WO2014172796A1

WO2014172796A1 - Compiling and providing a global textile quality benchmark

Info

Publication number: WO2014172796A1
Application number: PCT/CH2014/000050
Authority: WO
Inventors: Sivakumar Narayanan
Original assignee: Uster Technologies Ag
Priority date: 2013-04-22
Filing date: 2014-04-17
Publication date: 2014-10-30

Abstract

Methods for compiling and providing a global textile quality benchmark related to a plurality of textile materials of same type located at different locations (21 -24) are disclosed. At least one piece of quality data is received for each of the plurality of textile materials via a global communications network (31-34). The received quality data are statistically processed so as to enable a cumulative frequency analysis. A result of the processing is stored as a global textile quality benchmark that can be transmitted via the global communications network (41 -43, 45). The resulting global textile quality benchmark is always up to date and increasingly comprehensive.

Description

COMPILING AND PROVIDING A GLOBAL TEXTILE QUALITY BENCHMARK

TECHNICAL FIELD

The present invention relates generally to textile quality control. More particularly, it relates to methods for compiling and providing a global textile quality benchmark, and to a corresponding computer software product and corresponding computer networks.

BACKGROUND ART

In textile industry, quality control is important in order to find the proper tradeoff between quality, productivity and costs. Quality is preferably controlled along the whole textile chain, including raw materials such as cotton fibers, intermediate products such as sliver, roving and yarn, and finished products such as fabric. The quality control can be performed online, i.e., during production, or offline, i.e.. in a textile laboratory. Many devices for monitoring and testing textile materials and measuring their physical parameters are known for this purpose. Examples are the following:

· USTER® 11 VI 1000 for offline analysis of cotton fibers; see "USTER® HVI 1000

The fiber classification and analysis system", Uster Technologies AG, 201 1 ;

• USTER* TESTER 5 for offline evenness testing of slivers and yarns; see "USTER^® TESTER 5 The yarn inspection system", Uster Technologies AG, 201 1 ;

• USTER* QUANTUM 3 for online quality assurance of yarns; see "USTER*

QUANTUM 3 - The yam quality assurance system", Uster Technologies AG, 201 1.

In order to compare the quality level of one textile mill with another's, a common "quality language" is needed. Worldwide accepted quality benchmarks or quality references in the textile industry are the USTER® STA TISTICS; see USTER® NEWS BULLETIN Ήο. 49, Uster Technologies AG, November 2012, or CD-ROM "USTER® STATISTICS 2013^", Version 1 .0, Uster Technologies AG, 2013. The USTER^® STATISTICS are a

comprehensive statistical survey of the quality of textile materials produced worldwide. They essentially contain statistical data in the form of graphs with percentile curves for numerous textile materials. These graphical cumulative frequency representations statistically indicate the extent by which a certain textile material is above or below a certain value. For instance, a percentile value of 25 % means that 25 % of the textile mills worldwide produce the respective product with the same or better quality. Numerical editions, in contrast to graphical, are also available. In order to compile the USTER* STATISTICS, the applicant of the present protective right collects a set of samples representative for the worldwide production of the respective textile product, tests them in his textile laboratory and statistically evaluates the test results. A new edition, which allows for new parameters, new measuring instruments, general quality changes and geographic shifts, is released roughly every five years. The results are available via the internet or on a CD-ROM. Although the USTER '¹ STATISTICS have a vital role as a means of adding value in the textile world, they have certain drawbacks. In today's dynamic economy, a five-year interval between two editions is quite long; a faster pace is, however, hardly possible due to the large efforts needed for a new edition. Moreover, the samples collected do not cover all markets and all types of textile materials. The USTER*

ST A TISTICS are valid only with those laboratory instruments with which they have been established, and online measurements are not covered. A further drawback is the limited number of samples, due to which it is not possible to give results for subsamples, e.g., for samples from a certain region only.

