A major breakthrough in global quality benchmarking for textiles came in October with the launch of the 2018 edition of USTER STATISTICS in a mobile app format. The app delivers a new user experience, with simple, intuitive handling.
What else is new with USTER STATISTICS 2018? Extended datasets and analyses, based on testing of many thousands of samples, cover a wider range of yarn types and applications than ever before. Iris Biermann, USTER’s Head of Textile Technologies, presents the major features and reveals valuable, profit-boosting insights for spinning mills in this special interview.
Excerpts:
The Textile Magazine: Which innovation in USTER STATISTICS 2018 are users already appreciating most?
Iris Biermann: The extended range for blended yarns has received only positive feedback. With the new mobile app, we are proud to present a virtually seamless blended yarn range. Users can enter their chosen blend ratio in 1% steps. After entering the ratio, the graph with relevant quality data is selected, based on an intelligent algorithm running in the background. This feature fulfills requests from many users for more coverage of blended yarn types in USTER STATISTICS.
The Textile Magazine: This is probably not the only new feature?
Iris Biermann: Far from it. For example, there is now a new distinction between AFIS seed coat neps and fiber neps, to optimize laydowns. These values mean spinners can also optimize efficiency in removing neps during further process steps, such as carding, as well as predicting more accurately the level of white spots on fabric after dyeing. As we know, the root cause of these white spots is a high level of fiber neps with a high proportion of immature fibers. The big advantage of reliably predicting the appearance of white spots – thanks to USTER STATISTICS 2018 – is to minimize the risk of claims.
The Textile Magazine: What other improvements can be achieved by studying the STATISTICS data?
Iris Biermann: For USTER STATISTICS 2018, we used a new source for sliver and roving data. These are now based on USTER TESTER generations 5 and 6. Personally I recommend greater use of the STATISTICS to evaluate sliver and roving quality, with respect to evenness. A finisher sliver with poor evenness will be incapable of producing a yarn with good evenness. We know this from general experience. From a low quality finisher sliver, a low quality roving will be produced, ending up with a yarn of low quality, based on the evenness level.
The Textile Magazine: So would that be the end of the story for this product?
Iris Biermann: Not exactly. Some collected samples did prove this, but from careful examination of all sample data, it is interesting that other finisher slivers – with a similar low quality – resulted in a medium quality rovings. In this case, we can conclude that the mill did a good job of processing the slivers. I assume they chose the perfect machine settings for drafting, for instance. And I’m convinced that their machine maintenance is at a high level, so that the top rollers are in optimum condition. To elaborate on this, the latest USTER NEWS BULLETIN No.51 shows examples of how spinners can benefit from the detailed sliver and roving data in USTER STATISTICS 2018.
The Textile Magazine: What other production benefits can spinning mills gain from the STATISTICS?
Iris Biermann: The HL sensor of USTER TESTER 6 offers new values which provide a clear business advantage, as there is a strong correlation between yarn hairiness and fabric behavior. If spinners compare the new hairiness values provided by the Tester with USTER STATISTICS 2018, they will, for example, obtain more sensitive indicators about traveller change cycles. Trials have shown that a mill can optimize traveller change cycles based on the S1+2u values – saving money and extending traveller working lifetimes. At the same time, the yarn quality stays consistent at the required level and fabric appearance does not change either.
The Textile Magazine: It’s clear that USTER STATISTICS offer great advantages to spinners. What makes them so important to the wider textile industry?
Iris Biermann: As with the very first edition in 1957, USTER STATISTICS still assists the industry to determine fair market prices for a given yarn quality. That’s a big help for yarn producers, yarn consumers and traders alike. The many years of meticulous testing of yarns – as well as fibers, slivers, rovings, cops and packages – generates data which means much more to the textile industry than just benchmarks. USTER data and USTER equipment make the perfect combination for managing a textile mill with quality in mind.