associated with decomposition of the fiber will occur causing possible discoloration and a severe drop in physical and end-use properties for the fiber.

Sampling


It is not possible or desirable to test all the raw material or all the final output from a production process because of time and cost constraints. Also many tests are destructive so that there would not be any material left after it had been tested. Because of this, representative samples of the material are tested. The amount of material that is actually tested can represent a very small proportion of the total output. It is therefore important that this small sample should be truly representative of the whole of the material. For instance if the test for cotton fibre length is considered, this requires a 20 mg sample which may have been taken from a bale weighing 250kg. The sample represents only about one eleven-millionth of the bulk but the quality of the whole bale is judged on the results from it.

The aim of sampling is to produce an unbiased sample in which the proportions of, for instance, the different fibre lengths in the sample are the same as those in the bulk. Or to put it another way, each fibre in the bale should have an equal chance of being chosen for the sample methods from the test lot.

• Test specimen: this is the one that is actually used for the individual measurement and is derived from the laboratory sample. Normally, measurements are made from several test specimens.

• Package: elementary units (which can be unwound) within each container in the consignment. They might be bump top, hanks, skeins, bobbins, cones or other support on to which have been wound tow, top, sliver, roving or yarn.

• Container or case: a shipping unit identified on the dispatch note, usually a carton, box, bale or other container which may or may not contain packages.

Fibre sampling from bulk

Zoning
Zoning is a method that is used for selecting samples from raw cotton or wool or other loose fibre where the properties may vary considerably from place to place. A handful of fibres is taken at random from each of at least 40 widely spaced places (zones) throughout the bulk of the consignment and is treated as follows. Each handful is divided into two parts and one half of it is discarded at random; the retained half is again divided into two and half of that discarded. This process is repeated until about nix fibres remain in the handful (where n is the total number of fibres required in the sample and x is the number of original handfuls). Each handful is treated in a similar manner and the fibres that remain are placed together to give a correctly sized test sample containing n fibres. The method is shown diagrammatically in Fig. 1. It is important that the whole of the final sample is tested.

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Fig:- Sampling by zoneing

Core sampling
Core sampling is a technique that is used for assessing the proportion of grease, vegetable matter and moisture in samples taken from unopened bales of raw wool. A tube with a sharpened tip is forced into the bale and a core of wool is withdrawn. The technique was first developed as core boring in which the tube was rotated by a portable electric drill. The method was then developed further to enable the cores to be cut by pressing the tube into the bale manually. This enables samples to be taken in areas remote from sources of power. The tubes for manual coring are 600mm long so that they can penetrate halfway into the bale, the whole bale being sampled by coring from both ends. A detachable cutting tip is used whose internal diameter is slightly smaller than that of the tube so that the cores will slide easily up the inside of the tube. The difference in diameter also helps retain the cores in the tube as it is withdrawn. To collect the sample the tube is entered in the direction of compression of the bale so that it is perpendicular to the layers of fleeces. A number of different sizes of nominal tube diameter are in use, 14, 15 and 18mm being the most common the weight of core extracted varying accordingly. The number of cores extracted is determined according to a sampling schedule and the cores are combined to give the required weight of sample. As the cores are removed they are placed immediately in an air-tight container to prevent any loss of moisture from them. The weight of the bale at the time of coring is recorded in order to calculate its total moisture content.

The method has been further developed to allow hydraulic coring by machine in warehouses where large numbers of bales are dealt with. Such machines compress the bale to 60% of its original length so as to allow the use of a tube which is long enough to core the full length of the bale.

Fibre sampling from combed slivers, rovings and yarn

One of the main difficulties in sampling fibres is that of obtaining a sample that is not biased. This is because unless special precautions are taken, the longer fibres in the material being sampled are more likely to be selected by the sampling procedures, leading to a length-biased sample. This is particularly likely to happen in sampling material such as sliver or yarn where the fibres are approximately parallel. Strictly speaking, it is the fibre extent as defined in Fig. 1.2 rather than the fibre length as such which determines the likelihood of selection. The obvious area where length bias must be avoided is in the measurement of fibre length, but any bias can also have effects when other properties such as fineness and strength are being measured since these properties often vary with the fibre length.

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Fig 2.:- The meaning of extenet

There are two ways of dealing with this problem:
1 Prepare a numerical sample (unbiased sample).
2 Prepare a length-biased sample in such a way that the bias can be allowed for in any calculation.