Expert systems for single textile mills are known. Such an expert system is a computer- implemented system which collects textile production data, including quality data, from the mill and statistically evaluates them. The results of the statistical evaluations are output in reports with clearly arranged graphical representations and/or numerical values. These reports help the mill managers to make informed choices about production processes, to guarantee quality and to reduce costs. An example of a textile expert system is USTER* QUANTUM EXPERT 3; see "USTER^® QUANTUM EXPERT 3 - The yarn quality assurance system^". Uster Technologies AG, 201 1. An expert system for a single textile mill is also described in CH-705^"443 A2.

US-2004/024484 Al discloses an economical communication structure for the monitoring of the workstations of a textile machine. The communication structure essentially consists of bus lines and controllers. Each yarn clearer f an open-end spinning machine is connected via the communication structure with a central quality evaluation unit. The central quality evaluation unit produces statistic data from the quality and/or control data received from the yarn clearers. For example, it calculates average or absolute quality schemata in the form of quality matrices, spectrograms, CV values and the like.

US-5'621 '637 A discloses a method of controlling the quality in the production of a plurality of yams in a corresponding number of processing stations which are similar to one another. All processing stations of the production line are equipped with measuring devices which each continuously detect a signal via measured values. The acquired data are transmitted to a central evaluation unit which detects an indication of the quality of the product in each processing station based on a quality value. The quality value may be determined by a comparison of the acquired data with predetermined desired values. An examination of individual typical signal patterns makes it possible to identify

malfunctioning machine components of the production line.

EP-0'622'481 Al solves the problem of diagnosing an abnormal state of a yam monitor in a spinning machine. The problem is solved by comparing the monitoring results of each yam monitor with the monitoring results of a plurality of other yam monitors. For this purpose, all yam monitors of a factory are connected via slave and master computers to a monitor computer. The monitor computer is connected to a host computer installed at a service center of a spinning machine maker via a telephone line. The host computer processes and analyzes data from the monitor computer and monitors all yarn monitors individually.

WO-02/1 1032 A 1 discloses a method for marketing cotton. A fiber quality measurement instrument located in a cotton gin provides fiber quality data concurrently with the making up of cotton into individual bales. The fiber quality measurement instrument is connected through a global communications network, such as the internet, for uploading fiber quality data to a database storage device. For electronic commerce, a search engine is connected via the global communications network to interrogate the database to select bales having fiber qualities within specified ranges for a candidate buyer.

US-201 1 /022491 8 A 1 deals with the detection of repeat defects in web manufacturing processes. Web material is produced at geographically distributed web manufacturing sites and shipped in the form of web rolls to converting sites. Defect information is detected at the web manufacturing sites and transmitted to a conversion control system via a network. Based on the defect information, the conversion control system defines a conversion plan for each web roll and communicates it to the appropriate converting site via the network.

SUMMARY OF INVENTION

It is the ob ject of the present invention to provide methods for compiling and providing a global textile quality benchmark, which methods reduce or eliminate the drawbacks of the USTER* STA TISTICS mentioned above. These and other objects are achieved by the methods as defined in the independent claims. Further independent claims are directed towards a corresponding computer software product and corresponding computer networks. Advantageous embodiments are prov ided in the dependent claims.

The invention suggests a completely new way of compiling the global textile quality benchmark. The quality data are generated in a decentralized manner, i.e., at the sites of various users which are located all over the world, rather than centrally at the provider's site. This yields a broader data pool that is always up-to-date. Suitable measurement devices are already at the users' sites, such that acquisitions of new measurement devices are not necessary. Only a connection between the provider and the users via a global communications network, such as the internet, is needed. The measurement devices are preferably online measurement devices, such as yarn clearers, which are connected directly or indirectly - e.g., via an expert system at the user's site - to the global communications network. Such online measurement devices generate large amounts of quality data which can form a sound basis for the statistical processing and evaluation.

