Still using the burning method to test fabric composition? Now there is a new method.

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Still using the burning method to test fabric composition? Now there is a new method. [Copy link]

 If you search the web for "how to determine what a fabric is made of," you'll probably find pages for "burn test." In a burn test, you take a small sample of fabric, place it over an open flame, observe if it shrinks, melts, or burns, and note the odor produced. However, Texas Instruments has come up with a new way, and it's amazing. Let's take a look. Now, with the TI DLP NIRscan Nano evaluation module (EVM) and the Sagitto system, it's easier and more accurate to determine the composition of fabrics and textiles. The Sagitto system combines miniature near-infrared sensors and machine learning models to help companies simplify the measurement process. Each type of fabric has a unique near-infrared fingerprint due to its different composition. Clothing often contains different types of fibers, and the precise composition of the composition is important throughout the use of clothing. See, it's easier and more accurate to determine the composition of fabrics and textiles. It seems that textile sellers will not be able to deceive our engineers in the future. As long as we take out the evaluation module and the Sagitto system, even the cunning merchants will not be able to escape the eyes of the law. How is such a magical measurement achieved? Let's take a look at the following introduction.

Many countries require textiles to be clearly labeled for their fiber composition. Sometimes these labels can be misleading. For example, in the image below we see a set of dish towels labeled 100% cotton, but tested by Sagitto and found to be a blend of 67% cotton and 33% polyester.

But why does fiber composition matter? It is estimated that 80 billion pieces of clothing are produced each year, of which 75% end up in landfill or incineration. Increasingly, consumers are demanding that large clothing retailers find alternative ways to deal with the large amounts of waste generated in the high-turnover fashion retail industry. Governments are also beginning to introduce regulations to encourage a “circular economy” and divert clothing from the garbage. Acrylic and polyester clothing can have a serious impact on the environment. For example, each wash cycle releases hundreds of thousands of microfibers into local wastewater treatment plants. Up to 40% of these microfibers may end up in rivers, lakes and oceans.

Therefore, the market urgently needs to develop new chemical recycling technologies for textiles. These recycling technologies require, for example, breaking down polyester and cotton clothing into their chemical constituents - cellulose fibers, polyester monomers and oligomers. But first, recyclers using chemical recycling need to accurately sort the raw materials by fiber composition. In traditional operations, employees usually sort waste textiles by feel and vision, that is, they determine the composition of textiles when they pick up each piece of clothing. Unfortunately, it is impossible for humans to accurately determine the composition of textiles containing fiber mixtures and meet the requirements of modern chemical recycling technologies. By integrating TI DLP NIRscan Nano into a robotic arm and adding sophisticated machine learning capabilities, it is possible to develop a precise robotic sorting system for chemical recycling plants. Sagitto combines DLP NIRscan Nano with cloud-based artificial intelligence. With Sagitto, you don't need to hire your own data scientists or even collect your own data to train machine learning models. Sagitto removes barriers such as equipment cost, skills and data, enabling a new class of manufacturers and producers to optimize production processes using the DLP NIRscan Nano EVM. With Sagitto artificial intelligence software and the DLP NIRscan Nano evaluation module, you can use a unique fabric composition demonstration model. Register on the Sagitto website and request access to a Sagitto demo account to make 50 free predictions using the DLP NIRscan Nano evaluation module. Texas Instruments is really a big manufacturer, always giving people surprises, I can't wait to get this set to play with it. It would be even better if the predictions were always free.

okhxyyo

Yes, it is true. Sometimes I buy clothes that are very expensive and I am afraid of being ripped off.

alan000345

okhxyyo posted on 2018-11-28 11:11 It is good. Sometimes I am afraid of being ripped off when buying clothes that are very expensive.

Yes, especially when buying clothes on Taobao, I have been ripped off many times. If this is okay, I will definitely buy one for fun. With this magic tool, I will no longer be afraid of being ripped off.