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Fig 3:- Selection of numerical sample

Numerical sample
In a numerical sample the percentage by number of fibres in each length group should be the same in the sample as it is in the bulk. In Fig.3, A and B represent two planes separated by a short distance in a sample consisting of parallel fibres. If all the fibres whose left-hand ends (shown as solid circles) lay between A and B were selected by some means they would constitute a numerical sample. The truth of this can be seen from the fact that if all the fibres that start to the left of A were removed then it would not alter the marked fibres. Similarly another pair of planes could be imagined to the right of B whose composition would be unaffected by the removal of the fibres starting between A and B. Therefore the whole length of the sample could be divided into such short lengths and there would be no means of distinguishing one length from another, provided the fibres
are uniformly distributed along the sliver. If the removal of one sample does not affect the composition of the remaining samples, then it can be considered to be a numerical sample and each segment is representative of the whole.

Length-biased sample
In a length-biased sample the percentage of fibres in any length group is proportional to the product of the length and the percentage of fibres of that length in the bulk. The removal of a length-biased sample changes the composition of the remaining material as a higher proportion of the longer fibres are removed from it.

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Fig4 :- selection of tuft sample

If the lines A and B in Fig. 3 represent planes through the sliver then the chance of a fibre crossing these lines is proportional to its length. If, therefore, the fibres crossing this area are selected in some way then the longer fibres will be preferentially selected. This can be achieved by gripping the sample along a narrow line of contact and then combing away any loose fibres from either side of the grips, so leaving a sample as depicted in Fig. 4 which is length-biased. This type of sample is also known as a tuft sample and a similar method is used to prepare cotton fibres for length measurement by the fibrograph. Figure  5 shows the fibre length histogram and mean fibre length from both a numerical sample and a length-biased sample prepared from the same material.

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Fig:5 Histogram of length based and numerical samples

By a similar line of reasoning if the sample is cut at the planes A and B the section between the planes will contain more pieces of the longer fibres because they are more likely to cross that section. If there are equal numbers of fibres in each length group, the total length of the group with the longest fibres will be greater than that of the other groups so that there will be a greater number of those fibres in the sample. Samples for the measurement of fibre diameter using the projection microscope are prepared in this manner by sectioning a bundle of fibres, thus giving a length-biased sample. The use of a length-biased sample is deliberate in this case so that the measured mean fibre diameter is then that of the total fibre length of the whole sample. If all the fibres in the sample are considered as being joined end to end the mean fibre diameter is then the average thickness of that fibre.

Random draw method
This method is used for sampling card sliver, ball sliver and top. The sliver to be sampled is parted carefully by hand so that the end to be used has no broken or cut fibres. The sliver is placed over two velvet boards with the parted end near the front of the first board. The opposite end of the sliver is weighed down with a glass plate to stop it moving as shown in Fig. 1.6. A wide grip which is capable of holding individual fibres is then used to remove and discard a 2mm fringe of fibres from the parted end. This procedure is repeated, removing and discarding 2mm draws of fibre until a distance equal to that of the longest fibre in the sliver has been removed. The sliver end has now been ‘normalised’ and any of the succeeding draws can be used to make up a sample as they will be representative of all fibre lengths. This is because they represent a numerical sample as described
above where all the fibres with ends between two lines are taken as the sample. When any measurements are made on such a sample all the fibres must be measured.

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Fig 6:- The random Draw method

Cut square method
This method is used for sampling the fibres in a yarn. A length of the yarn being tested is cut off and the end untwisted by hand. The end is laid on a small velvet board and covered with a glass plate. The untwisted end of the yarn is then cut about 5mm from the edge of the plate as shown in Fig. 7. All the fibres that project in front of the glass plate are removed one by one with a pair of forceps and discarded. By doing this all the cut fibres are removed, leaving only fibres with their natural length. The glass plate is then moved back a few millimetres, exposing more fibre ends. These are then removed one by one and measured. When these have all been measured the plate is moved back again until a total of 50 fibres have been measured. In each case once the plate has been moved all projecting fibre ends must be removed and measured. The whole process is then repeated on fresh lengths of yarn chosen at random from the bulk, until sufficient fibres have been measured.

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Fig7 :- The cut square method

Yarn sampling

When selecting yarn for testing it is suggested that ten packages are selected at random from the consignment. If the consignment contains more than five cases, five cases are selected at random from it. The test sample then consists of two packages selected at random from each case. If the consignment contains less than five cases, ten packages are selected at random from all the cases with approximately equal numbers from each case. The appropriate number of tests are then carried out on each package.

Fabric sampling

When taking fabric samples from a roll of fabric certain rules must be observed. Fabric samples are always taken from the warp and weft separately as the properties in each direction generally differ. The warp direction should be marked on each sample before it is cut out. No two specimens should contain the same set of warp or weft threads. This is shown diagrammatically in Fig. 8 where the incorrect layout shows two warp samples which contain the same set of warp threads so that their properties will be very similar. In the correct layout each sample contains a different set of warp threads so that their properties are potentially different depending on the degree of uniformity of the fabric. As it is the warp direction in this case that is being tested the use of the same weft threads is not important. Samples should not be taken from within 50mm of the selvedge as the fabric properties can change at the edge and they are no longer representative of the bulk.