The method according to the invention serves for compiling a global textile quality benchmark related to a plurality of textile materials of same type located at different locations. At least one piece of quality data is received for each of the plurality of textile materials via a global communications network, the received quality data are statistically processed so as to enable a cumulative frequency analysis, and evaluated result of the processing is stored as a global textile quality benchmark. In one embodiment, a further piece of quality data is received for a further textile material via the global communications network, the further piece of quality data is statistically processed together with quality data received earlier so as to enable a cumulative frequency analysis, and a result of the processing is stored as an updated global textile quality benchmark.

The statistical processing preferably comprises a generation of a cumulative frequency distribution and/or a cumulative probability distribution for the received quality data.

The textile materials are for instance textile fibers, slivers, rovings, yarns or fabrics. The at least one piece of quality data preferably is a quality parameter from the following set:

• for fibers: micronaire, upper half mean length, uniformity index, short fiber index, bundle tenacity, color, trash, spinning consistency index, neps count, length, maturity, trash;

• for slivers: mass variations;

• for rovings: count variations, mass variations;

• for yarns: count variations, mass variations, hairiness, imperfections, trash,

diameter variation, tensile properties, hairiness length, twist, yarn classification.

These parameters, their units, the devices with which they can be measured and the measurement conditions are described in detail in Chapter 3 of "USTER® STA TISTICS - Application Handbook^". Edition 2013, Uster Technologies AG, January 2013.

In one embodiment, for each of the plurality of textile materials at least one quality parameter is measured at the corresponding geographic location, the at least one piece of quality data is derived from the at least one measurement, and the at least one piece of quality data is transmitted via the global communications network for the purpose of being statistically processed together with other quality data. The at least one quality parameter can be measured by means of a measurement dev ice which is directly or indirectly connected to the global communications network for transmitting the at least one piece of quality data. The expression "indirectly connected^" means that the connection may be realized via a computer or a local-area network at the user's site. The at least one piece of quality data can be transmitted via the global communications network substantially concurrently with the measurement of the at least one quality parameter. In a preferred embodiment, the measurement device is an online measurement device for continuously monitoring the textile material during production, e.g., a yarn clearer. The at least one result of the statistical evaluation may be in the form of at least one graphical representation or of at least one numerical value.

In addition to the at least one quality infomiation, at least one descriptive piece of metadata is preferably received for each of the plurality of textile materials via the global communications network and allocated to the at least one piece of quality data. The piece of metadata is, for instance, chosen from the following set: date and time of measurement, geographic location, air temperature, air humidity, type of textile material, production process of textile material, intended use of textile material, geographic origin of textile material, type(s) of production machine(s) on which the textile material was produced, type of measurement device, settings of measurement device. in one embodiment the pieces of quality data received for at least two of the plurality of textile materials are compiled in a compilation and the compilation is outputted as a quality comparison. In another embodiment, the at least one piece of quality data received for one of the plurality of textile materials on the one hand and the global textile quality benchmark on the other hand are compared and the comparison is outputted as a quality comparison.

The computer software product according to the invention has a software code stored on a machine-readable carrier for carryin out the method described above when the computer software product runs on a computer.

The invention further relates to a method for providing a global textile quality benchmark related to a plurality of textile materials of same type located at different geographic locations. The global textile quality benchmark is compiled according to the method described above. The global textile quality benchmark is transmitted via the global communications network for performing the cumulative frequency analysis, or a request is received via the global communications network, the cumulative frequency analysis is performed and a result of the cumulative frequency analysis is returned via the global communications network.

In one embodiment, for each of the plurality of textile materials at: least one quality parameter is measured at the corresponding geographic location by means of a

measurement device which is directly or indirectly connected to the global

communications network for transmitting the at least one piece of quality data. The at least one piece of quality data is derived from the at least one measurement. The at least one piece of quality data is transmitted via the global communications network for the purpose of being statistically processed together with other quality data. The global textile quality benchmark is returned to at least one of the measurement devices via the global communications network and stored in said measurement dev ice for performing the cumulative frequency analysis. The invention also relates to a computer network for compiling a global textile quality benchmark related to a plurality of textile materials of same type located at different geographic locations. The computer network comprises a transmitter host computer located at each of the different locations, and a server computer connected to each of the transmitter host computers via a global communications network. The server computer is programmed for receiving from each of the host computers at least one piece of quality data for each of the plurality of textile materials, statistically processing the received quality data and storing a result of the processing as a global textile quality benchmark.