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Fig 8:- Fabric Sampling

Standardisation Of Testing


When a textile material is tested certain things are expected from the results. Some of these are explicit but other requirements are implicit. The explicit requirements from the results are either that they will give an indication of how the material will perform in service or that they will show that it meets its specification. The implicit requirement from a test is that it is reproducible, that is if the same material is tested either at another time, or by another operator or in a different laboratory the same values will be obtained. In other words the test measures some ‘true’ or correct value of the property being assessed. If the test results vary from laboratory to laboratory then the test is not measuring anything real and it is pointless carrying it out. However, the values that are obtained from testing textile materials are not expected to be exactly the same, so that appropriate statistical criteria should be applied to the results to see whether they fall within the accepted spread of values.

The lack of reproducibility of test results can be due to a number of causes.

Variation in the material

Most textile materials are variable, natural fibres having the most variation in their properties. The variation decreases as the production progresses from fibres to yarns to fabrics, since the assembly of small variable units into larger units helps to smooth out the variation in properties. The problem of variable material can be dealt with by the proper selection of representative samples and the use of suitable statistical methods to analyse the results.

Variation caused by the test method

It is important that any variations due to the test itself are kept to the minimum. Variability from this source can be due to a number of causes:

1 The influence of the operator on the test results. This can be due to differences in adherence to the test procedures, care in the mounting of specimens, precision in the adjustment of the machine such as the zero setting and in the taking of readings.

2 The influence of specimen size on the test results, for instance the effect of specimen length on measured strength.

3 The temperature and humidity conditions under which the test is carried out. A number of fibres such as wool, viscose and cotton change their properties as the atmospheric moisture content changes.

4 The type and make of equipment used in the test. For instance pilling tests can be carried out using a pilling box or on the Martindale abrasion machine. The results from these two tests are not necessarily comparable.

5 The conditions under which the test is carried out such as the speed, pressure or duration of any of the factors.

It is therefore necessary even within a single organisation to lay down test procedures that minimise operator variability and set the conditions of test and the dimensions of the specimen. Very often in such cases, factors such as temperature, humidity and make of equipment are determined by what is available.

However, when material is bought or sold outside the factory there are then two parties to the transaction, both of whom may wish to test the material. It therefore becomes important in such cases that they both get the same result from testing the same material. Otherwise disputes would arise which could not be resolved because each party was essentially testing a different property.

This requires that any test procedures used by more than one organisation have to be more carefully specified, including, for instance, the temperature and humidity levels at which the test takes place. The details in the procedure have to be sufficient so that equipment from different manufacturers will produce the same results as one another. This need for standard written test methods leads to the setting up of national standards  for test procedures so making easier the buying and selling of textiles within that country. Even so certain large organisations, such as IWS or Marks and Spencer, have produced their own test procedures to which suppliers have to conform if they wish to carry the woolmark label or to sell to Marks and Spencer.

Most countries have their own standards organisations for example: BS (Britain), ASTM (USA) and DIN (Germany) standards. The same arguments that are used to justify national standards can also be applied to the need for international standards to assist world-wide trade, hence the existence of International Organization for Standardization (ISO) test methods and, within the European Union, the drive to European standards.

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Reasons For Textile Testing


The testing of textile products is an expensive business. A laboratory has to be set up and furnished with a range of test equipment. Trained operatives have to be employed whose salaries have to be paid throughout the year, not just when results are required. Moreover all these costs are non productive and therefore add to the final cost of the product. Therefore it is important that testing is not undertaken without adding some benefit to the final product.

There are a number of points in the production cycle where testing may be carried out to improve the product or to prevent sub-standard merchandise progressing further in the cycle.

Checking raw materials

The production cycle as far as testing is concerned starts with the delivery of raw material. If the material is incorrect or sub-standard then it is impossible to produce the required quality of final product.

The textile industry consists of a number of separate processes such as natural fibre production, man-made fibre extrusion, wool scouring, yarn spinning, weaving, dyeing and finishing, knitting, garment manufacture and production of household and technical products. These processes are very often carried out in separate establishments, therefore what is considered to be a raw material depends on the stage in processing at which the testing takes place. It can be either the raw fibre for a spinner, the yarn for a weaver
or the finished fabric for a garment maker. The incoming material is checked for the required properties so that unsuitable material can be rejected or appropriate adjustments made to the production conditions. The standards that the raw material has to meet must be set at a realistic level. If the standards are set too high then material will be rejected that is good enough for the end use, and if they are set too low then large amounts of inferior material will go forward into production.

Monitoring production

Production monitoring, which involves testing samples taken from the production line, is known as quality control. Its aim is to maintain, within known tolerances, certain specified properties of the product at the level at which they have been set. A quality product for these purposes is defined as one whose properties meets or exceeds the set specifications. Besides the need to carry out the tests correctly, successful monitoring of production also requires the careful design of appropriate sampling procedures and the use of statistical analysis to make sense of the results.

Assessing the final product

In this process the bulk production is examined before delivery to the customer to see if it meets the specifications. By its nature this takes place after the material has been produced. It is therefore too late to alter the production conditions. In some cases selected samples are tested and in other cases all the material is checked and steps taken to rectify faults. For instance some qualities of fabric are inspected for faulty places which are then mended by skilled operatives; this is a normal part of the process and the material would be dispatched as first quality.

Investigation of faulty material

If faulty material is discovered either at final inspection or through a customer complaint it is important that the cause is isolated. This enables steps to be taken to eliminate faulty production in future and so provide a better quality product. Investigations of faults can also involve the determination of which party is responsible for faulty material in the case of a dispute between a supplier and a user, especially where processes such as finishing have been undertaken by outside companies. Work of this nature is often contracted out to independent laboratories who are then able to give an unbiased opinion.

Product development and research

In the textile industry technology is changing all the time, bringing modified materials or different methods of production. Before any modified product reaches the market place it is necessary to test the material to check that the properties have been improved or have not been degraded by faster production methods. In this way an improved product or a lower-cost product with the same properties can be provided for the customer. A large organisation will often have a separate department to carry out research and development; otherwise it is part of the normal duties of the testing department.

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HIGH VOLUME INSTRUMENT SYSTEM


Uster Technologies
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The testing of fibres was always of importance to the spinner. It has been known for a long time that the fibre characteristics have a decisive impact on the running behaviour of the production machines, as well as on the yarn quality and manufacturing costs. In spite of the fact that fibre characteristics are very important for yarn production, the sample size for testing  fibre characteristics is not big enough. This is due to the following

  • The labour and time involvement for the testing of a representative sample was too expensive. The results were often available  much too late to  take corrective action.
  • The results often depended on the operator and / or the  instrument, and could therefore not be considered objective
  • One failed in trying to rationally administer the flood of the raw material data, to evaluate such data and to introduce the necessary corrective measures.

Only recently technical achievements have made possible the development of automatic computer-controlled testing equipment. With their use, it is possible to quickly determine the more important fibre characteristics.

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Recent developments in HVI technology are the result of requests made by textile manufacturers for additional and more precise fibre property  information. Worldwide competitive pressure on product price and product quality dictates close control of all resources used in the manufacturing process.

Historical Development of HVI:-

Conventionally measurement of the fibre properties was mainly carried out using manual method and it included the maximum chance of getting errors involved in it due to manual errors and was also a time consuming job. Thus there was a need for development of an instrument capable of measuring all properties in minimum time for better cotton classification.

PCCA (plans cotton cooperative association) played a key role in the development of High Volume Instrument (HVI) testing to determine the fibre properties of cotton which revolutionized the cotton and textile industries. As its name implies, HVI determines the fibre properties of a bale of cotton more quickly and more accurately than the previous method of evaluating some of those properties by hand classing. The HVI system provides more information about a bale of cotton than the subjective hand classing method.

In 1960, PCCA and Motion Control, Inc., an instrument manufacturer in Dallas, Texas, began pioneering the development of a system to eliminate the potential for human error that existed with hand classing and expand the number of fibre properties that could rapidly be determined for each bale of cotton. The goal was to be able to provide seven fibre quality characteristics for every bale produced by PCCA’s farmer-owners. Laboratory instruments were available for determining most of the fibre properties, but they required up to 15 minutes or longer to determine each of the properties. The PCCA theory was based on economics: the faster cotton could be classed, the faster it could be marketed; and, the more accurate measurements of quality could result in a more adequate supply of cotton with fibre properties to meet the specific needs of textile mills.

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fig1 :- Present day USDA cotton classing system.image

By the mid-1960s, the United States Department of Agricultural (USDA) and the Cotton Producers Institute (now called Cotton, Incorporated) also became involved in the research required to bring this concept to the marketplace.

In 1968 three of the first five HVI lines were in operation in Lubbock, Texas. One line was at Texas Tech University’s International Textile Center and two at PCCA. These lines were the very earliest versions to have all seven-fibre properties combined into a single testing line and measure them in less than 20 seconds per test.