In one embodiment, at least one transmitter host computer is connected to at least one measurement device, from which the transmitter host computer receives the at least one piece of quality data. The at least one measurement device is preferably an online measurement device for continuously monitoring the textile material during production, e.g.. a yarn clearer. A still further aspect of the invention is a computer network for prov iding global textile quality data related to a plurality of textile materials of same type located at different geographic locations. The computer network comprises a transmitter host computer located at each of the different locations, at least one receiver host computer and a server comput er connected to each of the transmitter host computers and to the at least one receiver host computer via a global communications network. The server computer is programmed for receiving from each of the transmitter host computers at least one piece of quality data for each of the plurality of textile materials, statistically processing the received quality data, storing a result of the processing as a global textile qual ity benchmark, and transmitting the global textile quality benchmark via the global communications network to the at least one receiver host computer. Alternatively, the server computer is programmed for receiving a request from the at least one receiver host computer via the global communications network, performing the cumulative frequency analysis and returning a result of the cumulative frequency analysis to the at least one receiv er host computer via the global communications network.

The expression ..different geographic locations'" in the present document relates to locations that can unambiguously be distinguished from each other on a geographic scale. These can be for instance distinct continents, countries, regions, cities, towns or at least distinct production sites within a town. In order to give a physically measurable distinction criterion, we define for the purpose of the present document that the different geographic locations shall have a minimum distance of 1 km from each other. The prerequisite of the textile materials being located at different geographic locations implies that the at least one piece of quality data is generated by means of distinct measurement devices for each of the textile materials.

The terms "global" and "worldwide" are used synonymously throughout the present document.

BRIEF DESCRIPTION OF DRAWINGS

Preferred embodiments of the invention will be explained below by reference to the enclosed drawings.

Figure 1 shows a block diagram of a system for carrying out the methods according to the invention.

Figure 2 shows a detail of the diagram of Figure 1 . Figure 3 shows a cumulative frequency distribution and a cumulative probability distribution as can be used in the methods according to the invention.

Figure 4 shows a diagram with a global textile quality benchmark which can result from the method according to the invention.

DESCRIPTION OF EMBODIMENTS

Figure 1 schematically shows a provider 1 of a global textile statistical benchmark and several users 2 1 -25 of the benchmark. The provider 1 and the users 21 -25 are located at different geographic locations. Such different geographic locations may be, for instance, different continents, countries, regions, cities, towns or at least different production sites within one town. The users 21 -25 are. e.g., textile mills. In Figure 1 there are depicted five users 2 1 -25; this number is, of course, only an example and shall not limit the generality of the invention. Preferably there are a large number of users from all around the world. The provider 1 is connected with each user 2 1 -25 via a global communications network 31 -34, 4 1 -43. 45. such as the internet, at least in a star-shaped configuration.

A detail of the system of Figure 1 is schematically shown in Figure 2. A user 23 has at his site suitable devices 5 1 -56 (hereinafter called "the measurement devices") for monitoring or testing textile materials and measuring their physical quality parameters. The measurement devices 5 1 -56 may be online devices, such as yarn clearers, or laboratory devices, such as yarn testers. Online measurement devices are preferred, since they continuously monitor the quality of the textile materials during production and thus generate large amounts of quality data, which form a sound basis for the statistical evaluation described below. There may be online devices as well as laboratory devices at a user's 23 site. In the example of Figure 2, there are a plurality of yarn clearers 5 1 . 52 on a spinning machine 61 , a plurality of yarn clearers 53-55 on a winding machine 62 and a yarn tester 56 in a textile laboratory 63; of course, the numbers of measurement devices and machines will be larger in a textile mill than schematically shown in Figure 2.

The various measurement devices 5 1 -56 measure physical parameters of textile materials. They are connected via connections 71 -74, e.g., via a local area network, to a transmitter host computer 8, where they are temporarily stored. In many textile mills, online measurement devices are connected to an expert system such as USTER^® QUANTUM EXPERT 3. Such an expert system automatically collects textile production data, including quality data, from the mill, statistically evaluates them and creates reports from the statistical evaluation. The host computer 8 may be, but is not necessarily, a computer on which an expert system runs. In any case, the host computer 8 is connected via a connection 33, 43, which is part of the global communications network referred to in Figure 1 , to the provider 1. The measured parameters and/or data derived from them (hereinafter called "the measurement data") are transmitted via the connection 33 from the host computer 8 to the provider 1. Alternatively, the measurement data can be transmitted directly from the corresponding measurement device 51-56 to the provider 1. The data transmittal can be carried out continuously or from time to time. In the same manner, other users 21 , 22, 24 can transmit their measurement data to the provider 1 via connections 31 , 32, 34, as shown in Figure 1 .

In addition to the measurement data, descriptive metadata can be transmitted from the users 21-24 to the provider 1 via the global communications network. Such metadata can include, but are not limited to, the following: date and time of the measurement, geographic location, air temperature, air humidity, type of the textile material, further data of the textile material (which were not necessarily measured by the users 21 -24. but are known), production process of the textile material, intended use of the textile material, geographic origin of the textile material, type(s) of the production machine(s) on which the textile material was produced, type of the measurement device, settings of the

measurement device.

The transmitted data, including the measurement data and the corresponding metadata, are uploaded into a database and stored there by the provider 1. Databases as such are well- known and need not be further described here. The database must be suitable for storing, managing and dynamically handling large amounts of data, since it is continuously or frequently fed with data from the current worldwide textile production and grows every day. A statistical processing or evaluation of a plurality of measurement data is performed by the provider 1. The result of the processing is stored as a global textile quality benchmark that enables a cumulative frequency analysis. It can be, e.g., percentile values of a certain textile parameter (cf. Figure 4), related to measurement data of said parameter stored in the database. The statistical processing can be performed ahead, e.g., periodically, or on request by a user 21 -23, 25. It is performed automatically, e.g., by a computer software having access to the provider's 1 database.

The receipt of measurement data their statistical processing as described above is preferably not a singular event. It is rather an ongoing process in which new measurement data are permanently received, stored and processed together with measurement data received earlier. The resulting global textile quality benchmark is thus always up to date and increasingly comprehensive. Users 21 -23, 25 can retrieve the global textile quality benchmark from the provider 1 via connections 41 -43, 45, which are parts of the global communications network. The retrievable quality benchmark is always the result of the statistical processing described above. It is preferably possible to restrict the retrieval by using certain search terms and thus filtering the results. The search terms may include the metadata listed above.

However, in order to guarantee the anonymity of the users 21 -24, at least the resolution with respect to the user's 21 -24 geographic location should be limited to larger geographic entities such as whole countries. It should not be possible to derive from the benchmark conclusions on individual users, such as, "User 23 produced last month yarn with an unevenness of 1 2 % CV_m." For the retrieval, the provider 1 may provide a search mask, preferably displaying the search terms, to the users 21 -23, 25.

By way of example. Figure 1 shows three users 21 -23 who transmit their measurement data to the provider 1 and also retrieve benchmarks from the provider 1 . From the commercial point of view, such a bidirectional communication is the normal case, in the sense of a give-and-take basis. From the technical point of view, a unidirectional communication is, of course, possible. In the example of Figure 1 , a user 24 only transmits measurement data to the provider 1 , but does not retrieve any benchmarks from the provider 1 . On the other hand, another user 25 retrieves benchmarks from the provider 1 without transmitting any measurement data.