In 1980, USDA built a new classing office in Lamesa, Texas, (about 60 miles south of Lubbock) specifically designed only for instrument testing all of the cotton samples received at that office using the latest version of the HVI equipment. This was a daring step but was based on data collected and analysed and improvements made in the HVI system during the previous 20 years. Although met with scepticism in the initial years by many in the cotton and textile industries, the HVI system prevailed, and USDA continued to install the instrument testing lines in all government cotton classing offices. In 1991, USDA used the HVI system on all the cotton provided to the department for classing. Today, HVI class data is accepted throughout the world and is the foundation on which cotton is traded.

Manufacturers:-

In total, there are five companies manufacturing rapid instrument testing machines in the world,

i. Uster technologies, Inc.,

ii. Premier Evolvics Pvt. Ltd.,

iii. Lintronics (China, Mainland)

iv. Changing Technologies (China, Mainland)

v. Statex Engineering (India).

High volume instrument (HVI) is the most common rapid instrument testing machine made by Uster Technologies, Inc. The only other company that has over 100 machines installed in the world, mostly in Asia, is Premier Evolvics Pvt. Ltd. based in India. It is estimated that close to 2,000 rapid instruments testing machines have already been stalled in the world, mostly from Uster Technologies, Inc. Not only do the machines from each company differ, but various models from each company also differ among themselves. The full fledge models of both the manufacturers are capable of measuring measure micronaire, length, length uniformity, strength, colour, trash, maturity, sugar content etc.

Principle:-

High volume instrument systems are based on the fibre bundle testing, i.e., many fibres are checked at the same time and their average values determined. Traditional testing using micronaire, pressley, stelometre, and fibro graph are designed to determine average value for a large number of fibres, the so called fibre bundle tests. In HVI, the bundle testing method is automated.

CONCEPTS IN BALE MANAGEMENT

This is based on the categorising of cotton bales according to their fibre quality characteristics. It includes the measurement of the fibre characteristics with reference to each individual bale, separation of bales into classes and lying down of balanced bale mixes based on these classes. The reason for undertaking this work lies in the fact that there is sometimes a considerable variation in the fibre characteristics from one bale to another, even within the same delivery. This variation will result in the yarn quality variation if the bales are mixed in an uncontrolled manner.

The bale management software, normally embedded with an HVI, helps in selection of bales for a particular mix from the available stock. Once the data are received from HVI in the software, classification of bales in groups are done with user defined criteria.image

· Manual calculation errors and the tedious task of day to day manual planning of mix are avoided.

· The storage of large number of data enables for tracking long period records or results thereby helping in clear analysis.

· More cost effective mix can be made since cost factor is also included. It also helps in planning for further requirements or purchase.

· Additional details such as party name, weighment details, and rejection details can be printed along with the test results which will be useful for the mill personnel for better analysis.

· Separate range criteria shall be selected for basic samples , lot samples and mixing

· Flexible intervals in grouping of bales with reference to the selected category.

· Basic sample results and results checked after lot arrival shall be compared graphically or numerically for easy decision making of approval or rejection.

Ø Information

The instruments are calibrated to read in staple length. Length measurements obtained from the instrument are considerably more repeatable than the staple length determination by the classer.  In one experiment the instrument repeated the same staple length determination 44% of the time while the classer repeated this determination only 29% of the time.  Similarly, the instrument repeated to 1/32″ on 76% of the samples, while the classer agreed on 71% of the samples to within 1/31″.

The precision of the HVI length measurement has been improved over the last few years. If we take the same bale of cotton used in the earlier example and repeatedly measure length with  an HVI system, over two-thirds of measurements will be  in a range of only about 1/32 nd of an inch: 95% of the individual readings will be within 1/32nd of an inch of the bale average. In the 77000 bales tested, the length readings were repeated within 0.02″ on 71% of the bales between laboratories.

Ø Length uniformity

The HVI system gives an indication of the fibre length distribution in the bale by use of a length uniformity index. This uniformity index is obtained by dividing the mean fibre length by the upper-half-mean length and expressing the ratio as a percent.  A reading of 80% is considered average length uniformity. Higher numbers mean better length uniformity and lower numbers poorer length uniformity. Cotton with a length uniformity index of 83 and above is considered to have good length uniformity, a length uniformity index below 78 is considered to show poor length uniformity.

Ø Short fibre index

The measure of short-fibre content (SFC) in Motion Control’s HVI systems is based on the fibre length distribution throughout the test specimen. It is not the staple length that is so important but the short fibre content which is important. It is better to prefer a lower commercial staple, but with much lower short-fibre content.

The following data were taken on yarns produced under identical conditions and whose cotton fibres were identical in all properties except for short-fibre content. The effects on ends down and several aspects of yarn quality are shown below.