The statistical processing performed in the methods according to the invention is illustrated by means of Figure 3. The figure shows a diagram 1 10 in a two-dimensional Cartesian plane which is spanned by two axes 1 1 1 , 1 12. A first, horizontal axis 1 1 1 indicates a coefficient of variation of the yarn mass CV_m in percent. A second, vertical axis 1 12 indicates a cumulative frequency in percent. The quality data received from the different users 21-24 for the coefficient of mass variation CV_m and for a certain yarn type - for instance ring-spun cotton yarn with a yam count of Ne 30 - show a certain frequency distribution (not shown in Figure 3), e.g., a normal distribution. From this frequency distribution a cumulative frequency distribution 1 1 8 can be determined. Furthermore, a cumulative probabil ity distribution 1 19 can be determined, e.g., by fitting the cumulative frequency distribution 1 18. The cumulative frequency distribution 1 1 8 and/or the cumulative probability distribution 1 19 already constitute a simple textile quality benchmark resulting from the method according to the invention.

Figure 4 shows a diagram 120 with a more complex a global textile quality benchmark which can result from the method according to the invention. The diagram 120 lies in a two-dimensional Cartesian plane which is spanned by two axes 121 , 122. A first.

horizontal axis 121 indicates a yarn count, i.e., the length of 1 kg yarn or the inverse, in three different units. A second, vertical axis 122 indicates the coefficient of variation of the yarn mass CV_m in percent. The scales of both axes are preferably logarithmic. In the diagram five percentile curves 125-129 - straight lines in this example - arc drawn. For instance, 5 % of the tested samples had CV_m values (plotted against the corresponding yarn count) below the 5 % percentile line 125. The percentile curves 125-129 are generated from cumulative frequency distributions 1 18 and/or cumulative probability distributions 1 1 9 as shown in Figure 3, which have to be determined for at least two and preferably more than two different yarn counts.

The global textile quality benchmark plotted in the diagram 120 should preferably be tagged with descriptive metadata (not shown in Figure 4). In the example of Figure 4, such metadata could be the following: • Type: yarn

• Material: cotton, 100 %

• Process: ring spun, carded, bobbin

• Intended use: knitting

· Spinning machine: manufacturer MM, Type TT

• Measurement device: USTER® QUANTUM 3

• Measurement location: Asia

• Measurement time: 201 1 -2012.

These metadata can be used as search terms for retrieving the textile quality data plotted in the diagram 120.

In one embodiment, the quality data received from at least two of the plurality of users 21 - 24 can be compiled in a compilation. The compilation can for instance be a simple table showing comparable values of the quality data received, e.g., CV_m values for a certain yarn type. Alternatively, the compilation can be more detailed. The compilation is outputted as a quality comparison of the different textile materials at the locations 21 -24.

In another embodiment, the quality data received from one of the users 21 -24 on the one hand and the global textile quality benchmark on the other hand are compared. The result of such a comparison could for instance be a statement such as: "The Ne 30 yarn produced by the user 22 is on the 25 % percentile.^" The comparison is outputted as a quality comparison.

Instead of or in addition to a diagram such as shown in Figure 4, at least one numerical value could be provided as a result of the method according to the invention. The retrieval of numerical values is preferably interactive, i.e., the users 21 -23, 25 input certain input data and get in response certain output data. In addition to the search terms such as listed above, a user 21 -23, 25 could search for yarn parameters such as the following:

• Yarn count = Ne 20

• CV_m = 13 %.

Then, under the same prerequisites as in the example of Figure 4, the single numerical value 25 % (or 25^th percentile) results. The benchmark, such as the diagram 120 of Figure 4, can be provided to the users 21-23, 25 in various ways, some of which are listed in the following:

• The benchmark can be made available on a provider's 1 server, from where it can be downloaded by users 21 -23, 25 via the global communications network such as the internet.

• The benchmark can be integrated into an electronic-commerce (e- commerce)

software which can be accessed by users 21-23, 25 to enable trading and/or sourcing activities.

• The benchmark can be downloaded via the global communications network on a user's 21-23, 25 mobile devices such as smart phones or tablet computers, stored thereon and retrieved therefrom.