LOT -A, (8.6% SFC) LOT-B (11.6% SFC)
Ends down / 1000 hrs 7.9 12.8
Skein strength (lb) 108.1 97.4
Single end strength g/tex 15 14.5
apperance index 106 89
Evenness (CV%) 16 17.3
Thin places 15 36
Thick places 229 364
Minor Defects 312 389

These results show that an increase of short-fibre content in cotton is detrimental to process efficiency and product quality. HVI systems measure length parameters of cotton samples by the fibrogram technique. The following assumptions describe the fibro gram sampling process: image

· The fibrogram sample is taken from some population of fibres.

· The probability of sampling a particular fibre is proportional to its length

· A sampled fibre will be held at a random point along its length

· A sampled fibre will project two ends away from the holding point, such that all of the ends will be parallel and aligned at the holding point.

· All fibres have the same uniform density

The High Volume Instruments also provide empirical equations of short fibre content based on the results of cotton produced in the United States in a particular year.

Short Fibre Index = 122.56 – (12.87 x UHM) – (1.22 x UI)

where UHM – Upper Half Mean Length (inches)
UI – Uniformity Index

Short Fibre Index = 90.34 – (37.47 x SL2) – (0.90 x UR)

Where SL2 – 2.5% Span length (inches)
UR – Uniformity Ratio

In typical fibrogram curve, the horizontal axis represents the lengths of the ends of sampled fibres. The vertical axis represents the percent of fibre ends in the fibrogram having that length or greater.

1. Strength and elongation:-

Ø Principle of measurement

HVI uses the “Constant rate of elongation” principle while testing the fibre sample. The available conventional methods of strength measurement are slow and are not compatible to be used with the HVI. The main hindering factor is the measurement of weight of the test specimen, which is necessary to estimate the tenacity of the sample. Expression of the breaking strength in terms of tenacity is important to make easy comparison between specimens of varying fineness.

Ø Method

The strength measurement made by the HVI systems is unlike the traditional laboratory measurements of Pressley and Stelometer in several important ways. First of all the test specimens are prepared in a very different manner. In the laboratory method the fibres are selected, combed and carefully prepared to align them in the jaw clamps. Each and every fibre spans the entire distance across the jaw surfaces and the space between the jaws.

Strength is measured physically by clamping a fibre bundle between 2 pairs of clamps at known distance. The second pair of clamps pulls away from the first pair at a constant speed until the fibre bundle breaks. The distance it travels, extending the fibre bundle before breakage, is reported as elongation.

In the HVI instruments the fibres are randomly selected and automatically prepared for testing. They are combed to remove loose fibres and to straighten the clamped fibres, also brushed to remove crimp before testing. The mechanization of the specimen preparation techniques has resulted in a “tapered” specimen where fibre ends are found in the jaw clamp surfaces as well as in the space between the jaws.

A second important difference between traditional laboratory strength measurements and HVI strength measurements is that in the laboratory measurements the mass of the broken fibres is determined by weighing the test specimen. In the HVI systems the mass is determined by the less direct methods of light absorption and resistance to air flow. The HVI strength mass measurement is further complicated by having to measure the mass at the exact point of breaks on the tapered specimen.

A third significant difference between laboratory and HVI strength measurements is the rate or speed at which the fibres are broken. The HVI systems break the fibres about 10 times faster than the laboratory methods.

Ø Information

Generally HVI grams per Tex readings are 1 to 2 units (3 to 5%) higher in numerical value. In some individual cases that seem to be related to variety, the differences can be as much as 6 to 8% higher. This has not caused a great deal of problems in the US, perhaps because a precedent was set many years ago when we began adjusting our Stelometer strength values about 27% to put them on Presley level.

Relative to the other HVI measurements, the strength measurement is less precise. Going back to our single bale of cotton and doing repeated measurements on the bale we shall find that 68% of the readings will be within 1 g/Tex of the bale average. So if the bale has an average strength of 25 g.tex, 68% of the individual readings will be between 24 and 26 g/Tex, and 95% between 23 and 27 g/Tex

Because of this range in the readings within a single bale, almost all HVI users make either 2 or 4 tests per bale and average the readings. When the average readings are repeated within a laboratory, the averages are repeated to within one strength unit about 80% of  the time. However, when comparisons are made between laboratories the agreement on individual bales to within plus or minus 1 g/tex decreases to 55%.

This decrease in strength agreement between laboratories is probably related to the difficulty of holding a constant relative humidity in the test labs. Test data indicate that 1% shift in relative humidity will shift the strength level about 1%. For example, if the relative humidity in the laboratory changes 3% (from 63 to 66%), the strength would change about 1 g/tex (from 24 to 25 g/Tex)

2. Fibre fineness:-image

Ø Principle of measurement

Fibre fineness is normally expressed as a micronaire value (microgram per inch). It is measured by relating airflow resistance to the specific surface of fibres and maturity ration is calculated using a sophisticated algorithm based on several HVI™ measurements.