• The benchmark can be made available on social network platforms via the global communications network. In the example shown in Figure 2, the benchmark can be transmitted from the provider 1 via the connection 43 to the user's 23 transmitter host computer 8, and from there via the local connection 74 to the yarn tester 56. The yarn tester 56 can store the thus received benchmark and use it for benchmarking tested yarns in future tests. New measurement data can be transmitted via the connections 73, 33 to the provider, where they are processed for updating the benchmark, and so on. Thus, in this embodiment there is a loop or feedback between the provider 1 and the user 23, by which loop the benchmark as well as the testing results are continuously improv ed. Not only the yarn tester 56, but also other measurement devices such as the yarn clearers 51 -55 can be included into such a loop. A plurality of loops between the provider 1 and a plurality of users 21-23 can be established.

It is understood that the present invention is not limited to the embodiments discussed above. The person skilled in the art will be able to derive further variants with the knowledge of the invention which shall also belong to the subject matter of the present invention. LIST OF REFERENCE NUMERALS

1 Provider

21 -25 Users or their locations

31 -34 Connections for transmittal of piece of quality data

41 -43. 45 Connections for transmittal of a result of a quality benchmark

51 -56 Measurement devices

61 , 62 Textile production machines

63 Textile laboratory

71 -74 Local connections

8 Transmitter host computer

1 10 Diagram

1 1 1 Horizontal axis

1 12 Vertical axis

1 18 Cumulative frequency distribution

1 19 Cumulative probability distribution

120 Diagram

121 Horizontal axis

122 Vertical axis

125-129 Percentile curves

Claims

A method for compiling a global textile quality benchmark (1 10, 120) related to a plurality of textile materials of same type located at di fferent geographic locations (21 -24), wherein

at least one piece of quality data is received for each of the plurality of textile materials via a global communications network (31 -34),

the received quality data are statistically processed so as to enable a cumulative frequency analysis, and

a result of the processing is stored as a global textile quality benchmark (1 10, 120). The method according to claim 1 , wherein

a further piece of quality data is received for a further textile material via the global communications network (31 -34),

the further piece of quality data is statistically processed together with quality data received earlier so as to enable a cumulative frequency analysis, and

a result of the processing is stored as an updated global textile quality benchmark (1 10, 120).

The method according to any of the preceding claims, wherein the statistical processing comprises a generation of a cumulative frequency distribution (1 18) and/or a cumulative probability distribution (1 19) for the received quality data.

The method according to any of the preceding claims, wherein the textile materials are textile fibers, slivers, rovings, yarns or fabrics.

The method according to claim 4. wherein the at least one piece of quality data is a quality parameter from the following set:

for fibers: micronaire, upper half mean length, uniformity index, short fiber index, bundle tenacity, color, trash, spinnin consistency index, neps count. length, maturity, trash;

for slivers: mass variations;

for rovings: count variations, mass variations; for yarns: count variations, mass variations, hairiness, imperfections, trash, diameter variation, tensile properties, hairiness length, twist, yam classi fication.

6. The method according to any of the preceding claims, wherein for each of the

plurality of textile materials at least one quality parameter is measured at the corresponding geographic location (21 -24), the at least one piece of quality data is derived from the at least one measurement, and the at least one piece of quality data is transmitted via the global communications network (31 -34) for the purpose of being statistically processed together with other quality data.

7. The method according to claim 6, wherein the at least one quality parameter is

measured by means of a measurement device (5 1 -56) which is directly or indirectly connected to the global communications network (31 -34) for transmittin the at least one piece of quality data.

8. The method according to claim 7, wherein the at least one piece of quality data is transmitted via the global communications network (31 -34) substantially

concurrently with the measurement of the at least one quality parameter. 9. The method according to claim 7 or 8, wherein the measurement device is an online measurement device, such as a yarn clearer (51 -55), for continuously monitoring the textile material during production.

10. The method according to any of the preceding claims, wherein the result of the

statistical processing is stored in the form of at least one graphical representation

(120) or of at least one numerical value.