Ø Method

The micronaire reading given by the HVI systems is the same as has been used in the commercial marketing of cotton for almost 25 years.  The repeatability of the data and the operator ease of performing the test have been improved slightly in the HVI micronaire measurement over the original instruments by elimination of the requirement of exactly weighing the test specimen. The micronaire instruments available today use microcomputers to adjust the reading for a range of test specimen sizes.

Ø Information

The micronaire reading is considered both precise and referable. For example, if we have a bale of cotton that has an average micronaire of 4.2 and repeatedly test samples from that bale, over two-thirds of that micronaire readings will be between 4.1 and 4.3 and 95 %of the readings between and 4.0 and 4.4. Thus, with only one or two tests per bale we can get a very precise measure of the average micronaire of the bale.

This reading is also very repeatable from laboratory to laboratory.  In USDA approx. 77000 bales were tested per day in each laboratory, micronaire measurements made in different laboratories agreed with each other within 0.1 micronaire units on 77% of the bales.

The reading is influenced by both fibre maturity and fibre fineness. For a given growing area, the cotton variety generally sets the fibre fineness, and the environmental factors control or influence the fibre maturity. Thus, within a growing area the micronaire value is usually highly related to the maturity value.  However, on an international scale, it cannot be known from the micronaire readings alone if cottons with different micronaire are of different fineness or if they have different maturity levels.

3. Moisture image

Ø Principle of measurement

Moisture content of the cotton sample at the time of testing, using conductive moisture probe and the main principle involved in the measurement is based on the measurement of the dielectric constant of a material.

4. Colour

Ø Principle of measurement

Rd (Whiteness), +b (Yellowness), Colour Grade

Measured optically by different colour filters, converted to USDA Upland or Pima Colour Grades or regional customized colour chart.

Ø Other information

The measurement of cotton colour predates the measurement of micronaire, but because colour has always been an important component of classer’s grade it has not received attention as an independent fibre property. However the measurement of colour was incorporated into the very early HVI systems as one of the primary fibre properties.

Determination of cotton colour requires the measurement of two properties, the grayness and yellowness of the fibres. The grayness is a measure of the amount of light reflected from the mass of the fibre. We call this the reflectance or Rd value. The yellowness is measured on what we call Hunter’s +b scale after the man who developed it. The other scales  that describe colour space (blue, red, green) are not measured becasue they are considered relatively constant for cotton.

Returning once again to the measurements  on our single bale, we see that repeated measurements of colour are in good agreement. For greyness or reflectance readings, 68% of the readings will be within 0.5 Rd units of the bale average, and 95% within one Rd unit for the average.

As for yellowness, over two-thirds of these readings will be within one-fourth of one +b unit of the average, and 95% within one-half of one +b unit. The greyness (Rd) and yellowness (+b) measurements are related to grade through a colour chart which was developed by a USDA researcher. The USDA test of 77000 bales showed the colour readings to be the most repeatable of all data between  laboratories; 87% of the bales repeated within one greyness(Rd) unit, and 85% repeated within one-half of one yellowness(+b) unit.

5. Trash content

Ø Principle of measurement

Particle Count, % Surface Area Covered by Trash, Trash Code

Measured optically by utilizing a digital camera, and converted to USDA trash grades or customized regional trash standards.

Ø Other information

The HVI systems measure trash or non-lint content by use of video camera to determine the amount of surface area of the sample that is covered with dark spots.  As the camera scans the surface of the sample, the video output drops when a dark spot (presumed to be trash) is encountered. The video signal is processed by a microcomputer to determine the number of dark spots encountered (COUNT) and the per cent of the surface area covered by the dark spots (AREA). The area and count data are used in an equation to predict the amount of visible non-lint content as measured on the Shirley Analyser. The HVI trash data output is a two-digit number which gives the predicted non-lint content for that bale. For example, a trash reading of 28 would mean that the predicted Shirley Analyser visible non-lint content of that bale would be 2.8%.

While the video trash instruments have been around for several years, but the data suggest that the prediction of non-lint content is accurate to about 0.75% non-lint, and that the measurements are repeatable 95% of the time to within 1% non-lint content.

6. Maturity and stickiness

Ø Principle of measurement

Calculated using a sophisticated algorithm based on several HVI™ measurements.

Ø Other information

Near infrared analysis provides a fast, safe and easy means to measure cotton maturity, fineness and sugar content at HVI speed without the need for time consuming sample preparation or fiber blending.