1 1. The method according to any of the preceding claims, wherein, in addition to the at least one piece of quality data, at least one descriptive piece of metadata is received for each of the plurality of textile materials via the global communications network

(31 -34) and allocated to the at least one piece of quality data. The method according to cl aim 1 1 , wherein the at least one piece of metadata is chosen from the following set: date and time of measurement, geographic location, air temperature, air humidity, type of textile material, production process of textile material, intended use of textile material, geographic origin of textile material, type or types of production machine or machines on which the textile material was produced, type of measurement device, settings of measurement device.

The method according to any of the preceding claims, wherein the pieces of quality data received for at least two of the plurality of textile materials are compiled in a compilation and the compilation is outputted as a quality comparison.

The method according to any of the preceding claims, wherein the at least one piece of quality data received for one of the plurality of textile materials on the one hand and the global textile quality benchmark ( 1 10, 120) on the other hand are compared and the comparison is outputted as a quality comparison.

A computer software product with a software code stored on a machine-readable earner for carrying out the method according to any of the preceding claims when the computer software product runs on a computer.

A method for providing a global textile quality benchmark (1 10, 120) related to a plurality of textile materials of same type located at different geographic locations (21 -24), wherein

the global textile quality benchmark (1 10, 120) is compiled according to any of the preceding claims, and

the global textile quality benchmark ( 1 10, 120)is transmitted via the global communications network (41 -43, 45) for performing the cumulative frequency analysis, or

a request is received via the global communications network (3 1 -33), the cumulative frequency analysis is performed and a result of the cumulative frequency analysis is returned via the global communications network (41 -43).

17. The method according to claim 16, wherein

for each of the plurality of textile materials at least one quality parameter is measured at the corresponding geographic location (23) by means of a measurement device (56) which is directly or indirectly connected to the global communications network (33) for transmitting the at least one piece of quality data.

the at least one piece of quality data is derived from the at least one measurement, the at least one piece of quality data is transmitted via the global communications network (33) for the purpose of being statistically processed together with other quality data, and

the global textile quality benchmark (1 10, 120) is returned to at least one of t he measurement devices (56) via the global communications network (43) and stored in said measurement device (56) for performing the cumulative frequency analysis.

A computer network for compiling a global textile quality benchmark (1 10, 120) related to a plurality of textile materials of same type located at different geographic locations (21 -24), comprising

a transmitter host computer (8) located at each of the different geographic locations (21 -24), and

a server computer connected to each of the transmitter host computers (8) via a global communications network (31 -34), which server computer is programmed for receiving from each of the host computers (8) at least one piece of quality data for each of the plurality of textile materials,

statistically processing the received quality data, and

storing a result of the processing as a global textile quality benchmark (110,

120).

19. The computer network according to claim 18, wherein at least one transmitter host computer (8) is connected to at least one measurement device (51 -56), from which the transmitter host computer (8) receives the at least one piece of quality data.

20. The computer network according to claim 19, wherein the at least one measurement device (51 -55) is an online measurement device, such as a yarn clearer (51-55), for continuously monitoring the textile material during production. A computer network for providing a global textile quality benchmark (1 10, 120) related to a plurality of textile materials of same type located at different geographic locations (21 -24), comprising

a transmitter host computer (8) located at each of the different geographic locations (21 -24),

at least one receiver host computer and

a server computer connected to each of the transmitter host computers (8) and to the at least one receiver host computer via a global communications network (31-34, 41- 43, 45), which server computer is programmed for

receiving from each of the transmitter host computers (8) at least one piece of quality data for each of the plurality of textile materials,

statistically processing the received quality data,

storing a result of the processing as a global textile quality benchmark (1 10, 120), and

transmitting the global textile quality benchmark (1 10, 120) via the global communications network (41-43, 45) to the at least one receiver host computer, or

receiving a request from the at least one receiver host computer via the global communications network (31-33), performing the cumulative frequency analysis and returning a result of the cumulative frequency analysis to the at least one receiver host computer via the global communications network (41-43).