This technology is based on the near infrared reflectance spectroscopy principle in the wavelength range of 750 to 2500 nanometres. Differences of maturity in cotton fibres are recognized through distinctly different NIR absorbance spectra. NIR technology also allows for the measurement of sugar content by separating the absorbance characteristics of various sugars from the absorbance of cotton material.

Cotton maturity is the best indicator of potential dyeing problems in cotton products. Immature fibres do not absorb dye as well as mature fibres. This results in a variety of dye-related appearance problems such as barre, reduced colour yield, and white specks. Barre is an unwanted striped appearance in fabric, and is often a result of using yarns containing fibres of different maturity levels.  For dyed yarn, colour yield is diminished when immature fibres are used. White specks are small spots in the yarn or fabric which do not dye at all. These specks are usually attributed to neps (tangled clusters of very immature fibres)

NIR maturity and dye uptake in cotton yarns have been shown to correlate highly with maturity as measured by NIR.  A correlation of R=0.96 was obtained for a set of 15 cottons.

In a joint study by ITT and a European research organization, 45 cottons from four continents were tested for maturity using the NIR method and the SHIRLEY Development Fineness/ Maturity tester (FMT). For these samples, NIR and FMT maturity correlated very highly (R=0.94).

On 15 cottons from different growth areas of the USA, NIR maturity was found to correlate with r2 = 0.9 through a method developed by the United States Department of Agriculture (USDA).  In this method, fibres are cross-sectioned and microscopically evaluated.

Sugar Content is a valid indicator of potential processing problems. Near infrared analysis, because of its adaptability to HVI, allows for screening of bales prior to use. The information serves to selected bales to avoid preparation of cotton mixes of bales with excessive sugar content. Cotton stickiness consists of two major causes- honeydew form white flies and aphids and high level of natural plant sugars. Both are periodic problems which cause efficiency losses in yarn manufacturing.

The problems  with the randomly distributed honeydew contamination often results in costly production interruptions and requires immediate action often as severe as discontinuing the use of contaminated cottons.

Natural plant sugars are more evenly distributed and cause problems of residue build-up, lint accumulation and roll laps. Quality problems created by plant sugar stickiness are often more critical in the spinning process than the honeydew stickiness. Lint residues which accumulate on machine parts in various processes will break loose and become part of the fibre mass resulting in yarn imperfections. An effective way to control cotton stickiness in processing is to blend sticky and non-stick cottons. Knowing the sugar content of each bale of cotton used in each mix minimizes day-to-day variations in processing efficiency and products more consistent yarn quality. Screening the bale inventory for sugar content prior to processing will allow the selection of mixes with good processing characteristics while also utilizing the entire bale inventory.

The relationship between percent sugar content by NIR analysis and the Perkins method shows an excellent correlation of r2=0.95. The amount of reducing material on cotton fibre in the Perkins method is determined by comparing the reducing ability of the water extract of the fibre to that of a standard reducing substance. Using the NIR method, the amount of reducing sugar in cotton is measured.

Merits of HVI testing:-

· The results are practically independent of the operator.

· The results are based on large volume samples, and are therefore more significant.

· The time for testing per sample is 0.3 minutes. The respective fibre data are immediately available.

· About 180 samples per hour can be tested and that too with only 2 operators.

· The data are clearly arranged in summarised reports.

· They make possible the best utilisation of raw material data.

· It is best applied to instituting optimum condition for raw material.

· Problems as a result of fibre material can be predicted, and corrective measures instituted before such problems can occur.

· The classing of cotton and the laying down of a mix in the spinning mill. This HVI testing is suitable for the extensive quality control of all the bales processed in a spinning mill.

· The mill is in a position to determine its own quality level within a certain operating range.

Standardized process for hvi testing:-

image

· Pre-season precision and accuracy tests for all HVIs:-

All offices are required to select known-value cotton samples and perform stringent and consistent performance evaluations, before machines can be placed into production.

· Instrument calibration

Strict calibration procedures used by all offices and Quality Assurance Branch Known-value cottons and tiles used for calibration, Periodic calibration checks, Data is collected, analysed and corrective actions taken when necessary

· Quality Assurance Branch, Check lot Program

Approximately 1% of entire crop is selected from each field office for retest in “QA” as Check lots. Check lot data is returned to classing offices quickly for review. Check lot system assists in monitoring office performance and ensuring proper testing levels.

· Laboratory Atmospheric Conditions:-

Testing laboratories are required to maintain conditions of 70°±1° F and 65%±2% RH. All cotton must stabilize at moisture content level of 6.75%-8.25% prior to HVI testing.

Various HVI models available in market in present date are:-

· USTER® HVI 1000

· Available Options

• Barcode Reader (M700)

• UPS – Uninterrupted Power Supply device

• UV Module

• NEP Module

· ART 2-high volume fibre tester premier

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